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how do hypescalers describe their current level of compute v demand during their most recent earnings ?

I'll search the most recent earnings materials from major hyperscalers for their commentary on compute supply versus demand.

  1. Identify company

    Input

    { "query": "Amazon" }

    Output

    Company: AMAZON COM Ticker: AMZN Stock Quote: { "price": 220.07, "change_percentage": 1.71003, "change": 3.7, "volume": 35923144.0, "day_low": 217.04, "day_high": 220.67, "year_high": 242.52, "year_low": 161.38, "market_cap": 2347027205187.0, "price_avg_50": 225.6506, "price_avg_200": 214.4797, "open": 217.7, "previous_close": 216.37, "timestamp": "2025-10-13 16:00 EDT", "currency": "USD" } Latest Results: Q2 2025 results announced on 2025-08-01 Recent Earnings (12 periods): Format: [doc_type] | [title] | [date] | document_id | number_of_chunks Q2 2025: • 8-K | Item 2.02: Financial Results | 2025-07-31 | 6 | 19 chunks • earnings-slide | Q2 2025 | 2025-07-31 | 7 | 7 chunks • earnings-call-transcript | Q2 2025 | 2025-07-31 | 8 | 17 chunks • 10-Q | Q2 2025 | 2025-08-01 | 9 | 80 chunks Q1 2025: • 8-K | Item 2.02: Financial Results | 2025-05-01 | 10 | 17 chunks • earnings-slide | Q1 2025 | 2025-05-01 | 11 | 5 chunks • earnings-call-transcript | Q1 2025 | 2025-05-01 | 12 | 17 chunks • 10-Q | Q1 2025 | 2025-05-02 | 13 | 77 chunks FY 2024: • 8-K | Item 2.02: Financial Results | 2025-02-06 | 14 | 19 chunks • earnings-slide | Q4 2024 | 2025-02-06 | 15 | 6 chunks • earnings-call-transcript | Q4 2024 | 2025-02-06 | 16 | 20 chunks • 10-K | FY 2024 | 2025-02-07 | 17 | 127 chunks Q3 2024: • 8-K | Item 2.02: Financial Results | 2024-10-31 | 18 | 19 chunks • earnings-slide | Q3 2024 | 2024-10-31 | 19 | 6 chunks • earnings-call-transcript | Q3 2024 | 2024-10-31 | 20 | 13 chunks • 10-Q | Q3 2024 | 2024-11-01 | 21 | 184 chunks Q2 2024: • 8-K | Item 2.02: Financial Results | 2024-08-01 | 22 | 17 chunks • earnings-slide | Q2 2024 | 2024-08-01 | 23 | 8 chunks • earnings-call-transcript | Q2 2024 | 2024-08-01 | 24 | 13 chunks • 10-Q | Q2 2024 | 2024-08-02 | 25 | 77 chunks Q1 2024: • 8-K | Item 2.02: Financial Results | 2024-04-30 | 26 | 23 chunks • earnings-slide | Q1 2024 | 2024-04-30 | 27 | 7 chunks • earnings-call-transcript | Q1 2024 | 2024-04-30 | 28 | 14 chunks • 10-Q | Q1 2024 | 2024-05-01 | 29 | 73 chunks FY 2023: • 8-K | Item 2.02: Financial Results | 2024-02-01 | 30 | 25 chunks • earnings-slide | Q4 2023 | 2024-02-01 | 31 | 8 chunks • earnings-call-transcript | Q4 2023 | 2024-02-01 | 32 | 14 chunks • 10-K | FY 2023 | 2024-02-02 | 33 | 133 chunks Q3 2023: • 8-K | Item 2.02: Financial Results | 2023-10-26 | 34 | 25 chunks • earnings-slide | Q3 2023 | 2023-10-26 | 35 | 6 chunks • earnings-call-transcript | Q3 2023 | 2023-10-26 | 36 | 7 chunks • 10-Q | Q3 2023 | 2023-10-27 | 37 | 78 chunks Q2 2023: • 8-K | Item 2.02: Financial Results | 2023-08-03 | 38 | 23 chunks • earnings-call-transcript | Q2 2023 | 2023-08-03 | 39 | 13 chunks • earnings-slide | Q2 2023 | 2023-08-03 | 40 | 6 chunks • 10-Q | Q2 2023 | 2023-08-04 | 41 | 74 chunks Q1 2023: • 8-K | Item 2.02: Financial Results | 2023-04-27 | 42 | 25 chunks • earnings-call-transcript | Q1 2023 | 2023-04-27 | 43 | 9 chunks • earnings-slide | Q1 2023 | 2023-04-27 | 44 | 7 chunks • 10-Q | Q1 2023 | 2023-04-28 | 45 | 73 chunks FY 2022: • 8-K | Item 2.02: Financial Results | 2023-02-02 | 46 | 22 chunks • earnings-call-transcript | Q4 2022 | 2023-02-02 | 47 | 9 chunks • earnings-slide | Q4 2022 | 2023-02-02 | 48 | 4 chunks • 10-K | FY 2022 | 2023-02-03 | 49 | 118 chunks Q3 2022: • earnings-call-transcript | Q3 2022 | 2022-10-27 | 50 | 9 chunks • earnings-slide | Q3 2022 | 2022-10-27 | 51 | 7 chunks • 10-Q | Q3 2022 | 2022-10-28 | 52 | 78 chunks Other Recent Documents (5 per category): Events: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • 8-K | Item 5.07: Submission of Section 13(a) Matter | 2025-05-22 | 1 | 3 chunks • 8-K | Item 7.01: Regulation FD Disclosure | 2025-04-10 | 2 | 16 chunks • other-transcript | Goldman Sachs Communacopia + Technology Conference 2024 | 2024-09-09 | 3 | 12 chunks • 8-K | Item 5.07: Submission of Section 13(a) Matter | 2024-05-24 | 4 | 3 chunks • 8-K | Item 5.02: Leadership Changes | 2024-05-14 | 5 | 2 chunks [...] Proxies: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • DEFA14A | 2025-05-02 | 53 | 19 chunks • DEFA14A | 2025-04-10 | 54 | 2 chunks • DEF 14A | Proxy Statement | 2025-04-10 | 55 | 177 chunks • DEFA14A | 2024-05-03 | 56 | 22 chunks • DEF 14A | Proxy Statement | 2024-04-11 | 57 | 210 chunks [...] News: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • press-release | National Advertising Division Finds Certain Reus Cata-Kor NA... | 2025-10-13 | 206 | 3 chunks • news | Amazon Creates 250,000 Jobs Nationwide for Holiday Season | 2025-10-13 | 207 | 1 chunks • press-release | Design trifft Leistung: Tineco sorgt zum Prime Day für einen... | 2025-10-13 | 208 | 3 chunks • news | Former Justice Kennedy Critiques Supreme Court's Confrontati... | 2025-10-12 | 209 | 1 chunks • news | Israel Rejects UK's Role Claim in Gaza Ceasefire | 2025-10-12 | 210 | 1 chunks [...] Prospectuses & Registrations: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • S-3ASR | 2023-02-03 | 58 | 43 chunks • FWP | 2022-11-29 | 59 | 4 chunks • FWP | 2022-04-11 | 60 | 4 chunks • FWP | 2021-05-11 | 61 | 4 chunks • S-8 | Securities to be Offered to Employees | 2020-11-04 | 62 | 10 chunks [...]
  2. Identify company

    Input

    { "query": "Microsoft" }

    Output

    Company: MICROSOFT Ticker: MSFT Stock Quote: { "price": 514.05, "change_percentage": 0.60474, "change": 3.09, "volume": 14252086.0, "day_low": 511.68, "day_high": 516.41, "year_high": 555.45, "year_low": 344.79, "market_cap": 3821019177124.9995, "price_avg_50": 513.471, "price_avg_200": 453.9435, "open": 516.41, "previous_close": 510.96, "timestamp": "2025-10-13 16:00 EDT", "currency": "USD" } Latest Results: Q4 2025 results announced on 2025-07-30 Recent Earnings (12 periods): Format: [doc_type] | [title] | [date] | document_id | number_of_chunks FY 2025: • 8-K | Item 2.02: Financial Results | 2025-07-30 | 267 | 10 chunks • 10-K | FY 2025 | 2025-07-30 | 268 | 183 chunks • earnings-call-transcript | Q4 2025 | 2025-07-30 | 269 | 15 chunks Q3 2025: • 8-K | Item 2.02: Financial Results | 2025-04-30 | 270 | 10 chunks • 10-Q | Q3 2025 | 2025-04-30 | 271 | 90 chunks • earnings-call-transcript | Q3 2025 | 2025-04-30 | 272 | 15 chunks Q2 2025: • 8-K | Item 2.02: Financial Results | 2025-01-29 | 273 | 10 chunks • 10-Q | Q2 2025 | 2025-01-29 | 274 | 84 chunks • earnings-slide | Q2 2025 | 2025-01-29 | 275 | 10 chunks • earnings-call-transcript | Q2 2025 | 2025-01-29 | 276 | 18 chunks Q1 2025: • 8-K | Item 2.02: Financial Results | 2024-10-30 | 277 | 10 chunks • 10-Q | Q1 2025 | 2024-10-30 | 278 | 81 chunks • earnings-slide | Q1 2025 | 2024-10-30 | 279 | 15 chunks • earnings-call-transcript | Q1 2025 | 2024-10-30 | 280 | 19 chunks FY 2024: • 8-K | Item 2.02: Financial Results | 2024-07-30 | 281 | 11 chunks • 10-K | FY 2024 | 2024-07-30 | 282 | 203 chunks • earnings-slide | Q4 2024 | 2024-07-30 | 283 | 16 chunks • earnings-call-transcript | Q4 2024 | 2024-07-30 | 284 | 18 chunks Q3 2024: • 8-K | Item 2.02: Financial Results | 2024-04-25 | 285 | 10 chunks • 10-Q | Q3 2024 | 2024-04-25 | 286 | 85 chunks • earnings-slide | Q3 2024 | 2024-04-25 | 287 | 18 chunks • earnings-call-transcript | Q3 2024 | 2024-04-25 | 288 | 18 chunks Q2 2024: • 8-K | Item 2.02: Financial Results | 2024-01-30 | 289 | 10 chunks • 10-Q | Q2 2024 | 2024-01-30 | 290 | 90 chunks • earnings-slide | Q2 2024 | 2024-01-30 | 291 | 20 chunks • earnings-call-transcript | Q2 2024 | 2024-01-30 | 292 | 18 chunks Q1 2024: • 8-K | Item 2.02: Financial Results | 2023-10-24 | 293 | 10 chunks • 10-Q | Q1 2024 | 2023-10-24 | 294 | 78 chunks • earnings-slide | Q1 2024 | 2023-10-24 | 295 | 12 chunks • earnings-call-transcript | Q1 2024 | 2023-10-24 | 296 | 18 chunks FY 2023: • 8-K | Item 2.02: Financial Results | 2023-07-25 | 297 | 13 chunks • earnings-call-transcript | Q4 2023 | 2023-07-25 | 298 | 17 chunks • earnings-slide | Q4 2023 | 2023-07-25 | 299 | 12 chunks • 10-K | FY 2023 | 2023-07-27 | 300 | 142 chunks Q3 2023: • 10-Q | Q3 2023 | 2023-04-25 | 301 | 85 chunks • 8-K | Item 2.02: Financial Results | 2023-04-25 | 302 | 11 chunks • earnings-call-transcript | Q3 2023 | 2023-04-25 | 303 | 17 chunks • earnings-slide | Q3 2023 | 2023-04-25 | 304 | 12 chunks Q2 2023: • 10-Q | Q2 2023 | 2023-01-24 | 305 | 83 chunks • 8-K | Item 2.02: Financial Results | 2023-01-24 | 306 | 12 chunks • earnings-call-transcript | Q2 2023 | 2023-01-24 | 307 | 17 chunks • earnings-slide | Q2 2023 | 2023-01-24 | 308 | 19 chunks Q1 2023: • 10-Q | Q1 2023 | 2022-10-25 | 309 | 91 chunks • 8-K | Item 2.02: Financial Results | 2022-10-25 | 310 | 12 chunks • earnings-call-transcript | Q1 2023 | 2022-10-25 | 311 | 17 chunks • earnings-slide | Q1 2023 | 2022-10-25 | 312 | 17 chunks [... more periods available] Other Recent Documents (5 per category): Events: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • 8-K | Item 5.02: Leadership Changes | 2025-09-30 | 257 | 2 chunks • other-transcript | Goldman Sachs Communicopia + Technology Conference 2025 | 2025-09-10 | 258 | 11 chunks • other-transcript | Deutsche Bank's 2025 Technology Conference | 2025-08-28 | 259 | 9 chunks • 8-K | Item 5.03: Non-Reliance Notice | 2025-07-01 | 260 | 25 chunks • other-transcript | 2025-03-04 | 261 | 17 chunks [...] Proxies: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • DEF 14A | Proxy Statement | 2024-10-24 | 119 | 120 chunks • DEFA14A | 2024-10-24 | 120 | 5 chunks • DEFA14A | 2023-10-19 | 121 | 5 chunks • DEF 14A | Proxy Statement | 2023-10-19 | 122 | 115 chunks • DEF 14A | Proxy Statement | 2022-10-27 | 123 | 140 chunks [...] News: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • press-release | Nerdio Extends Leadership in Enhancing Windows 365 Managemen... | 2025-10-13 | 124 | 2 chunks • news | Wayve Seeks $2B Funding from Microsoft, SoftBank to Boost Va... | 2025-10-13 | 125 | 1 chunks • press-release | GPTBots Showcases Comprehensive Enterprise AI Solutions Alig... | 2025-10-13 | 126 | 2 chunks • press-release | Media Monitoring Tools Market Set for Robust Growth, Project... | 2025-10-13 | 127 | 4 chunks • news | LSEG Microsoft Partnership Enhances AI-Ready Financial Data ... | 2025-10-13 | 128 | 1 chunks [...] Prospectuses & Registrations: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • S-3ASR | 2024-12-12 | 181 | 76 chunks • EFFECT | 2024-05-06 | 182 | 1 chunks • S-4 | Merger/Acquisition Registration | 2024-04-26 | 183 | 70 chunks • S-3ASR | 2021-12-10 | 184 | 63 chunks • EFFECT | 2021-03-04 | 185 | 1 chunks [...]
  3. Identify company

    Input

    { "query": "Google" }

    Output

    Company: Alphabet Ticker: GOOGL Aliases: GOOGL, GOOG Stock Quote: { "price": 244.15, "change_percentage": 3.20413, "change": 7.58, "volume": 24450526.0, "day_low": 239.71, "day_high": 244.38, "year_high": 256.0, "year_low": 140.53, "market_cap": 2952889794328.9995, "price_avg_50": 225.8386, "price_avg_200": 187.75185, "open": 240.21, "previous_close": 236.57, "timestamp": "2025-10-13 16:00 EDT", "currency": "USD" } Latest Results: Q2 2025 results announced on 2025-07-24 Recent Earnings (12 periods): Format: [doc_type] | [title] | [date] | document_id | number_of_chunks Q2 2025: • 8-K | Item 2.02: Financial Results | 2025-07-23 | 83 | 12 chunks • 10-Q | Q2 2025 | 2025-07-24 | 84 | 66 chunks Q1 2025: • 8-K | Item 2.02: Financial Results | 2025-04-24 | 85 | 12 chunks • earnings-call-transcript | Q1 2025 | 2025-04-24 | 86 | 17 chunks • 10-Q | Q1 2025 | 2025-04-25 | 87 | 60 chunks FY 2024: • 8-K | Item 2.02: Financial Results | 2025-02-04 | 88 | 14 chunks • earnings-call-transcript | Q4 2024 | 2025-02-04 | 89 | 18 chunks • 10-K | FY 2024 | 2025-02-05 | 90 | 151 chunks Q3 2024: • 8-K | Item 2.02: Financial Results | 2024-10-29 | 91 | 12 chunks • earnings-call-transcript | Q3 2024 | 2024-10-29 | 92 | 19 chunks • 10-Q | Q3 2024 | 2024-10-30 | 93 | 65 chunks Q2 2024: • 8-K | Item 2.02: Financial Results | 2024-07-23 | 94 | 12 chunks • earnings-call-transcript | Q2 2024 | 2024-07-23 | 95 | 19 chunks • 10-Q | Q2 2024 | 2024-07-24 | 96 | 62 chunks Q1 2024: • 8-K | Item 2.02: Financial Results | 2024-04-25 | 97 | 14 chunks • earnings-call-transcript | Q1 2024 | 2024-04-25 | 98 | 20 chunks • 10-Q | Q1 2024 | 2024-04-26 | 99 | 112 chunks FY 2023: • 8-K | Item 2.02: Financial Results | 2024-01-30 | 100 | 13 chunks • earnings-call-transcript | Q4 2023 | 2024-01-30 | 101 | 17 chunks • 10-K | FY 2023 | 2024-01-31 | 102 | 159 chunks Q3 2023: • 8-K | Item 2.02: Financial Results | 2023-10-24 | 103 | 12 chunks • earnings-call-transcript | Q3 2023 | 2023-10-24 | 104 | 17 chunks • 10-Q | Q3 2023 | 2023-10-25 | 105 | 63 chunks Q2 2023: • 8-K | Item 2.02: Financial Results | 2023-07-25 | 106 | 13 chunks • earnings-call-transcript | Q2 2023 | 2023-07-25 | 107 | 17 chunks • 10-Q | Q2 2023 | 2023-07-26 | 108 | 89 chunks Q1 2023: • 8-K | Item 2.02: Financial Results | 2023-04-20 | 109 | 7 chunks • 8-K | Item 2.02: Financial Results | 2023-04-25 | 110 | 12 chunks • earnings-call-transcript | Q1 2023 | 2023-04-25 | 111 | 17 chunks • 10-Q | Q1 2023 | 2023-04-26 | 112 | 54 chunks FY 2022: • 8-K | Item 2.02: Financial Results | 2023-02-02 | 113 | 13 chunks • earnings-call-transcript | Q4 2022 | 2023-02-02 | 114 | 17 chunks • 10-K | FY 2022 | 2023-02-03 | 115 | 163 chunks Q3 2022: • 8-K | Item 2.02: Financial Results | 2022-10-25 | 116 | 42 chunks • earnings-call-transcript | Q3 2022 | 2022-10-25 | 117 | 17 chunks • 10-Q | Q3 2022 | 2022-10-26 | 118 | 65 chunks [... more periods available] Other Recent Documents (5 per category): Events: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • 8-K | Item 8.01: Other Events | 2025-09-05 | 176 | 2 chunks • 8-K | Item 8.01: Other Events | 2025-09-03 | 177 | 2 chunks • 8-K | Item 8.01: Other Events | 2025-07-18 | 178 | 18 chunks • 8-K | Item 5.07: Submission of Section 13(a) Matter | 2025-06-12 | 179 | 3 chunks • other-transcript | 2025-05-15 | 180 | 23 chunks [...] Proxies: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • DEFA14A | 2025-04-25 | 252 | 2 chunks • DEF 14A | Proxy Statement | 2025-04-25 | 253 | 111 chunks • DEF 14A | Proxy Statement | 2024-04-26 | 254 | 115 chunks • DEFA14A | 2024-04-26 | 255 | 1 chunks • DEFA14A | 2023-04-21 | 256 | 1 chunks [...] News: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • press-release | Reimagining Education: How AI Can Teach Kids to Think Again | 2025-10-13 | 247 | 3 chunks • press-release | Digital Marketing Market Global Forecast 2025-2030, Profiles... | 2025-10-10 | 248 | 3 chunks • press-release | Imaging Radar for Autonomous Systems Patent Landscape Analys... | 2025-10-10 | 249 | 5 chunks • news | Gap Launches Multi-Year AI Partnership with Google Cloud | 2025-10-09 | 250 | 1 chunks • news | Alphabet Plans €5B Belgium AI Infrastructure Expansion, Adds... | 2025-10-08 | 251 | 1 chunks [...] Prospectuses & Registrations: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • FWP | 2025-04-29 | 262 | 6 chunks • FWP | 2025-04-28 | 263 | 5 chunks • S-3ASR | 2025-04-25 | 264 | 78 chunks • S-8 | Securities to be Offered to Employees | 2023-07-26 | 265 | 9 chunks • S-8 | Securities to be Offered to Employees | 2022-07-27 | 266 | 6 chunks [...]
  4. Identify company

    Input

    { "query": "Meta" }

    Output

    Company: Meta Platforms Ticker: META Stock Quote: { "price": 715.7, "change_percentage": 1.47455, "change": 10.4, "volume": 9208366.0, "day_low": 707.6413, "day_high": 719.94, "year_high": 796.25, "year_low": 479.8, "market_cap": 1797977992275.0, "price_avg_50": 752.422, "price_avg_200": 669.9162, "open": 713.01, "previous_close": 705.3, "timestamp": "2025-10-13 16:00 EDT", "currency": "USD" } Latest Results: Q2 2025 results announced on 2025-07-31 Recent Earnings (12 periods): Format: [doc_type] | [title] | [date] | document_id | number_of_chunks Q2 2025: • 8-K | Item 2.02: Financial Results | 2025-07-30 | 129 | 11 chunks • earnings-slide | Q2 2025 | 2025-07-30 | 130 | 16 chunks • earnings-call-transcript | Q2 2025 | 2025-07-30 | 131 | 18 chunks • 10-Q | Q2 2025 | 2025-07-31 | 132 | 232 chunks Q1 2025: • 8-K | Item 2.02: Financial Results | 2025-04-30 | 133 | 11 chunks • earnings-slide | Q1 2025 | 2025-04-30 | 134 | 17 chunks • earnings-call-transcript | Q1 2025 | 2025-04-30 | 135 | 17 chunks • 10-Q | Q1 2025 | 2025-05-01 | 136 | 140 chunks FY 2024: • 8-K | Item 2.02: Financial Results | 2025-01-29 | 137 | 12 chunks • earnings-slide | Q4 2024 | 2025-01-29 | 138 | 17 chunks • earnings-call-transcript | Q4 2024 | 2025-01-29 | 139 | 20 chunks • 10-K | FY 2024 | 2025-01-30 | 140 | 208 chunks Q3 2024: • 8-K | Item 2.02: Financial Results | 2024-10-30 | 141 | 12 chunks • earnings-slide | Q3 2024 | 2024-10-30 | 142 | 17 chunks • earnings-call-transcript | Q3 2024 | 2024-10-30 | 143 | 16 chunks • 10-Q | Q3 2024 | 2024-10-31 | 144 | 143 chunks Q2 2024: • 8-K | Item 2.02: Financial Results | 2024-07-31 | 145 | 12 chunks • earnings-slide | Q2 2024 | 2024-07-31 | 146 | 18 chunks • earnings-call-transcript | Q2 2024 | 2024-07-31 | 147 | 17 chunks • 10-Q | Q2 2024 | 2024-08-01 | 148 | 152 chunks Q1 2024: • 8-K | Item 2.02: Financial Results | 2024-04-24 | 149 | 10 chunks • earnings-slide | Q1 2024 | 2024-04-24 | 150 | 17 chunks • earnings-call-transcript | Q1 2024 | 2024-04-24 | 151 | 17 chunks • 10-Q | Q1 2024 | 2024-04-25 | 152 | 187 chunks FY 2023: • 8-K | Item 2.02: Financial Results | 2024-02-01 | 153 | 15 chunks • earnings-slide | Q4 2023 | 2024-02-01 | 154 | 21 chunks • earnings-call-transcript | Q4 2023 | 2024-02-01 | 155 | 16 chunks • 10-K | FY 2023 | 2024-02-02 | 156 | 195 chunks Q3 2023: • 8-K | Item 2.02: Financial Results | 2023-10-25 | 157 | 13 chunks • earnings-slide | Q3 2023 | 2023-10-25 | 158 | 26 chunks • earnings-call-transcript | Q3 2023 | 2023-10-25 | 159 | 15 chunks • 10-Q | Q3 2023 | 2023-10-26 | 160 | 129 chunks Q2 2023: • 8-K | Item 2.02: Financial Results | 2023-07-26 | 161 | 13 chunks • earnings-call-transcript | Q2 2023 | 2023-07-26 | 162 | 14 chunks • earnings-slide | Q2 2023 | 2023-07-26 | 163 | 23 chunks • 10-Q | Q2 2023 | 2023-07-27 | 164 | 124 chunks Q1 2023: • 8-K | Item 2.02: Financial Results | 2023-04-26 | 165 | 11 chunks • earnings-call-transcript | Q1 2023 | 2023-04-26 | 166 | 15 chunks • earnings-slide | Q1 2023 | 2023-04-26 | 167 | 22 chunks • 10-Q | Q1 2023 | 2023-04-27 | 168 | 192 chunks FY 2022: • 8-K | Item 2.02: Financial Results | 2023-02-01 | 169 | 14 chunks • earnings-call-transcript | Q4 2022 | 2023-02-01 | 170 | 17 chunks • earnings-slide | Q4 2022 | 2023-02-01 | 171 | 24 chunks • 10-K | FY 2022 | 2023-02-02 | 172 | 229 chunks Q3 2022: • earnings-call-transcript | Q3 2022 | 2022-10-26 | 173 | 15 chunks • earnings-slide | Q3 2022 | 2022-10-26 | 174 | 27 chunks • 10-Q | Q3 2022 | 2022-10-27 | 175 | 126 chunks Other Recent Documents (5 per category): Events: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • other-transcript | Connect 2025 | 2025-09-18 | 63 | 13 chunks • other-transcript | Goldman Sachs Communicopia + Technology Conference 2025 | 2025-09-09 | 64 | 13 chunks • 8-K | Item 9.01: Financial Exhibits | 2025-05-30 | 65 | 5 chunks • other-transcript | AGM 2025 | 2025-05-28 | 66 | 21 chunks • 8-K | Item 5.02: Leadership Changes | 2025-04-11 | 67 | 5 chunks [...] Proxies: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • DEFA14A | 2025-04-17 | 78 | 1 chunks • DEF 14A | Proxy Statement | 2025-04-17 | 79 | 162 chunks • DEFA14A | 2024-04-19 | 80 | 1 chunks • DEF 14A | Proxy Statement | 2024-04-19 | 81 | 179 chunks • PRE 14A | Preliminary Proxy Statement | 2024-03-29 | 82 | 177 chunks [...] News: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • news | Instagram explores dedicated TV app amid Reels expansion | 2025-10-09 | 73 | 1 chunks • news | Graphcore Plans $1.3B India Investment, Bengaluru AI Hub, 50... | 2025-10-09 | 74 | 1 chunks • news | Indonesia Suspends Then Restores TikTok License After Data S... | 2025-10-06 | 75 | 1 chunks • news | Dutch Court Orders Meta to Offer Algorithm-Free Timelines to... | 2025-10-02 | 76 | 1 chunks • press-release | Meta to Announce Third Quarter 2025 Results | 2025-10-01 | 77 | 1 chunks [...] Prospectuses & Registrations: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • FWP | 2024-08-07 | 68 | 2 chunks • S-3ASR | 2023-05-01 | 69 | 44 chunks • FWP | 2023-05-01 | 70 | 3 chunks • S-8 | Securities to be Offered to Employees | 2023-03-01 | 71 | 6 chunks • EFFECT | 2022-11-23 | 72 | 1 chunks [...]
  5. Identify company

    Input

    { "query": "Oracle" }

    Output

    Company: ORACLE Ticker: ORCL Stock Quote: { "price": 308.01, "change_percentage": 5.13722, "change": 15.05, "volume": 21140437.0, "day_low": 297.74, "day_high": 310.7, "year_high": 345.72, "year_low": 118.86, "market_cap": 864061872002.0, "price_avg_50": 266.9708, "price_avg_200": 197.05576, "open": 298.7, "previous_close": 292.96, "timestamp": "2025-10-13 16:00 EDT", "currency": "USD" } Latest Results: Q1 2026 results announced on 2025-09-10 Recent Earnings (12 periods): Format: [doc_type] | [title] | [date] | document_id | number_of_chunks Q1 2026: • 8-K | Item 2.02: Financial Results | 2025-09-09 | 211 | 15 chunks • earnings-call-transcript | Q1 2026 | 2025-09-09 | 212 | 12 chunks • 10-Q | Q1 2026 | 2025-09-10 | 213 | 66 chunks FY 2025: • 8-K | Item 2.02: Financial Results | 2025-06-11 | 214 | 18 chunks • earnings-call-transcript | Q4 2025 | 2025-06-11 | 215 | 11 chunks • 10-K | FY 2025 | 2025-06-18 | 216 | 162 chunks Q3 2025: • 8-K | Item 2.02: Financial Results | 2025-03-10 | 217 | 19 chunks • earnings-call-transcript | Q3 2025 | 2025-03-10 | 218 | 11 chunks • 10-Q | Q3 2025 | 2025-03-11 | 219 | 62 chunks Q2 2025: • 8-K | Item 2.02: Financial Results | 2024-12-09 | 220 | 18 chunks • earnings-call-transcript | Q2 2025 | 2024-12-09 | 221 | 10 chunks • 10-Q | Q2 2025 | 2024-12-10 | 222 | 60 chunks Q1 2025: • 8-K | Item 2.02: Financial Results | 2024-09-09 | 223 | 13 chunks • earnings-call-transcript | Q1 2025 | 2024-09-09 | 224 | 12 chunks • 10-Q | Q1 2025 | 2024-09-10 | 225 | 52 chunks FY 2024: • 8-K | Item 2.02: Financial Results | 2024-06-11 | 226 | 17 chunks • earnings-call-transcript | Q4 2024 | 2024-06-11 | 227 | 13 chunks • 10-K | FY 2024 | 2024-06-20 | 228 | 262 chunks Q3 2024: • 8-K | Item 2.02: Financial Results | 2024-03-11 | 229 | 18 chunks • earnings-call-transcript | Q3 2024 | 2024-03-11 | 230 | 11 chunks • 10-Q | Q3 2024 | 2024-03-12 | 231 | 58 chunks Q2 2024: • 8-K | Item 2.02: Financial Results | 2023-12-11 | 232 | 16 chunks • earnings-call-transcript | Q2 2024 | 2023-12-11 | 233 | 15 chunks • 10-Q | Q2 2024 | 2023-12-12 | 234 | 56 chunks Q1 2024: • 8-K | Item 2.02: Financial Results | 2023-09-11 | 235 | 12 chunks • earnings-call-transcript | Q1 2024 | 2023-09-11 | 236 | 10 chunks • 10-Q | Q1 2024 | 2023-09-12 | 237 | 51 chunks FY 2023: • 8-K | Item 2.02: Financial Results | 2023-06-12 | 238 | 21 chunks • earnings-call-transcript | Q4 2023 | 2023-06-12 | 239 | 11 chunks • 10-K | FY 2023 | 2023-06-20 | 240 | 181 chunks Q3 2023: • 8-K | Item 2.02: Financial Results | 2023-03-09 | 241 | 20 chunks • earnings-call-transcript | Q3 2023 | 2023-03-09 | 242 | 12 chunks • 10-Q | Q3 2023 | 2023-03-10 | 243 | 69 chunks Q2 2023: • 8-K | Item 2.02: Financial Results | 2022-12-12 | 244 | 19 chunks • earnings-call-transcript | Q2 2023 | 2022-12-12 | 245 | 12 chunks • 10-Q | Q2 2023 | 2022-12-13 | 246 | 69 chunks [... more periods available] Other Recent Documents (5 per category): Events: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • 8-K | Item 8.01: Other Events | 2025-09-26 | 201 | 42 chunks • other-transcript | Status Update | 2025-09-22 | 202 | 5 chunks • 8-K | Item 5.02: Leadership Changes | 2025-09-22 | 203 | 7 chunks • 8-K | Item 7.01: Regulation FD Disclosure | 2025-06-30 | 204 | 2 chunks • 8-K | Item 8.01: Other Events | 2025-02-03 | 205 | 46 chunks [...] Proxies: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • DEFA14A | 2025-09-26 | 191 | 1 chunks • DEF 14A | Proxy Statement | 2025-09-26 | 192 | 110 chunks • DEFA14A | 2024-09-25 | 193 | 1 chunks • DEF 14A | Proxy Statement | 2024-09-25 | 194 | 114 chunks • DEF 14A | Proxy Statement | 2023-09-22 | 195 | 164 chunks [...] News: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • press-release | Oracle and Duality Deliver Privacy-First AI to Government an... | 2025-10-13 | 186 | 2 chunks • press-release | NVIDIA Spectrum-X Ethernet Switches Speed Up Networks for Me... | 2025-10-13 | 187 | 5 chunks • press-release | Zoom partners with Oracle to help enterprises scale customer... | 2025-10-13 | 188 | 3 chunks • press-release | DDN Infinia Now Available in Oracle Cloud Marketplace | 2025-10-13 | 189 | 3 chunks • press-release | Cloudflare Integrates Services with Oracle Cloud Infrastruct... | 2025-10-13 | 190 | 4 chunks [...] Prospectuses & Registrations: Format: [doc_type] | [title] | [date] | document_id | number_of_chunks • FWP | 2025-09-24 | 196 | 7 chunks • FWP | 2025-01-30 | 197 | 4 chunks • FWP | 2024-09-25 | 198 | 4 chunks • S-3ASR | 2024-03-15 | 199 | 75 chunks • S-8 | Securities to be Offered to Employees | 2023-12-13 | 200 | 9 chunks [...]

Now I'll search the most recent earnings materials from these hyperscalers for commentary on compute capacity versus demand.

  1. Searched documents

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    compute capacity supply demand constraint +capacity +infrastructure +(AI capacity) --QDF=5

    Output

    [Total chunks returned: 6] <chunk> [Document ID: Index]: [8:10] Ticker: AMZN Publication Date: 2025-07-31 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Andy Jassy** (President & CEO, Amazon): On the supply constraints as it relates to AWS and what we see there, You know, as I mentioned, well, we have more demand than we have capacity at this point. And I think that and and you see, you know, some of the constraints, and they kind of exist in multiple places. The single biggest constraint is power. But I you know, you also see constraints off and on with chips and then some of the components that, you know, once you have the chips to actually make the servers, you know, you there are you know, sometimes you have new generations of chips that are a little bit later than they're supposed to be and sometimes you get the chips and, you know, the yield you get in making servers isn't what you what you expect when you get to ramp. So there are a bunch of those pieces today that we're working on. It's really true across the industry today. I I don't believe that we will have fully resolved the amount of capacity we need for the amount of demand that we have in a couple quarters. I think it will take several quarters. But I do expect that it's gonna get better each quarter and I'm optimistic about that. I think on the Alexa question, you know, I I think what I'd start by saying the Alexa Plus experience is so much better than I think our prior Alexa experience. She's much more intelligent than her prior self. She's much more capable. And I would say unlike the the other chatbots that are out there today who are good at answering questions but really can't take any action for you, Alexa Plus can take a lot of action for you, which is very compelling. So I can ask Alexa to play music for me or play video for me or move my music from one device to another. Or if I'm listening to a a song that's on a that's in a movie, I can ask Alexa plus to actually put that movie scene on that of a song I'm playing, and it'll put it on my Prime Video on on Fire TV. Or if I have guests coming over, I can say, you know, Alexa, draw the curtains, put the light on the porch and the driveway, increase the temperature by five degrees, and put on music that would be great for a dinner party. And and she does all that just for using natural language. So she could take a lot of actions, and it's compelling. And what we see so far, you know, we've we've been rolling out Alexa Plus starting in The US. It's it's with millions of customers now. The rest come the rest in The US coming in the next couple months and starting the international rollout more broadly later in the year. And customers really like the experience. They recognize how much better it is than what it was before. The ratings are very high. The usage is is much more expansive than what they were using before. The number calls they're making is is meaningfully higher. And I I think there are a number of different areas where we'll see benefit. I I think first, you know, if you if you build the world's best personal assistant, that has a lot of utility for customers and, therefore, it gets used a lot. So it means everything from people are excited about the devices that they can buy from us that has Alexa Plus enabled in it. People do a lot of shopping, and it's it's really it's a delightful shopping experience that will keep getting better. I think over time, there will be opportunities, you know, as as people are engaging more multi turn conversations to have advertising play a role to help people find discovery and also as a lever to drive revenue. And I think over time, could also imagine as we keep adding functionality that there could be some sort of subscription element beyond what there is today. Today, Prime members get Alexa Plus for free and non Prime members pay $19.99 a month for Alexa Plus. So I think it's very it's still very early days, but we're very encouraged by the experience we're providing and you can bet we're gonna be iterating on it constantly. </chunk> <chunk> [Document ID: Index]: [8:14] Ticker: AMZN Publication Date: 2025-07-31 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Andy Jassy** (President & CEO, Amazon): So I think a lot of the you know, compute and the inference is gonna ultimately be run on top of Tranium too. And I think that that price performance is gonna matter to people as they get to scale. You know, then I would say that that middle layer of the stack are really it's it's a combination of services that customers care about to be able to build models and then to be able to leverage existing leading frontier models and then build, you know, high quality generate AI applications that do inference at scale. And, you know, we see it for people building models. They continue to use SageMaker AI very expansively. And then Bedrock, you're leveraging leading frontier models, is also growing very substantially. And, you know, as I said in my opening comments, the the number of agents of scale is still really small in the scheme of what's gonna be the case. But part of the problem is it's actually hard to actually build agents, and it's it's hard to deploy these agents in a secure and scalable way. And so I think the launches we made recently in strands that make it much easier to build agents and then agent core that make it much easier to deploy at scale and in a secure way are are being very well received and customers are excited. It's gonna change what's possible on the agent side. Yeah. And then and then I think that it's you've got a very large number. I mean, remember, 85 to 90% of the global IT spend is still on premises. If you believe that equation is gonna flip, which I do and we do, you have a lot of legacy infrastructure that you've gotta move. These are mainframes. These are VMware's instances. And, you know, when we build agents like AWS transform to make it much easier to to move mainframes to the cloud, much easier to move VMware to the cloud, much easier to move dot net windows to dot net Linux to save money. Like, those are compelling for enterprises or things like Curo that allow customers to develop in a in a much easier way and in a much more structured way, which is why I think people are excited about. So I think I really like the inputs in the set of services that we're building in the in the AI space today. Customers really like them, and it's resonating with them. I still think it's very early days in AI and in terms of adoption. But I the other thing I would just say is that, remember, because we're at a stage right now where so much of the activity is is training and figuring out how to get your generative AI applications into production, people aren't paying as close attention as they will in making sure that those generative AI applications are operating where the rest of their data and infrastructure is. Remember, a lot of generative AI, inference is just gonna be another building block like compute, storage, and database. And so people are gonna actually wanna run those applications close to where their other applications are running, where their data is. There's just so many more applications and data running in AWS than anywhere else. And I'm very optimistic about as we get to a bigger scale, what's gonna happen for AWS on the AI side. And I think we have a set of services that is unique top to bottom in the stack. I think on the last part about what do we expect with respect to acceleration. You know, we don't we don't give guidance by segments. I'm not gonna try and give you guidance, but I I do I do believe that the combination of more enterprises who have resumed their march to modernize their infrastructure and move from on premises to the cloud, coupled with the fact that AI is going to accelerate in terms of more companies deploying more AI applications into production that start to scale, coupled with the fact that I do think that more capacity is gonna come online in the in the coming months and quarters, make me optimistic about the AWS business. </chunk> <chunk> [Document ID: Index]: [8:13] Ticker: AMZN Publication Date: 2025-07-31 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Andy Jassy** (President & CEO, Amazon): Yeah. So on on the first one around AI, the first thing I would say is that I think it is so early right now in AI. If if you look at what's really happening in the space, you have it's it's very top heavy. So you have a a small number of very large frontier models that are being trained that's that spend a lot on computing. A couple of which are being trained on top of AWS and others are are being trained elsewhere. And then you also have, I would say, a relatively small number of very large scale generative AI applications. You know, you know, the one category would be chatbots with the largest by a fair bit being ChatGPT, but the other category being really, I'll call it, coding agents. So these are companies like Cursor, Vercel, and Lovable, some of the companies like that. Again, several of which run significant chunks on top of AWS. And then you've got a very large number of Generve AI applications that are in pilot mode that are in pilots or that are being developed as we speak, and a very substantial number of agents that also people are starting to try to build and and figure out how to get into production in a broad way. But but they're all they're they're quite early. And many of them that are out there are you know, they're significant, but they're just smaller in terms of usage relative to some of those top heavy applications I mentioned earlier. We have a a very significant number of enterprises and startups who are running applications on top of AWS's AI services. And and then, you know but but they're all again, like, the the amount of usage and the expansiveness of the use cases and how much people are putting them into production and the number of agents that are gonna exist, it's still just earlier stage than it's gonna be. And so then when you think about what's gonna matter in AI, what's gonna what what are customers gonna care about when they're thinking about what what infrastructure to use, I think you kind of have to look at the different layers of the stack. And, you know, I think for those that are, you know, both building models, but also just if you look at where the real costs are, they're gonna ultimately be an inference. Today, so much of the cost in training because customers are really training their models and trying to figure out how get applications into production. But in at scale, you know, 80 to 90% of the cost will be an inference because you only train periodically, but you're spitting out predictions and and inferences all the time. And so what they're gonna care a lot about is they're gonna care about the compute and the hardware they're using. And, know, you we have a very deep partnership with NVIDIA and and will for as long as I can foresee, but we we we saw this movie in the CPU space with Intel where customers are hankering for better price performance. And so, you know, we built just like in in the CPU space where we built our own custom silicon and building Graviton, which is about 40% more price performance than the other leading x 86 processors. We've done the same thing on the custom silicon side in AI with Tranium. And our second version of Tranium two has really you know, it's it's become the backbone of Anthropix, you know, next cloud models they're trading on top of, and it's become the the backbone of of Bedrock and the inference that we do. So I think a lot of the inference, it's about 3040% better price performance than the other GPU providers out there right now. And we're already working on our third version of trading as well. </chunk> <chunk> [Document ID: Index]: [8:8] Ticker: AMZN Publication Date: 2025-07-31 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Andy Jassy** (President & CEO, Amazon): Yes, I'll take both of those. I'll start with the tariffs. I think what we said a number of times and we still believe it is we just don't know what's going to happen moving forward. It's hard to know where the tariffs are going to settle particularly in China. It's hard to know what will happen when we deplete some of the pre buys that we did on our own first party retail and then some of the forward deploying that we saw of our third party selling partners. And when, you know, if costs go up over time, it's, you know, we're unsure at this point who's gonna end up absorbing those higher costs. What we can tell you is what we've seen so far in the first half of the year. In the first half, we just haven't seen diminished demand and we haven't seen any kind of broad scale ASP increases. And, you know, so that that could change in the second half. There are a lot of things that we don't know, but that's what we've seen so far. On the question on AWS, you know, the first thing I'd say is, you know, it's as you said, Doug, in your question, know, year over year percentages and growth rates are always a function of the base in which you operate. And we have a, you know, a meaningfully larger business in the AWS segment than others. I think the second player is about 65% of the size of of a AWS. And we when we look at the results over the last number of quarters, there's sometimes where as far as we can tell, we're growing faster than others and sometimes others are growing faster than us. But it's still like if you if you look at second place player you're talking about, it's a pretty it's still a pretty significant segment, you know, market segment leadership position that we have. And regardless, these are all really just moments in time. The last week is a moment in time too where the reality of what really matters is what customers' experiences are in operating on these platforms. And if if you look at what matters to customers, what they care they care a lot about what the operational performance is, you know, what the availability is, what the durability is, what the latency and throughput is of of the various services. And I think we have a pretty significant advantage in that area. They care a lot about security. If you have data that matters and for most companies, they're putting data that they really care about in the cloud. The security and the privacy of that data matters a lot, and there are very different results in security in AWS than you'll see in other players. And, yeah, you could just you just look at what's happened the last couple months. You can just see kind of adventures at some of these players almost every month. And so very big difference, I think, in security. And then I I think a a really significant difference in functionality where not just in the core infrastructure do we have a lot more functionality in our services. But I think if you look at our end to end offering in AWS in in AI, it's you know, from the bottom of stack all the way to the top, it it's pretty different. So, you know, I feel good about the the the inputs and the services that we're offering to customers across AI as well as non AI. And, you know, we could we we have more demand than we have capacity right now. So we could be doing more revenue and helping customers more, and we're working very hard on on changing that outcome and how much capacity we have, but it's still like, you know, you go get the business, it's a $123,000,000,000 annual revenue run rate business, and it's still early. I mean, how often do you have an opportunity that's a $123,000,000,000 of annual revenue run rate where you say it's still early? It's it's a very unusual opportunity that we're very bullish about. **Operator**: Thank you. Our next question comes from Mark Mahaney with Evercore. Please proceed with your question. </chunk> <chunk> [Document ID: Index]: [8:6] Ticker: AMZN Publication Date: 2025-07-31 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Brian Olsavsky** (SVP & CFO, Amazon): Advertising revenue grew 22% year over year, driven by sponsored products as we saw strong traffic in our stores. Advertising remains an important contributor to profitability in the North American international segments. Our full funnel advertising approach of connecting brands with customers is resonating. Moving next to our AWS segment. Revenue was $30,900,000,000 an increase of 17.5% year over year. AWS now has an annualized revenue run rate of more than a 123,000,000,000. During the second quarter, we continue to see growth in both our generative AI and non generative AI businesses. As companies turn their attention to newer initiatives, bring more workloads to the cloud, restart or accelerate existing migrations from on premise to the cloud, and tap into the power of generative AI. AWS operating income was $10,200,000,000. We did see AWS segment margins decline from a record high of 39.5% in q one to 32.9% in q two. The largest quarter over quarter driver of the decrease for about half is due to the seasonal step up in stock based compensation expense driven by the timing of our annual compensation cycle. AWS margins also saw headwinds from higher depreciation expense as well as unfavorable impacts from year over year fluctuations in foreign exchange rates. The depreciation expense is a result of our growing investments in capital expenditures in AWS. As we've said in the past, we expect AWS operating margins to fluctuate over time, driven in part by the level of investments we are making at any point in time. We will continue to invest more capital in chips, data centers, and power to pursue this unusually large opportunity that we have in generative AI. Now turning to our cash CapEx, which was $31,400,000,000 in q two. We expect q two CapEx to be reasonably representative of our quarterly capital investment rate for the back half of this year. AWS continues to be the primary driver as we invest to support demand for our AI services and increasingly in custom silicon like Tranium, as well as tech infrastructure to support our North America and international segments. Additionally, we continue to invest in our fulfillment and transportation network to support growth of the business, improve delivery speeds, and lower our cost to serve by investing in same day delivery facilities as well as robotics and automation. Collectively, these investments will support growth for many years to come. Moving on to our third quarter financial guidance. As a reminder, our guidance considers a range of possibilities which take into consideration Q2 results, trends we see quarter to date, and expectations around the macroeconomic environment including tariffs. Q3 net sales are expected to be between $174,000,000,000 and $179,500,000,000 We estimate the year over year impact of changes in foreign exchange rates based on current rates, which we expect to be a favorable impact of approximately 130 basis points. As a reminder, global currencies can fluctuate during the quarter. Q3 operating income is expected to be between $15,500,000,000 and $20,500,000,000 In this dynamic environment, we'll focus on what matters most, delivering exceptional customer value through broad selection, competitive prices, and unmatched convenience. We remain focused on driving a better customer experience and believe putting customers first is the only reliable way to create lasting value for our shareholders. With that, let's move on to your questions. </chunk> <chunk> [Document ID: Index]: [8:12] Ticker: AMZN Publication Date: 2025-07-31 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Andy Jassy** (President & CEO, Amazon): On the Project Kuiper question, so Project Kuiper is our low Earth orbit satellite constellation that we're putting up and launching. And, you know, there's 400 to 500,000,000 households worldwide who don't have broadband connectivity. And it means they can't do a lot of the things we take for granted like education online or business online or shopping or or entertainment. There is really a digital divide, and it's much needed. And it's also true for enterprises and for governments if they have assets or needs to have visibility or connectivity that they can't get today given the lack of broadband in a bunch of places around the world. So there's there's a high need. I would say that as we get our constellation into space, there will really be two players that have what I would consider the the modern technology in low earth orbit satellite. You know, one is is the incumbent in in the market today, and the second will be Project Kuiper. I think that we will have a a pretty meaningful differentiation here in performance. If you look at the performance of what I expect on the uplink and downlink, I think Project Kuiper will be advantaged. I also think the pricing is gonna be very compelling for customers. And then I think if you think about the three key customer segments who want, low Earth orbit satellite, consumers, enterprises, and governments, We have very strong relationships with all three customer segments given our consumer businesses and our AWS business. And I think if you if you think about enterprises and governments, a lot of what they wanna do when they take the data down from space is they actually wanna put it into a cloud to do analysis, analytics, and and AI and and various operations on top of it. And the fact that Project Kuiper and AWS are so seamlessly connected is very attractive to enterprises and to governments. I'm kind of amazed. We we haven't launched Project Kuiper yet, but the number of enterprise and government agreements that have been signed already to use Project Kuiper is impressive. So we're we're working very hard to get the satellites into space. We have some delays with some of the rocket providers, but we we have most of the available rocket launches over the next couple of years. And we're very hopeful to get this service into commercial into commercial beta later this year or early next year. **Operator**: Thank you. And our next question comes from the line of Brian Novak with Morgan Stanley. Please proceed with your question. **Andy Jassy** (President & CEO, Amazon): Thanks for taking my questions. **Brian Nowak** (Managing Director , Morgan Stanley): Andy, I have two for you on AWS. They're a little tough, but I'm gonna throw them at you. So there is a Wall Street Finance person narrative right now that AWS is falling behind in GenAI with concerns about care loss to peers, etcetera. Can you just sort of address that? What what is your rebuttal to that? And talk to us about your and the team's most important focal points just to ensure that AWS stays on the knife's edge of innovation versus hyperscaler peers? And then secondly, I know AWS is a big business, but is there any reason to assume it shouldn't accelerate in the back half and into '26 given the size of the opportunity and all of the Gen AI capabilities gonna sort of come to us in the next next twelve months? </chunk>
  2. Searched documents

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    compute capacity supply demand constraint +capacity +infrastructure +(AI capacity) --QDF=5

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    [Total chunks returned: 6] <chunk> [Document ID: Index]: [269:6] Ticker: MSFT Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q4 2025 Highlighted Text: **Amy Hood** (EVP & CFO, Microsoft): Dynamics three sixty five revenue increased 2321% in constant currency with strong execution in our core annuity sales motions leading to growth across all workloads. Segment gross margin dollars increased 1615% in constant currency and gross margin percentage increased slightly driven by the efficiency gains noted earlier even as we deliver more AI features across our products and scale our AI infrastructure. Operating expenses increased 76% in constant currency and operating income increased 2119% in constant currency. Next, the Intelligent Cloud segment. Revenue was $29,900,000,000 and grew 2625% in constant currency ahead of expectations driven by Azure and our on premises server business. In Azure and other cloud services revenue grew 39% significantly ahead of expectations driven by accelerated growth in our core infrastructure business primarily from our largest customers. As a reminder, new cloud and AI workloads are built and scaled using the breadth of our services. Revenue from Azure AI services was generally in line with expectations. And while we brought additional data center capacity online this quarter demand remains higher than supply. In our on premises server business revenue decreased 23% in constant currency ahead of expectations primarily driven by transactional purchasing which also has higher end period revenue recognition. Enterprise and Partner Services revenue increased 76% in constant currency with growth in Enterprise Support Services partially offset by a decline in Industry Solutions. Segment gross margin dollars increased 1716% in constant currency and gross margin percentage decreased four points year over year driven by scaling our AI infrastructure, partially offset by Azure efficiency gains noted earlier. Operating expenses increased 64% in constant currency and operating income grew 23%. Now to more personal computing. Revenue was $13,500,000,000 and grew 9% exceeding expectations primarily due to Windows OEM as well as Xbox content and services. Windows OEM and devices revenue increased 3% year over year ahead of expectations as inventory levels remained elevated. Search and news advertising revenue ex TAC increased 2120% in constant currency driven by continued growth in both volume and revenue per search as well as roughly eight points of favorable impact from third party partnerships including the benefit of a low prior year comparable. And in gaming, revenue increased 10%. Xbox content and services revenue increased 1312% in constant currency driven by better than expected performance from first party content and Xbox Game Pass. Segment gross margin dollars increased 15%. Gross margin percentage increased three points year over year with improvement across all businesses. Operating expenses increased 43% in constant currency. Operating income increased 3433% in constant currency driven by continued prioritization of higher margin opportunities. Now back to total company results. Capital expenditures were $24,200,000,000 including $6,500,000,000 of finance leases, where we recognized the full value at the time of lease commencement. Cash paid for PP and E was $17,100,000,000 The difference is primarily due to finance leases. More than half our spend was on long lived assets that will support monetization over the next fifteen years and beyond. The remaining spend was primarily for servers both CPUs and GPUs and driven by strong demand signals. Cash flow from operations was $42,600,000,000 up 15% driven by strong cloud billings and collections partially offset by higher supplier payments. And this quarter free cash flow was $25,600,000,000 Other income and expense was negative $1,700,000,000 primarily due to losses on investments accounted for under the equity method. </chunk> <chunk> [Document ID: Index]: [269:8] Ticker: MSFT Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q4 2025 Highlighted Text: **Amy Hood** (EVP & CFO, Microsoft): For Intelligent Cloud, we expect revenue of $30,100,000,000 to $30,400,000,000 or growth of 25% to 26% with roughly one point of benefit from FX as noted earlier. Revenue will continue to be driven by Azure, which can have quarterly variability in year on year growth rates depending on the timing of capacity delivery and when it comes online as well as from in period revenue recognition depending on the mix of contracts. In Azure, we expect Q1 revenue growth of approximately 37% in constant currency driven by strong demand for our portfolio of services on a significant base. Even as we continue bringing more data center capacity online, we currently expect to remain capacity constrained through the first half of our fiscal year. In our on premises server business, we expect revenue to decline in the low to mid single digits with the ongoing customer shift to cloud offerings. In More Personal Computing, we expect revenue to be 12,400,000,000.0 to $12,900,000,000 Windows OEM and devices revenue should decline in the mid to high single digits. We expect the elevated inventory levels at the end of Q4 to come down through the quarter in Windows OEM, although the range of potential outcomes remains wider than normal. Devices revenue should decline. Search and news advertising ex TAC revenue growth should be in the low to mid teens, down sequentially as growth rates normalize following the benefit from third party partnerships noted earlier. Growth will continue to be driven by volume and revenue per search across Edge and Bing. Overall Search and News advertising revenue growth should be in the low double digits. And in gaming, we expect revenue to decline in the mid to high single digits against a strong prior year comparable. We expect Xbox content and services revenue to decline in the mid single digits. Now back to company guidance. We expect COGS of 24,300,000,000.0 to $24,500,000,000 or growth of 21% to 22% and operating expense of 15,700,000,000.0 to $15,800,000,000 or growth of 5% to 6%. Other income and expense is estimated to be negative $1,300,000,000 primarily due to investments accounted for under the equity method. As a reminder, we do not recognize mark to market gains or losses on equity method investments. And lastly, we expect our Q1 effective tax rate to be between 1920%. In closing, we finished the year with double digit revenue and operating income growth and exceeded the FY 2025 operating margin commitment we shared a year ago. Our focus remains on investing in security, quality and AI platform and product innovation that delivers value and opportunity to our customers. We are excited for FY 2026. With that, let's go to Q and A, Jonathan. </chunk> <chunk> [Document ID: Index]: [269:1] Ticker: MSFT Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q4 2025 Highlighted Text: **Satya Nadella** (Chairman & CEO, Microsoft): Thank you, Jonathan. It was a very strong close to what was a record fiscal year for us. All up Microsoft Cloud surpassed $168,000,000,000 in annual revenue, up 23%. The rate of innovation and the speed of diffusion is unlike anything we have seen. To that end, we are building the most comprehensive suite of AI products and tech stack at massive scale. And to provide more context, I want to walk up the stack starting with Azure. Azure surpassed $75,000,000,000 in annual revenue, up 34% driven by growth across all workloads. We continue to lead the infrastructure wave and took share every quarter this year. We opened new DCs across six continents and now have over 400 data centers across 70 regions more than any other cloud provider. There is a lot of talk in the industry about building the first gigawatt and multi gigawatt data centers. We stood up more than two gigawatts of new capacity over the past twelve months alone and we continue to scale our capacity faster than any other competitor. Every Azure region is now AI first. All of our regions can now support liquid cooling, increasing the fungibility and the flexibility of our fleet. And we are driving and riding a set of compounding S curves across silicon systems and models to continuously improve efficiency and performance for our customers. Take for example, GBD4O family of models, which have the highest volume of inference tokens. Through software optimizations alone, we are delivering 90% more tokens for the same GPU compared to a year ago. Beyond the AI fleet, we continue to build our commercial cloud to address customers' unique data residency and sovereignty requirements. This quarter, we introduced the Microsoft Sovereign Cloud, the industry's most comprehensive solution spanning both public and private cloud deployments. All of this innovation is driving our strong results. We saw accelerating growth from migrations again this quarter. Nestle, for example, migrated more than 200 SAP instances, 10,000 plus servers, 1.2 petabytes of data to Azure with near zero business disruption. That makes it one of the largest and most successful migrations in business history. The next big accelerator in the cloud will be quantum and I'm excited about our progress. In fact, earlier this month, we announced the world's first operational deployment of Level two quantum computer in partnership with Atom Computing. This is how we will continue to think and make investments with decade long arcs while making progress every quarter. The next layer is data, which is foundational to every AI application. Microsoft Fabric is becoming the complete data and analytics platform for the AI era, spanning everything from SQL to NoSQL to analytics workloads. It continues to gain momentum with revenue up 55% year over year and over 25,000 customers. It's the fastest growing database product in our history. FabricOnely expands all databases and clouds including semantic models from Power BI and therefore it is the best source of knowledge and grounding for AI applications and context engineering. Azure Databricks and Snowflake on Azure both accelerated as well. Cosmos DB and Azure PostgreSQL are both powering mission critical workloads at scale. OpenAI for example uses Cosmos DB in the hot path of every chat GPT interactions storing chat history, user profiles and conversational state and Azure PostgreSQL stores metadata critical to the operation of ChatGPT as well as OpenAI's developer APIs. This year, we launched Azure AI Foundry to help customers design, customize and manage AI applications and agents at scale. Foundry features best in class tooling, management, observability and built in controls for trustworthy AI. </chunk> <chunk> [Document ID: Index]: [269:13] Ticker: MSFT Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q4 2025 Highlighted Text: **Amy Hood** (EVP & CFO, Microsoft): Thanks, Kash. Let me back up and first say, when you think about the full year comments I've made on CapEx as well as the Q1 guidance of over 30,000,000,000 you first have to ground yourself in the fact that we have $368,000,000,000 of contracted backlog we need to deliver not just across Azure, but across the breadth of the Microsoft cloud. So in terms of feeling good about the ROI and the growth rates and the correlation, I feel very good that the spend that we're making is correlated to basically contracted on the books business that we need to deliver and we need the teams to execute at their very best to get the capacity in place as quickly and effectively as they can. And so when you look, we've talked about the growth rate will decline year over year, but at its core, our investments, particularly in short lived assets like servers, GPUs, CPUs, networking storage, is just really correlated to the backlog we see and the curve of demand. And I talked about, my gosh, in January and said, I thought we'd be in better supplydemand shape by June. And now I'm saying, I hope I'm in better shape by December. And that's not because we slowed CapEx even with accelerating the spend and trying to pull leases in and get CPUs and GPUs in the system as quickly as we can. We are still seeing demand improve. And so I am not as focused, Kash, on trying to pick a date at which revenue growth and CapEx growth will meet and cross. I'm focused on building backlog, building business and delivering capacity, which we are seeing has a good ROI today in terms of our ability to get that done. So I don't want people to get overly focused on a pivot point because when you're in sort of these expansive moments, picking a data point usually means you're going to pick to be too conservative in terms of market share gain and in terms of winning. And so I tend to put my energy more there. Yes. **Satya Nadella** (Chairman & CEO, Microsoft): I think one of the other things, Kash, is that I think I said this in a previous earnings as well, which is the difference between a holster and a hyperscaler is software, and the same is going to be true here. That GPD four point example I gave is all software, The optimization even in the last year. So we know how to use the software skills to take any piece of hardware and make it multiple X better. And so that's kind of where the yield will come. But as Amy said, while you're really going and building out the plant, you don't want to sort of You just want to go in parallel on all of these fronts, and that's sort of what will compound over time. **Amy Hood** (EVP & CFO, Microsoft): And I do think it's important when Plata talks about the software layer, he's talking about in his comments to connect this back to the compounding S curves. And so I would remind people that is something that we saw through the prior cloud transition. It's how we operated through that one. And the same sort of skills and logic done at an even faster pace is what will apply the same transition. **Kash Rangan** (Managing Director, Goldman Sachs): Sounds very encouraging. Thank you so much. **Jonathan Neilson** (VP - IR, Microsoft): Thanks, Kash. Operator, next question please. **Operator**: The next question comes from the line of Michael Turrin with Wells Fargo. Please proceed. **Michael Turrin** (MD & Equity Research Analyst, Wells Fargo): Hey, great. Thanks very much for taking the questions and congrats from me as well on the metrics working in concert here. Amy, maybe on margin impressive to hear expectations for flat operating margin in the upcoming year as you absorb some of the mix shift towards Azure and some of the more AI focused offerings. Can you speak in more detail just around your ability to manage those trade offs and offset some of the mix shift? And I'm wondering specifically just on any productivity gains you're seeing from leveraging AI internally that you'd highlight or anything else you just mentioned in underpinning the full year expectation there? Thanks, </chunk> <chunk> [Document ID: Index]: [269:7] Ticker: MSFT Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q4 2025 Highlighted Text: **Amy Hood** (EVP & CFO, Microsoft): Our effective tax rate was approximately 17%. And finally, we returned $9,400,000,000 to shareholders through dividends and share repurchases bringing our total cash return to shareholders to over $37,000,000,000 for the full fiscal year. Now moving to our outlook. My commentary for both the full year and next quarter is on a U. S. Dollar basis unless specifically noted otherwise. Let me start with some full year commentary for FY 2026. First, FX. Assuming current rates remain stable, we expect FX to increase full year revenue growth and COGS growth by approximately two points and to increase operating expense growth by one point. Next, building on the strong momentum we saw this past year, we expect to deliver another year of double digit revenue and operating income growth in FY 2026. We will continue to invest against the expansive opportunity ahead across both capital expenditures and operating expenses given our leadership position in commercial cloud, strong demand signals for our cloud and AI offerings and significant contracted backlog. Capital expenditure growth as we shared last quarter will moderate compared to FY 2025 with a greater mix of short lived assets. Due to the timing of delivery of additional capacity in H1 including large finance lease sites, we expect growth rates in H1 will be higher than in H2. We remain focused on delivering revenue growth and increasing our operational agility. And as a result, we expect operating margins to be relatively unchanged year over year. And finally, we expect our FY 2026 effective tax rate to be between 1920%. Now to our outlook for the first quarter. Based on current rates, we expect FX to increase total revenue growth by two points. Within the segments, we expect FX to increase revenue growth by roughly three points in Productivity and Business Processes and roughly one point in Intelligent Cloud and More Personal Computing. We expect FX to increase COGS and operating expense growth by roughly one point. In commercial bookings, we expect healthy growth on a growing expiry base. Bookings growth will again be driven by strong execution across our core annuity sales motions and long term commitments to our platform. As a reminder, larger long term Azure contracts which are more unpredictable in their timing drive increased quarterly volatility in our bookings growth rate. Microsoft Cloud gross margin percentage should be roughly 67% down year over year driven by the impact of continuing to scale our AI infrastructure. We expect Q1 capital expenditures to be over $30,000,000,000 driven by the continued strong demand signals we see. As a reminder, there can be quarterly spend variability from cloud infrastructure build outs and the timing of delivery of finance leases. Next to segment guidance. In Productivity and Business Processes, we expect revenue of 32,200,000,000.0 to $32,500,000,000 or growth of 14% to 15% with roughly three points of benefit from FX as noted earlier. In M365 Commercial Cloud, we expect revenue growth to be between 1314% in constant currency with business trends that remain relatively stable compared to the prior quarter. ARPU growth will again be driven by E5 and M365 Copilot. M365 Commercial Products revenue growth should be in the mid to high single digits. As a reminder, M365 commercial products includes both the Windows commercial on premises components of M365 suites and office transactional purchasing both of which can be variable due to end period revenue recognition dynamics. M365 consumer cloud revenue growth should be in the low 20s driven by the January price increase. For LinkedIn, we expect revenue growth in the high single digits. And in Dynamics three sixty five, we expect revenue growth to be in the high teens with continued growth across all workloads. </chunk> <chunk> [Document ID: Index]: [269:5] Ticker: MSFT Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q4 2025 Highlighted Text: **Amy Hood** (EVP & CFO, Microsoft): Thank you, Satya, and good afternoon, everyone. This year, we delivered over $281,000,000,000 in revenue, up 15% year over year, which reflects the broad strength of our products and services. Operating income was over $128,000,000,000 up 17% year over year as we invested against the expansive opportunity ahead. And in our largest quarter of the year, we significantly exceeded expectations with strong execution by our sales and partner teams. As Satya shared, we're innovating faster than ever to deliver new value to our customers. This quarter revenue was $76,400,000,000 up 1817% in constant currency. Gross margin dollars increased 1615% in constant currency, while operating income increased 2322% in constant currency. And earnings per share was $3.65 an increase of twenty four percent and twenty two percent in constant currency. For the first time commercial bookings were over $100,000,000,000 increasing 3730% in constant currency on a strong prior year comparable. Strong execution across our core annuity sales motions, including healthy renewals as well as an increase in the number of 10,000,000 and $100,000,000 plus contracts for both Azure and Microsoft three sixty five helped drive these results. Commercial remaining performance obligation increased to $368,000,000,000 up 3735% in constant currency. Roughly 35% will be recognized in revenue in the next twelve months, up 21% year over year. The remaining portion recognized beyond the next twelve months increased 49%. And this quarter our annuity mix was again 98%. FX was roughly in line with expectations on total company revenue, segment level revenue, COGS and operating expense growth. Microsoft Cloud revenue was $46,700,000,000 ahead of expectations and grew 2725% in constant currency. Microsoft Cloud gross margin percentage was slightly better than expected at 68% down two points year over year from the impact of scaling our AI infrastructure partially offset by continued efficiency gains in Azure and M365 Commercial Cloud. Company gross margin percentage was 69%, down one point year over year driven by sales mix shift to Azure and the lower Microsoft Cloud gross margin noted earlier. Operating expenses increased 65% in constant currency and operating margins increased two points year over year to 45%. Better than expected revenue growth coupled with a focus on operating efficiently drove the margin expansion. At a total company level, headcount at the June was relatively unchanged year over year. Now to our segment results. Revenue from Productivity and Business Processes was $33,100,000,000 and grew 1614% in constant currency better than expected driven by M365 Commercial Products and Cloud Services and M365 Consumer Products and Cloud Services. M365 Commercial Cloud revenue was ahead of expectations and increased 1816% in constant currency with two points of benefit from in period revenue recognition. Business trends remained relatively stable to the prior quarter when excluding the in period revenue recognition with ARPU growth again driven by E5 and M365 Co Pilot. Paid M365 commercial seats grew 6% year over year with installed base expansion across all customer segments though primarily in our small and medium business and frontline worker offerings. M365 Commercial Products revenue increased 97% in constant currency ahead of expectations due to higher than expected Office 2024 transactional purchasing. M365 consumer cloud revenue was better than expected increasing 20% driven by ARPU growth following the January price increase and subscriber growth of 8%. LinkedIn revenue increased nine percent and eight percent in constant currency with growth across all businesses. The Talent Solutions continues to be impacted by weakness in the hiring market. </chunk>
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    [Total chunks returned: 6] <chunk> [Document ID: Index]: [131:13] Ticker: META Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Susan Li** (CFO, Meta Platforms): Justin, I can go ahead and and take a crack at both of those. And, obviously, Mark, you should you should feel free to weigh in. You know, right now, we are focused on, ensuring that we have enough capacity for our internal use cases, which includes both all of the core AI work that we do to support the recommendation, engine work on the organic, content side to support all the ads ranking and recommendation work, and then, of course, to make sure that we are building the training capacity that we think we need in order to build frontier AI models, and to make sure that we're preparing ourselves for, the types of inference use cases that we think, you know, might, that we might have ahead of us as we, eventually, you know, focus not only on developing frontier models, but also how we can expand, into the kinds of consumer use cases, that we think will, you know, be hopefully hopefully widely useful and, and engaging for our users. So at present, we're not really thinking about, external use case, external use cases on the infrastructure, but it's a, you know, it it it's it's a good question. On your second question, which is really around the sort of ROI on on CapEx, you know, there are a couple things. So, again, on the core AI side, we continue to see strong ROI. Our ability to measure that is quite good, and we feel sort of, you know, very good about the the rigorous measurement and returns that that we see there. On the Gen AI side, we are clearly much, much earlier on the return curve, and we don't expect, that the Gen AI work is going to be a meaningful driver of revenue, you know, this year or, or next year. But we remain, you know, generally very optimistic about the the monetization opportunities that will open up, and Mark spoke to them in his, in his script, the sort of five pillars, I won't repeat them here. And we think that over the medium to long term time frame, those are opportunities that are very adjacent and intuitive, you know, for where our in terms of where our business is today, why they would be big opportunities for us, and that there will be sort of big markets attached, attached to each of them. So, you know, we, again, are also I would say the last thing I would add here is we are building the infrastructure with fungibility in mind. Obviously, there are a lot of things that you have to build up front in terms of the data center, shells, the networking infrastructure, etcetera. But we will be, you know, ordering servers, which ultimately will be the biggest bulk of CapEx spend as we need them, and when we need them, and making sort of the the best decisions at those times in terms of figuring out where the capacity will go to use. **Operator**: Your next question comes from the line of Mark Schmulek with Bernstein. Please go ahead. **Mark Shmulik** (MD & Senior Analyst - US Internet, AB Bernstein): Yes. Thank you for taking my questions. Mark, as you go after the superintelligence vision, especially for those of us on the outside, what are kind of some of the markers or KPIs that you're tracking on whether you're on track and making progress? Is it really against kind of those five pillars you outlined above? Or should we be thinking more broadly? And Susan, obviously, AI delivering great ROI today, all those investments, and also building towards kind of longer term goals. Just curious, has there just been any change or adjustment to how you think about the relationship between revenues or core business performance and the cadence of investment? Thank you. </chunk> <chunk> [Document ID: Index]: [131:7] Ticker: META Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Susan Li** (CFO, Meta Platforms): So we expect to ramp our investments significantly in 2026 to support that work. Moving to our financial outlook. We expect third quarter twenty twenty five total revenue to be in the range of $47,500,000,000 to $50,500,000,000 Our guidance assumes foreign currency is an approximately 1% tailwind to year over year total revenue growth based on current exchange rates. While we are not providing an outlook for fourth quarter revenue, we would expect our year over year growth rate in the 2025 to be slower than the third quarter as we lap a period of stronger growth in the 2024. Turning now to the expense outlook. We expect full year 2025 total expenses to be in the range of 114,000,000,000 to $118,000,000,000 narrowed from our prior outlook of $113,000,000,000 to $118,000,000,000 and reflecting a growth rate of 20 to 24% year over year. While we're still very early in planning for next year, there are a few factors we expect will provide meaningful upward pressure on our 2026 total expense growth rate. The largest single driver of growth will be infrastructure costs driven by a sharp acceleration in depreciation expense growth and higher operating costs as we continue to scale up our infrastructure fleet. Aside from infrastructure, we expect the second largest driver of growth to be employee compensation as we add technical talent in priority areas and recognize a full year of compensation expenses for employees hired throughout 2025. We expect these factors will result in a 2026 year over year expense growth rate that is above the 2025 expense growth rate. Turning now to the CapEx outlook. We currently expect twenty twenty five capital expenditures including principal payments on finance leases to be in the range of 66,000,000,000 to $72,000,000,000 narrowed from our prior outlook of $64,000,000,000 to $72,000,000,000 and up approximately $30,000,000,000 year over year at the midpoint. While the infrastructure planning process remains highly dynamic, we currently expect another year of similarly significant CapEx dollar growth in 2026 as we continue aggressively pursuing opportunities to bring additional capacity online to meet the needs of our AI efforts and business operations. Onto tax. With the enactment of the new US tax law, we anticipate a reduction in our US federal cash tax for the remainder of the current year and future years. There are several alternative ways of implementing the provisions of the act which we are currently evaluating. While we estimate that the 2025 tax rate will be higher than our q two tax rate, we cannot quantify the magnitude at this time. In addition, we continue to monitor an active regulatory landscape including the increasing legal and regulatory headwinds in The EU that could significantly impact our business and our financial results. For example, we continue to engage with the European Commission on our less personalized ads offering or LPA, which we introduced in November 2024 based on feedback from the European Commission in connection with the DMA. As the commission provides further feedback on LPA, we cannot rule out that it may seek to impose further modifications to it that would result in a materially worse user and advertiser experience. This could have a significant negative impact on our European revenue as early as later this quarter. We have appealed the European Commission's DMA decision, but any modifications to our model may be imposed during the appeal process. In closing, this was another strong quarter for our business as our investments in infrastructure and technical talent continue to improve core ads performance and engagement on our platforms. We expect the significant investments we're making now will allow us to continue leveraging advances in AI to extend those gains and unlock a new set of opportunities in the years to come. With that, Krista, let's open up the call for questions. </chunk> <chunk> [Document ID: Index]: [131:3] Ticker: META Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Susan Li** (CFO, Meta Platforms): Thanks, Mark, and good afternoon, everyone. Let's begin with our consolidated results. All comparisons are on a year over year basis unless otherwise noted. Q2 total revenue was $47,500,000,000 up 22% on both a reported and constant currency basis. Q two total expenses were $27,100,000,000 up 12% compared to last year. In terms of the specific line items, cost of revenue increased 16% driven mostly by higher infrastructure costs and payments to partners, partially offset by a benefit from the previously announced extension of several useful lives. R and D increased 23% mostly due to higher employee compensation and infrastructure costs. Marketing and sales increased 9% primarily due to an increase in professional services related to our ongoing platform integrity efforts as well as marketing costs partially offset by lower employee compensation. G and A decreased 27% driven mostly by lower legal related costs. We ended Q2 with over 75,900 employees down 1% quarter over quarter as the vast majority of the employees impacted by performance related reductions earlier this year were no longer captured in our headcount. This was partially offset by continued hiring in priority areas of monetization, infrastructure, Reality Labs, AI, as well as regulation and compliance. Second quarter operating income was $20,400,000,000 representing a 43% operating margin. Our tax rate for the quarter was 11% which reflects excess tax benefits from share based compensation due to the increase in our share price versus prior periods. Net income was $18,300,000,000 or $7.14 per share. Capital expenditures including principal payments on finance leases were $17,000,000,000 driven by investments in servers, data centers, and network infrastructure. Free cash flow was $8,500,000,000 We repurchased $9,800,000,000 of our Class A common stock and paid 1,300,000,000 in dividends to shareholders. We also made $15,100,000,000 in non marketable equity investments in the second quarter which includes our minority investment in Scale AI along with other investment activities. We ended the quarter with $47,100,000,000 in cash and marketable securities and $28,800,000,000 in debt. Moving now to our segment results. I'll begin with our Family of Apps segment. Our community across the Family of Apps continues to grow and we estimate more than 3,400,000,000 people used at least one of our Family of Apps on a daily basis in June. Q two total family of apps revenue was $47,100,000,000 up 22% year over year. Q two family of apps ad revenue was $46,600,000,000 up 21 or 22% on a constant currency basis. Within ad revenue, the online commerce vertical was the largest contributor to year over year growth. On a user geography basis, ad revenue growth was strongest in Europe and rest of world at 2423% respectively. North America and Asia Pacific grew 2118%. In q two, the total number of ad impressions served across our services increased 11% with growth mainly driven by Asia Pacific. Impression growth accelerated across all regions due primarily to engagement tailwinds on both Facebook and Instagram and to a lesser extent ad load optimizations on Facebook. The average price per ad increased 9% benefiting from increased advertiser demand largely driven by improved ad performance. Pricing growth slowed modestly from the first quarter due to the accelerated impression growth in Q2. Family of Apps other revenue was $583,000,000 up 50% driven by WhatsApp paid messaging revenue growth as well as Meta Verified subscriptions. We continue to direct majority of our investments toward the development and operation of our family of apps. In q two, family of apps expenses were $22,200,000,000 representing 82% of our overall expenses. Family of expenses were up 14% mainly due to growth in employee compensation and infrastructure costs partially offset by lower legal related costs. Family of Apps operating income was $25,000,000,000 representing a 53% operating margin. </chunk> <chunk> [Document ID: Index]: [131:1] Ticker: META Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Mark Zuckerberg** (Founder, Chairman & CEO, Meta Platforms): Alright. Thanks, Ken. Thanks, everyone, for joining today. We had another strong quarter with more than 3,400,000,000 people using at least one of our apps each day and strong engagement across the board. Our business continues to perform very well, which enables us to invest heavily in our AI efforts. Over the last few months, we've begun to see glimpses of our AI systems improving themselves, and the improvement is slow for now but undeniable. And developing superintelligence, which we define as AI that surpasses human intelligence in every way, we think is now in sight. Meta's vision is to bring personal superintelligence to everyone so that people can direct it towards what they value in their own lives. And we believe that this has the potential to begin an exciting new era of individual empowerment. A lot has been written about all the economic and scientific advances that superintelligence can bring, and I'm extremely optimistic about this. But I think that if history is a guide, then an even more important role will be how superintelligence empowers people to be more creative, develop culture and communities, connect with each other, and lead more fulfilling lives. To build this future, we've established Meta Superintelligence Labs, which includes our foundations, product, and fair teams as well as a new lab that is focused on developing the next generation of our models. We're making good progress towards LAMA four point one and four point two. And in parallel, we are also working on our next generation of models that will push the frontier in the next year or so. We're building an elite talent dense team. Alexander Wang is leading the overall team. Nat Friedman is leading our AI products and applied research, and Xingjia Zhao is chief scientist for the new effort. They are all incredibly talented leaders, and I'm excited to work closely with them and the world class group of AI researchers and infrastructure and data engineers that we're assembling. I spent a lot of time building this team this quarter, and the reason that so many people are excited to join is because Meta has all of the ingredients that are required to build leading models and deliver them to billions of people. The people who are joining us are gonna have access to unparalleled compute as we build out several multi gigawatt clusters. Our Prometheus cluster is coming online next year, and we think it's going to be the world's first gigawatt plus cluster. We're also building out Hyperion, which will be able to scale up to five gigawatts over several years, and we have multiple more Titan clusters in development as well. We are making all these investments because we have conviction that superintelligence is going to improve every aspect of what we do. From a business perspective, I mentioned last quarter that there are five basic opportunities that we are pursuing, improved advertising, more engaging experiences, business messaging, Meta AI, and AI devices. So I can go into a bit of detail on each. On advertising, the strong performance this quarter is largely thanks to AI unlocking greater efficiency and and gains across our ad system. This quarter, we expanded our new AI powered recommendation model for ads to new surfaces and improved its performance by using more signals and longer context. It's it's driven roughly 5% more ad conversions on Instagram and 3% on Facebook. We're also seeing good progress with AI for ad creative, with a meaningful percent of our ad revenue now coming from campaigns using one of our generative AI features. This is gonna be especially valuable for smaller advertisers with limited budgets, while agencies will continue, the important work to help larger brands apply these tools strategically. </chunk> <chunk> [Document ID: Index]: [131:10] Ticker: META Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Susan Li** (CFO, Meta Platforms): Eric, for the second part of your question, you know, we, we haven't, in fact, kicked off our budgeting process for 2026. So the thinking about next year, there are clearly many, many moving pieces in a very dynamic operating environment. But there are certain aspects that we have some visibility into today, including the rough shape of our 2026 infrastructure plans, you know, and that flows through into our expense expectations next year. And we also have some visibility into the compensation expense growth that we'll recognize from the AI talent that we're hiring this year. And so those, you know, those two things are part of why we gave a little bit of an early preview into the expectations for growth for 2026, total expenses, as well as for 2026, for 2026 CapEx. So on the total expenses side, you know, as I mentioned, we expect infrastructure will be the single largest accelerate, contributor to 2026 expense growth. That's driven primarily by a sharp acceleration in depreciation expense growth in 2026, largely driven by recognizing incremental depreciation from assets that we purchased in place and service in '26 as well as from infrastructure deployed through 2025 that will recognize a full year of depreciation next year. We also expect a greater mix of our CapEx to be in shorter lived assets in 2025 and 2026 than it has been in prior years. And then the other component of infra cost growth next year would come from higher operating expenses, including energy costs, leases, maintenance, and operational expenses that are associated with maintaining that fleet. And we also expect some increased spend on cloud services in '26 to meet our capacity needs as well as growth in network related costs. So a lot going on on the infrastructure side as it contributes to the 2026 total expense number. After that, employee compensation is the next largest driver of expense growth in '26, again, primarily in the investments that we're making in technical talent, including recognizing a full year of compensation expense for the AI talent we hire this year. I realize this answer is getting a little long, so I'll try to wrap up quickly. On the CapEx side, you know, the big driver of our increased CapEx in '26 will be scaling GenAI capacity as we build out training capacity. That's gonna drive higher spend across, you know, servers, networking, data centers next year. We also expect that we're gonna continue investing significantly in CoreAI in 2026. And, again, this is a pretty, you know, very dynamic area of planning, but we wanted to share kind of our our early thoughts as things are shaping up. **Operator**: Your next question comes from the line of Brian Nowak with Morgan Stanley. Please go ahead. **Brian Nowak** (Managing Director , Morgan Stanley): Thanks for taking my question. I've I've two that the first one, Mark, just to kinda go back to the intelligence lab and serve the the vision for super intelligence. As you sort of sit here now versus twelve months ago, can you just sort of walk us through any any changes of technological constraints or technological gating factors that you are most focused on overcoming in the next twenty four months that may have been different than they were in the past just to make sure you can really lead in the idea of superintelligence over the next ten years? And then the second one, to Susan or Mark, one on the core. You've made so many improvements to the core to drive higher engagement recommendations, etcetera. Can you just walk us through a couple of the factors you're still most excited about to come in the next eighteen months that you think could drive further lift to engagement on the on the core platform? Thanks. </chunk> <chunk> [Document ID: Index]: [131:12] Ticker: META Publication Date: 2025-07-30 Doc Type: earnings-call-transcript Period: Q2 2025 Highlighted Text: **Douglas Anmuth** (MD & Internet Analyst, JP Morgan): Thanks so much for taking the questions. One for Mark and one for Susan. Mark, Meta has been a huge proponent of open source AI. How has your thinking changed here at all just as you pursue superintelligence and push for even greater returns on your significant infrastructure investments? And then, Susan, your comments on 26 CapEx suggest more than $100,000,000,000 of spend next year potentially. Do you continue to expect to finance all this yourself, or could there be opportunities to partner here? Thanks. **Mark Zuckerberg** (Founder, Chairman & CEO, Meta Platforms): Yeah. I mean, on on open source, I don't think that our thinking has particularly changed on this. We've always open sourced some of our models and not open sourced everything that we've done. So I would expect that we will continue to produce and share leading open source models. I also think that there are couple of trends that are playing out. One is that we're getting models that are so big that they're just not practical for a lot of other people to use. So it's we we kind of wrestle with whether it's productive or helpful to share that or if that's, you know, really just primarily helping competitors or something like that. So I think that there's there's that concern. And then, obviously, as you approach real superintelligence, I think there's a whole different set of safety concerns that I think we need to take very seriously that I that I wrote about in in in my note this morning. But I think the bottom line is I I I would expect that we will continue open sourcing work. I I expect us to continue to be a leader there. I also expect us to continue to not open source everything that we do, which is a continuation of of kind of what we what we've been been kind of working on. And and, yeah, I mean, I I think Susan will talk a little bit more about the infrastructure, but it it really is a a massive investment. Know, we think it will be good over time, but, you know, we we do take very seriously that this is a, just massive amount of capital to convert into many gigawatts of compute, which we think is is going to help us produce, leading research and and quality products in in running the business. I do look for opportunities to basically convert capital into quality of products that we can deliver for people, But this is is certainly a a a massive bet that we're we're we're kind of we're focused on, and and we wanna make sure that what we that what we build accrues to building the best products that we can deliver to the billions of people who use our services. **Susan Li** (CFO, Meta Platforms): Doug, on your second question about how, we expect to finance, the the growing CapEx next year, we certainly expect that we will we will finance, you know, some some large large share of that ourselves, but we're also exploring ways to work with financial partners to co develop data centers. We don't have any finalized transactions to announce, but we generally believe that there will be models here that will attract significant external financing to support large scale data center projects, that are developed using, you know, our ability to build world world class infrastructure while providing us with flexibility should our infrastructure requirements change over time. So we are exploring many different paths. **Operator**: Your next question comes from the line of Justin Post with Bank of America. Please go ahead. **Justin post** (Managing Director, Bank of America Merrill Lynch): Great. Thank you. I'll ask another one on the infrastructure. Mark, your spend is now approaching some of the biggest hyperscalers out there. Do Do you think of all this capacity mostly for internal uses, or do you think there's a way to share or even come up with a business model where leveraging that capacity for external uses? And then, Susan, when when you think about the the ROI on this CapEx, I'm sure you have internal models. I'm sure you can't share all that. But how are you thinking about the ROI, and are you optimistic about the long term returns? Thank you. </chunk>
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    [Total chunks returned: 8] <chunk> [Document ID: Index]: [313:3] Ticker: ORCL Publication Date: 2025-09-09 Doc Type: earnings-call-transcript Period: Q1 2026 Highlighted Text: **Larry Ellison** (Chairman and CTO, Oracle Corporation): Thank you, Safra. Eventually, AI will change everything. Right now, AI is fundamentally transforming Oracle and the rest of the computer industry, though not everyone fully grasps the extent of the tsunami that is approaching. Look at our quarterly numbers. Some things are undeniably evident. Several world-class AI companies have chosen Oracle to build large-scale GPU-centric data centers to train their AI models. That's because Oracle builds GW-scale data centers that are faster and more cost-efficient at training AI models than anyone else in the world. Training AI models is a gigantic multi-trillion dollar market. It's hard to conceive of a technology market as large as that one. If you look close, you can find one that's even larger. It's the market for AI inferencing. Millions of customers using those AI models to run businesses and governments. In fact, the AI inferencing market will be much, much larger than the AI training market. AI inferencing will be used to run robotic factories, robotic cars, robotic greenhouses, biomolecular simulations for drug design, interpreting medical diagnostic images and laboratory results, automating laboratories, placing bets in financial markets, automating legal processes, automating financial processes, automating sales processes. AI is going to write, that is, generate, the computer programs called AI agents that will automate your sales and marketing processes. Let me repeat that. AI is going to automatically write the computer programs that will then automate your sales processes and your legal processes and everything else, and your factories, and so on. Think about it. AI inferencing. It's AI inferencing that will change everything. Oracle is aggressively pursuing the AI, and we're not doing badly in the AI training market, by the way. Inferencing is bigger. Oracle is aggressively pursuing the inferencing market, as well as the AI training market. We think we are in a pretty good position to be a winner in the inferencing market because Oracle is by far the world's largest custodian of high-value private enterprise data. With the introduction of our new AI database, we added a very important new way for you to store your data in our database. You can vectorize it. By vectorizing it, by vectorizing all your data, all your data can be understood by AI models. We made it very easy for our customers to directly connect all their databases, all their new Oracle AI Databases, and cloud storage, OCI cloud storage, to the world's most advanced AI reasoning models: ChatGPT, Gemini, Grok, Llama, all of which are uniquely available in the Oracle Cloud. After you vectorize your data and link it to an LLM, the LLM of your choice, you can then ask any question you can think of. For example, how will the latest tariffs impact next quarter's revenue and profit? You ask that question, the large language model will then apply advanced reasoning to the combination of your private enterprise data plus publicly available data. You get answers to important questions without ever compromising the safety and security of your private data. I would like you to think about this for a moment. A lot of companies are saying, we're big into AI because we're writing agents. Guess what? We're writing a bunch of agents too. When they introduced ChatGPT almost three years ago, what you got to do is have a conversation and ask questions. You were not automating some process with an agent. </chunk> <chunk> [Document ID: Index]: [314:5] Ticker: ORCL Publication Date: 2025-09-09 Doc Type: earnings-call-transcript Period: Q1 2026 Highlighted Text: **Ken Bond** (Head of Investor Relations, Oracle Corporation): Thank you, Larry. Tiffany, please poll the audience for questions. **Operator**: At this time, if you would like to ask a question, press star, then the number one on your telephone keypad. To withdraw your question, simply press star one again. We will pause for just a moment to compile the Q&A roster. Your first question comes from the line of John DiFucci with Guggenheim Securities. Please go ahead. **John DiFucci** (Senior Managing Director and Senior Research Analyst, Guggenheim Securities): Thank you for taking my question. Listen, even I am sort of blown away by what this looks like going forward. This question, I guess, is sort of purposely open-ended. Larry and Safra, Oracle's become the de facto standard for AI training workloads, and you make money at it. I have a lot of faith in that. Clearly, there's more here than just AI training. I know it's a big part of it. You talked about it. Can you talk about what else, a little more detail about what else is driving these pretty amazing forecasts? **Safra Catz** (CEO, Oracle Corporation): Go ahead, Larry. I think that you were just covering this. **Larry Ellison** (Chairman and CTO, Oracle Corporation): A lot of people are looking for inferencing capacity. People are running out of inferencing capacity. The company that called us, I mentioned it, I think either last quarter or the quarter before, someone called us, we'll take all the capacity you have that's currently not being used anywhere in the world. We don't care. I'd never gotten a call like that. That's a very unusual call. That was for inferencing, not training. There's a huge amount of demand for inferencing. If you think about it, in the end, all this money we're spending on training is going to have to be translated into products that are sold, which is all inferencing. The inferencing market, again, is much larger than the training market. Yes, we are building, like everybody else, we're building agents with our applications. We're doing much more than that. No one's shown me a ChatGPT 3.5 again. Three years ago, three and a half, three years ago, a little less than three years ago, when ChatGPT amazed the world, you could simply talk to your computer and ask questions and get well-reasoned questions based on the latest and most precise information, as long as you ask those questions about publicly available data. There's a lot of publicly available data. If you combine the publicly available data with the enterprise data, which companies really don't want to share, you have to do it in such a way that your private enterprise data stays private, yet the large language model can still use it for reasoning. As to answer your question, like how do the latest tariffs or the latest steel prices or whatever affect my quarterly results, affect my ability to deliver products, affect my revenue, affect my costs, answer those kinds of questions. To answer those kinds of questions, we have to, and we have, we had to change our database, fundamentally change our database, so you can vectorize all data. That's the form in which large language models understand information exactly after it's been vectorized. Then allowing people to ask any question they want about anything. That's exactly what we've done. Unless you have a database that is secure and reliable and linked to all of the popular LLMs, and we've done all of that, unless you have that, you have to tell me who else has that besides Oracle. Unless you have that, this can be very hard for you to deliver a ChatGPT-like experience on top of your data as well as publicly available data. That is a unique value proposition for Oracle. That is because, again, we're the custodian of all of much more data than any of the application companies. They have their application data. They measure their customers in tens of thousands. We measure our customers in millions of databases. We think we're better positioned than anybody to take advantage of inferencing. </chunk> <chunk> [Document ID: Index]: [315:5] Ticker: ORCL Publication Date: 2025-09-09 Doc Type: earnings-call-transcript Period: Q1 2026 Highlighted Text: **Ken Bond** (SVP, Investor Relations, Oracle): Thank you, Larry. Tiffany, please poll the audience for questions. **Operator**: At this time, if you would like to ask a question, press star, then the number one on your telephone keypad. To withdraw your question, simply press star one again. We will pause for just a moment to compile the Q&A roster. Your first question comes from the line of John DiFucci with Guggenheim Securities. Please go ahead. **John DiFucci** (Senior Managing Director, Guggenheim Partners): Thank you for taking my question. Listen, even I am sort of blown away by what this looks like going forward. This question, I guess, is sort of purposely open-ended. Larry and Safra, Oracle's become the de facto standard for AI training workloads, and you make money at it. I have a lot of faith in that. Clearly, there's more here than just AI training. I know it's a big part of it. You talked about it. Can you talk about what else, a little more detail about what else is driving these pretty amazing forecasts? **Safra Catz** (Chief Executive Officer, Oracle): Go ahead, Larry. I think that you were just covering this. **Larry Ellison** (Chairman & CTO, Oracle): A lot of people are looking for inferencing capacity. People are running out of inferencing capacity. The company that called us, I mentioned it, I think either last quarter or the quarter before, someone called us, we'll take all the capacity you have that's currently not being used anywhere in the world. We don't care. I'd never gotten a call like that. That's a very unusual call. That was for inferencing, not training. There's a huge amount of demand for inferencing. If you think about it, in the end, all this money we're spending on training is going to have to be translated into products that are sold, which is all inferencing. The inferencing market, again, is much larger than the training market. Yes, we are building, like everybody else, we're building agents with our applications. We're doing much more than that. No one's shown me a ChatGPT 3.5 again. Three years ago, three and a half, three years ago, a little less than three years ago, when ChatGPT amazed the world, you could simply talk to your computer and ask questions and get well-reasoned questions based on the latest and most precise information, as long as you ask those questions about publicly available data. There's a lot of publicly available data. If you combine the publicly available data with the enterprise data, which companies really don't want to share, you have to do it in such a way that your private enterprise data stays private, yet the large language model can still use it for reasoning. As to answer your question, like how do the latest tariffs or the latest steel prices or whatever affect my quarterly results, affect my ability to deliver products, affect my revenue, affect my costs, answer those kinds of questions. To answer those kinds of questions, we have to, and we have, we had to change our database, fundamentally change our database, so you can vectorize all data. That's the form in which large language models understand information exactly after it's been vectorized. Then allowing people to ask any question they want about anything. That's exactly what we've done. Unless you have a database that is secure and reliable and linked to all of the popular LLMs, and we've done all of that, unless you have that, you have to tell me who else has that besides Oracle. Unless you have that, this can be very hard for you to deliver a ChatGPT-like experience on top of your data as well as publicly available data. That is a unique value proposition for Oracle. That is because, again, we're the custodian of all of much more data than any of the application companies. They have their application data. They measure their customers in tens of thousands. We measure our customers in millions of databases. We think we're better positioned than anybody to take advantage of inferencing. </chunk> <chunk> [Document ID: Index]: [313:5] Ticker: ORCL Publication Date: 2025-09-09 Doc Type: earnings-call-transcript Period: Q1 2026 Highlighted Text: **Ken Bond** (Head of Investor Relations, Oracle Corporation): Thank you, Larry. Tiffany, please poll the audience for questions. **Operator**: At this time, if you would like to ask a question, press star, then the number one on your telephone keypad. To withdraw your question, simply press star one again. We will pause for just a moment to compile the Q&A roster. Your first question comes from the line of John DiFucci with Guggenheim Securities. Please go ahead. **John DiFucci** (Senior Managing Director and Senior Research Analyst, Guggenheim Securities): Thank you for taking my question. Listen, even I am sort of blown away by what this looks like going forward. This question, I guess, is sort of purposely open-ended. Larry and Safra, Oracle's become the de facto standard for AI training workloads, and you make money at it. I have a lot of faith in that. Clearly, there's more here than just AI training. I know it's a big part of it. You talked about it. Can you talk about what else, a little more detail about what else is driving these pretty amazing forecasts? **Safra Catz** (CEO, Oracle Corporation): Go ahead, Larry. I think that you were just covering this. **Larry Ellison** (Chairman and CTO, Oracle Corporation): A lot of people are looking for inferencing capacity. People are running out of inferencing capacity. The company that called us, I mentioned it, I think either last quarter or the quarter before, someone called us, we'll take all the capacity you have that's currently not being used anywhere in the world. We don't care. I'd never gotten a call like that. That's a very unusual call. That was for inferencing, not training. There's a huge amount of demand for inferencing. If you think about it, in the end, all this money we're spending on training is going to have to be translated into products that are sold, which is all inferencing. The inferencing market, again, is much larger than the training market. Yes, we are building, like everybody else, we're building agents with our applications. We're doing much more than that. No one's shown me a ChatGPT 3.5 again. Three years ago, three and a half, three years ago, a little less than three years ago, when ChatGPT amazed the world, you could simply talk to your computer and ask questions and get well-reasoned questions based on the latest and most precise information, as long as you ask those questions about publicly available data. There's a lot of publicly available data. If you combine the publicly available data with the enterprise data, which companies really don't want to share, you have to do it in such a way that your private enterprise data stays private, yet the large language model can still use it for reasoning. As to answer your question, like how do the latest tariffs or the latest steel prices or whatever affect my quarterly results, affect my ability to deliver products, affect my revenue, affect my costs, answer those kinds of questions. To answer those kinds of questions, we have to, and we have, we had to change our database, fundamentally change our database, so you can vectorize all data. That's the form in which large language models understand information exactly after it's been vectorized. Then allowing people to ask any question they want about anything. That's exactly what we've done. Unless you have a database that is secure and reliable and linked to all of the popular LLMs, and we've done all of that, unless you have that, you have to tell me who else has that besides Oracle. Unless you have that, this can be very hard for you to deliver a ChatGPT-like experience on top of your data as well as publicly available data. That is a unique value proposition for Oracle. That is because, again, we're the custodian of all of much more data than any of the application companies. They have their application data. They measure their customers in tens of thousands. We measure our customers in millions of databases. We think we're better positioned than anybody to take advantage of inferencing. </chunk> <chunk> [Document ID: Index]: [212:5] Ticker: ORCL Publication Date: 2025-09-09 Doc Type: earnings-call-transcript Period: Q1 2026 Highlighted Text: **Speaker 4**: Thank you, Larry. Tiffany, please poll the audience for questions. **Speaker 0**: At this time, if you would like to ask a question, press star, then the number one on your telephone keypad. To withdraw your question, simply press star one again. We will pause for just a moment to compile the Q&A roster. Your first question comes from the line of John DiFucci with Guggenheim Securities. Please go ahead. **Speaker 2**: Thank you for taking my question. Listen, even I am sort of blown away by what this looks like going forward. This question, I guess, is sort of purposely open-ended. Larry and Safra, Oracle's become the de facto standard for AI training workloads, and you make money at it. I have a lot of faith in that. Clearly, there's more here than just AI training. I know it's a big part of it. You talked about it. Can you talk about what else, a little more detail about what else is driving these pretty amazing forecasts? **Speaker 0**: Go ahead, Larry. I think that you were just covering this. **Speaker 4**: A lot of people are looking for inferencing capacity. People are running out of inferencing capacity. The company that called us, I mentioned it, I think either last quarter or the quarter before, someone called us, we'll take all the capacity you have that's currently not being used anywhere in the world. We don't care. I'd never gotten a call like that. That's a very unusual call. That was for inferencing, not training. There's a huge amount of demand for inferencing. If you think about it, in the end, all this money we're spending on training is going to have to be translated into products that are sold, which is all inferencing. The inferencing market, again, is much larger than the training market. Yes, we are building, like everybody else, we're building agents with our applications. We're doing much more than that. No one's shown me a ChatGPT 3.5 again. Three years ago, three and a half, three years ago, a little less than three years ago, when ChatGPT amazed the world, you could simply talk to your computer and ask questions and get well-reasoned questions based on the latest and most precise information, as long as you ask those questions about publicly available data. There's a lot of publicly available data. If you combine the publicly available data with the enterprise data, which companies really don't want to share, you have to do it in such a way that your private enterprise data stays private, yet the large language model can still use it for reasoning. As to answer your question, like how do the latest tariffs or the latest steel prices or whatever affect my quarterly results, affect my ability to deliver products, affect my revenue, affect my costs, answer those kinds of questions. To answer those kinds of questions, we have to, and we have, we had to change our database, fundamentally change our database, so you can vectorize all data. That's the form in which large language models understand information exactly after it's been vectorized. Then allowing people to ask any question they want about anything. That's exactly what we've done. Unless you have a database that is secure and reliable and linked to all of the popular LLMs, and we've done all of that, unless you have that, you have to tell me who else has that besides Oracle. Unless you have that, this can be very hard for you to deliver a ChatGPT-like experience on top of your data as well as publicly available data. That is a unique value proposition for Oracle. That is because, again, we're the custodian of all of much more data than any of the application companies. They have their application data. They measure their customers in tens of thousands. We measure our customers in millions of databases. We think we're better positioned than anybody to take advantage of inferencing. </chunk> <chunk> [Document ID: Index]: [212:3] Ticker: ORCL Publication Date: 2025-09-09 Doc Type: earnings-call-transcript Period: Q1 2026 Highlighted Text: **Speaker 3**: Thank you, Safra. Eventually, AI will change everything. Right now, AI is fundamentally transforming Oracle and the rest of the computer industry, though not everyone fully grasps the extent of the tsunami that is approaching. Look at our quarterly numbers. Some things are undeniably evident. Several world-class AI companies have chosen Oracle to build large-scale GPU-centric data centers to train their AI models. That's because Oracle builds gigawatt-scale data centers that are faster and more cost-efficient at training AI models than anyone else in the world. Training AI models is a gigantic multi-trillion dollar market. It's hard to conceive of a technology market as large as that one. If you look close, you can find one that's even larger. It's the market for AI inferencing. Millions of customers using those AI models to run businesses and governments. In fact, the AI inferencing market will be much, much larger than the AI training market. AI inferencing will be used to run robotic factories, robotic cars, robotic greenhouses, biomolecular simulations for drug design, interpreting medical diagnostic images and laboratory results, automating laboratories, placing bets in financial markets, automating legal processes, automating financial processes, automating sales processes. AI is going to write, that is, generate, the computer programs called AI agents that will automate your sales and marketing processes. Let me repeat that. AI is going to automatically write the computer programs that will then automate your sales processes and your legal processes and everything else, and your factories, and so on. Think about it. AI inferencing. It's AI inferencing that will change everything. Oracle is aggressively pursuing the AI, and we're not doing badly in the AI training market, by the way. Inferencing is bigger. Oracle is aggressively pursuing the inferencing market, as well as the AI training market. We think we are in a pretty good position to be a winner in the inferencing market because Oracle is by far the world's largest custodian of high-value private enterprise data. With the introduction of our new AI database, we added a very important new way for you to store your data in our database. You can vectorize it. By vectorizing it, by vectorizing all your data, all your data can be understood by AI models. We made it very easy for our customers to directly connect all their databases, all their new Oracle AI Databases, and cloud storage, OCI cloud storage, to the world's most advanced AI reasoning models: ChatGPT, Gemini, Grok, Llama, all of which are uniquely available in the Oracle Cloud. After you vectorize your data and link it to an LLM, the LLM of your choice, you can then ask any question you can think of. For example, how will the latest tariffs impact next quarter's revenue and profit? You ask that question, the large language model will then apply advanced reasoning to the combination of your private enterprise data plus publicly available data. You get answers to important questions without ever compromising the safety and security of your private data. I would like you to think about this for a moment. A lot of companies are saying, we're big into AI because we're writing agents. Guess what? We're writing a bunch of agents too. When they introduced ChatGPT almost three years ago, what you got to do is have a conversation and ask questions. You were not automating some process with an agent. </chunk> <chunk> [Document ID: Index]: [314:10] Ticker: ORCL Publication Date: 2025-09-09 Doc Type: earnings-call-transcript Period: Q1 2026 Highlighted Text: **Larry Ellison** (Chairman and CTO, Oracle Corporation): I can do it with one sentence. Our networks move data very, very fast. If we can move data faster than the other people, if we have advantages in our GPU superclusters that are performance advantages, if you're paying by the hour, if we're twice as fast, we're half the cost. **Mark Moerdler** (Managing Director, SVP and Senior Research Analyst, Bernstein Research): That's tight. **Safra Catz** (CEO, Oracle Corporation): Our defense. **Larry Ellison** (Chairman and CTO, Oracle Corporation): I agree. **Mark Moerdler** (Managing Director, SVP and Senior Research Analyst, Bernstein Research): Thank you. **Operator**: Your final question comes from the line of Alex Zukin with Wolfe Research. Please go ahead. **Alex Zukin** (Managing Director and Software Equity Research Analyst, Wolfe Research): Hey, guys. I really appreciate you squeezing me in. I originally was going to ask you if the new Oracle AI Database really opens up the general enterprise inferencing market. Based on your script, it sounds like the answer to that question is hell yes. I guess my follow-up question would be, how do you see that pacing happening over the course of the next few years? How soon after the introduction of the Oracle AI Database would you expect your enterprise customers, your sophisticated customers, to really be open to interrogating their enterprise data in this fashion? How does the current supply constraint environment stand in the way of that demand, or is it solving as we speak? **Safra Catz** (CEO, Oracle Corporation): I don't know if, Larry, you want to cover it. You covered it in the. **Larry Ellison** (Chairman and CTO, Oracle Corporation): No, I've done it. **Safra Catz** (CEO, Oracle Corporation): Mark, go ahead. **Larry Ellison** (Chairman and CTO, Oracle Corporation): Yeah, you got it. Go ahead. OK. I think who wouldn't want that? I mean, I think everyone says they want to use AI. CEOs say they want to use AI. Heads of state, heads of government say they want to use AI. We've never had consumers like that. Historically, we don't deal with CEOs. Now we deal with CEOs. Now we deal with heads of government and heads of state on this because AI is so important. Letting people use AI on top of their data, that is what they want to do. They didn't know how to do it securely. They didn't know how to do it, period. One of the big risks was, oh my god, I can't share my, you know, JPMorgan Chase can't share all of its data. Goldman Sachs can't share all of its data with OpenAI. They won't do it. Or xAI or Llama or Meta. It's got to keep it private. We've got to keep your private data private. We've got to keep your private data secure. We have to make it available for inferencing by the latest and best reasoning models from OpenAI and xAI and everyone else. Because we have the database, because we can vectorize all the data in the database, because we have very elaborate security models in our database, in the Oracle database, we can do all that. We can deliver all that. What we chose to do with the AI database was not only make sure we can vectorize all the data so it can be understood by the AI model, we then bundled it with all of the AI models. That's why we did a deal with Google. That's why we did all of these deals where Gemini, you can get Gemini from the Oracle Cloud. You can get Grok from the Oracle Cloud. You can get ChatGPT from the Oracle Cloud. You get Llama from the Oracle Cloud. I could go on. We bundled them together so it's very easy for our customers to use these large language models on a combination. That's what they wanted, a combination of all of the publicly available data and all of their enterprise data, which allows them to ask and get answered any question they can think of, any question that's important to them. Everyone wants it. I think the demand is going to be insatiable. We can deliver a lot of databases and a lot of AI across our cloud over the next several years. We're in a good position to do that. **Safra Catz** (CEO, Oracle Corporation): This is going to be one of the reasons that Oracle databases, which are still the bulk of the enterprise market by a lot, are going to finally move into the cloud. Many of them will move in the public cloud using the Oracle AI Database. Many and the largest enterprises will want their own either dedicated regions or Oracle Cloud customer. They can finally get the benefit of AI for their own data using any LLM that they want because they're all in our cloud too. **Alex Zukin** (Managing Director and Software Equity Research Analyst, Wolfe Research): It sounds like very high margin AI revenue, guys. Congratulations. **Safra Catz** (CEO, Oracle Corporation): Thank you. Thank you. OK. </chunk> <chunk> [Document ID: Index]: [314:2] Ticker: ORCL Publication Date: 2025-09-09 Doc Type: earnings-call-transcript Period: Q1 2026 Highlighted Text: **Safra Catz** (CEO, Oracle Corporation): Now, before I dive into specific Q2 guidance, I'd like to share some of the overarching thoughts on fiscal year 2026 and the coming years. Clearly, it was an excellent quarter, and demand for Oracle Cloud Infrastructure continues to build. I expect we will sign additional multi-billion dollar customers and that RPO will likely grow to exceed half a trillion dollars. The enormity of this RPO growth enables us to make a large upward revision to the cloud infrastructure portion of our financial plan. We now expect Oracle Cloud Infrastructure will grow 77% to $18 billion this fiscal year and then increase to $32 billion, $73 billion, $114 billion, and $144 billion over the following four years. Much of this revenue is already booked in our $455 billion RPO number, and we are off to a fantastic start this year. While much attention is focused on our GPU-related business, our non-GPU infrastructure business continues to grow much faster than our competitors. We're also seeing our industry-specific cloud applications drive customers to our back-office cloud apps. Finally, the Oracle database is booming with 34 multi-cloud data centers now live inside of Azure, GCP, and AWS, and we will deliver another 37 data centers for a total of 71. All these trends point to revenue growth going higher. For fiscal year 2026, we remain confident and committed to full-year total revenue growth of 16% in constant currency. Beyond fiscal year 2026, I'm even more confident in our ability to further accelerate our top and bottom line growth rate. As mentioned, we will provide an update on our long-range financial targets at our financial analyst meeting at Oracle AI World in Las Vegas in October. Now, let me turn to my guidance for Q2, which I'll review on a non-GAAP basis, and assuming currency exchange rates remain the same as they are now. Currency should have a $0.03 positive impact on EPS and a 1% positive effect on revenue, depending on rounding. However, the actual currency impact may be different as it was in Q1. Here goes. Total revenue are expected to grow from 12% to 14% in constant currency and are expected to grow from 14% to 16% in U.S. dollars at today's exchange rate. Total cloud revenue is expected to grow from 32% to 36% in constant currency and is expected to grow from 33% to 37% in USD. Non-GAAP EPS is expected to grow between 8% to 10% and be between $1.58 and $1.62 in constant currency. Non-GAAP EPS is expected to grow 10% to 12% and be between $1.61 and $1.65 in USD. Lastly, my EPS guidance for Q2 assumes a base tax rate of 19%. However, one-time tax events could cause actual tax rates to vary as they did this quarter. Larry, over to you. </chunk>
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    [Total chunks returned: 6] <chunk> [Document ID: Index]: [86:7] Ticker: GOOGL Publication Date: 2025-04-24 Section: remark Doc Type: earnings-call-transcript Period: Q1 2025 Highlighted Text: Turning to the Google Cloud segment, which continued to deliver very strong results this quarter. Revenue increased by 28% to $12.3 billion in the first quarter reflecting growth in GCP across core and AI products at a rate that was much higher than cloud's overall revenue growth rate. Growth in Google Workspace was primarily driven by an increase in average revenue per seat. Google Cloud operating income increased to $2.2 billion and operating margin increased from 9.4% to 17.8%. As we scale our fleet, we continue to focus on driving improvements in productivity, efficiency and utilization to offset the growth in expenses, particularly from higher depreciation. As to other bets, for the first quarter, revenues were $450 million, and operating loss was $1.2 billion. The year-on-year decline in revenue and increase in operating loss primarily reflects the milestone payment received in the first quarter of 2024 for one of our other bets. With respect to CapEx, our reported CapEx in the first quarter was $17.2 billion, primarily reflecting investment in our technical infrastructure with the largest component being investment in servers, followed by data centers to support the growth of our business across Google Services, Google Cloud and Google DeepMind. In Q1, we returned value to shareholders in the form of $15.1 billion in share repurchases and $2.4 billion in dividend payments. As we announced today, our Board of Directors declared a 5% increase in our quarterly dividend and also approved and used $70 billion share repurchase authorization. Turning to our outlook. I would like to provide some commentary on several factors that will impact our business performance in the second quarter and the remainder of 2025. First, in terms of revenue, I'll highlight a couple of items that we mentioned last quarter that will have an impact on second quarter and 2025 revenue. First, in Google services, advertising revenue in 2025 will be impacted by lapping the strength we experienced in the financial service vertical throughout 2024. Second, in cloud, we're in a tight demand supply environment and given that revenues are correlated with the timing of deployment of new capacity, we could see variability in cloud revenue growth rates depending on capacity deployment each quarter. We expect relatively higher capacity deployment towards the end of 2025. Moving to investments, starting with our expectation for CapEx for the full year 2025. We still expect to invest approximately $75 billion in CapEx this year. The expected CapEx investment level may fluctuate from quarter-to-quarter due to the impact of changes in the timing of deliveries and construction schedules. In terms of expenses. First, as I mentioned on our previous earnings call, the significant increase in our investments in CapEx over the past few years will continue to put pressure on the P&L, primarily in the form of higher depreciation. In the first quarter, we saw 31% year-on-year growth in depreciation from the increase in technical infrastructure assets placed in service. given the increase in CapEx investments over the past few years, we expect the growth rate in depreciation to accelerate throughout 2025. Second, as we've previously said, we expect some head count growth in 2025 in key investment area. As we've disclosed previously, due to a shift in the timing of our annual employee stock-based compensation awards begin in 2023. Our first quarter stock-based comp expenses is relatively lower compared to the remaining quarters of the year. </chunk> <chunk> [Document ID: Index]: [86:1] Ticker: GOOGL Publication Date: 2025-04-24 Section: remark Doc Type: earnings-call-transcript Period: Q1 2025 Highlighted Text: Sundar Pichai (executive) Thanks, Jim. Good afternoon, everyone. We are pleased with our strong results this quarter. We continue to see healthy growth and momentum across the business, including AI powering new features. In search, we saw continued double-digit revenue growth. AI Overviews is going very well with over 1.5 billion users per month, and we are excited by the early positive reaction to AI mode. There's a lot more to come ahead. In subscriptions, we surpassed 270 million subscriptions with YouTube and Google One as key drivers. And cloud grew rapidly with significant demand for our solutions, and you saw our leadership in AI at Cloud Next across infrastructure, agents and more. Our differentiated full stack approach to AI continues to be central to our growth. This quarter was super exciting as we rolled out Gemini 2.5, our most intelligent AI model, which is achieving breakthroughs in performance and it's widely recognized as the best model in the industry. That's an extraordinary foundation for our future innovation, and we are focused on bringing this to people and customers everywhere. Looking ahead to IO, Brandcast and Google Marketing Live, I can wait for our teams to showcase the innovations they've been working on. Turning to our AI progress this quarter, which continues to enable significant growth opportunities. The elements of the AI stack I've previously mentioned are AI infrastructure, world-class research, including models and tooling and our products and platforms. Starting with AI infrastructure, our long-term investments in our global network have positioned us well. Google's network is robust and resilient, supported by over 2 million miles of fiber and 33 subsea cables. Complementing this, we offer the industry's widest range of TPUs and GPUs and continue to invest in next-generation capabilities. Ironwood, our 7-generation TPU and most powerful to date is the first designed specifically for inference at scale. It delivers more than 10x improvement in compute power or a recent high-performance DPU, while being nearly twice as power efficient. A strong relationship with NVIDIA continues to be a key advantage for us and our customers. We were the first cloud provider to offer NVIDIA's groundbreaking B200 and B200 Blackwell GPUs and will be offering their next-generation veriobin GPUs. Second, this infrastructure powers our world-class research, including our industry-leading models. We released Gemini 2.5 Pro last month, receiving extremely positive feedback from both developers and consumers, 2.5 Pro is state-of-the-art on a wide range of benchmarks and debuted #1 on the chatbot arena by a significant margin. Pro achieved big leaps in reasoning coating, science and math capabilities, opening up new possibilities for developers and customers. Active users in AI studio and Gemini API have grown over 200% since the beginning of the year. And last week, we introduced 2.5 Flash, which enables developers to optimize quality and cost. Our latest image and video generation models, Imagen 3 and Veo 2 are rolling out broadly and are powering incredible creativity. Turning to open models. We launched Gema 3 last month, delivering state-of-the-art performance for its size. Gema models have been download more than 140 million times. Lastly, we are developing AI models in new areas where there's enormous opportunity. For example, our new Gemini Robotics models. And in Health, we launched AI co scientist, a multi-agent AI research system, while AlphaFold has now been used by over 2.5 million researchers. </chunk> <chunk> [Document ID: Index]: [86:7] Ticker: GOOGL Publication Date: 2025-04-24 Section: remark Doc Type: earnings-call-transcript Period: Q1 2025 Highlighted Text: Turning to the Google Cloud segment, which continued to deliver very strong results this quarter. Revenue increased by 28% to $12.3 billion in the first quarter reflecting growth in GCP across core and AI products at a rate that was much higher than cloud's overall revenue growth rate. Growth in Google Workspace was primarily driven by an increase in average revenue per seat. Google Cloud operating income increased to $2.2 billion and operating margin increased from 9.4% to 17.8%. As we scale our fleet, we continue to focus on driving improvements in productivity, efficiency and utilization to offset the growth in expenses, particularly from higher depreciation. As to other bets, for the first quarter, revenues were $450 million, and operating loss was $1.2 billion. The year-on-year decline in revenue and increase in operating loss primarily reflects the milestone payment received in the first quarter of 2024 for one of our other bets. With respect to CapEx, our reported CapEx in the first quarter was $17.2 billion, primarily reflecting investment in our technical infrastructure with the largest component being investment in servers, followed by data centers to support the growth of our business across Google Services, Google Cloud and Google DeepMind. In Q1, we returned value to shareholders in the form of $15.1 billion in share repurchases and $2.4 billion in dividend payments. As we announced today, our Board of Directors declared a 5% increase in our quarterly dividend and also approved and used $70 billion share repurchase authorization. Turning to our outlook. I would like to provide some commentary on several factors that will impact our business performance in the second quarter and the remainder of 2025. First, in terms of revenue, I'll highlight a couple of items that we mentioned last quarter that will have an impact on second quarter and 2025 revenue. First, in Google services, advertising revenue in 2025 will be impacted by lapping the strength we experienced in the financial service vertical throughout 2024. Second, in cloud, we're in a tight demand supply environment and given that revenues are correlated with the timing of deployment of new capacity, we could see variability in cloud revenue growth rates depending on capacity deployment each quarter. We expect relatively higher capacity deployment towards the end of 2025. Moving to investments, starting with our expectation for CapEx for the full year 2025. We still expect to invest approximately $75 billion in CapEx this year. The expected CapEx investment level may fluctuate from quarter-to-quarter due to the impact of changes in the timing of deliveries and construction schedules. In terms of expenses. First, as I mentioned on our previous earnings call, the significant increase in our investments in CapEx over the past few years will continue to put pressure on the P&L, primarily in the form of higher depreciation. In the first quarter, we saw 31% year-on-year growth in depreciation from the increase in technical infrastructure assets placed in service. given the increase in CapEx investments over the past few years, we expect the growth rate in depreciation to accelerate throughout 2025. Second, as we've previously said, we expect some head count growth in 2025 in key investment area. As we've disclosed previously, due to a shift in the timing of our annual employee stock-based compensation awards begin in 2023. Our first quarter stock-based comp expenses is relatively lower compared to the remaining quarters of the year. </chunk> <chunk> [Document ID: Index]: [86:7] Ticker: GOOGL Publication Date: 2025-04-24 Section: remark Doc Type: earnings-call-transcript Period: Q1 2025 Highlighted Text: Turning to the Google Cloud segment, which continued to deliver very strong results this quarter. Revenue increased by 28% to $12.3 billion in the first quarter reflecting growth in GCP across core and AI products at a rate that was much higher than cloud's overall revenue growth rate. Growth in Google Workspace was primarily driven by an increase in average revenue per seat. Google Cloud operating income increased to $2.2 billion and operating margin increased from 9.4% to 17.8%. As we scale our fleet, we continue to focus on driving improvements in productivity, efficiency and utilization to offset the growth in expenses, particularly from higher depreciation. As to other bets, for the first quarter, revenues were $450 million, and operating loss was $1.2 billion. The year-on-year decline in revenue and increase in operating loss primarily reflects the milestone payment received in the first quarter of 2024 for one of our other bets. With respect to CapEx, our reported CapEx in the first quarter was $17.2 billion, primarily reflecting investment in our technical infrastructure with the largest component being investment in servers, followed by data centers to support the growth of our business across Google Services, Google Cloud and Google DeepMind. In Q1, we returned value to shareholders in the form of $15.1 billion in share repurchases and $2.4 billion in dividend payments. As we announced today, our Board of Directors declared a 5% increase in our quarterly dividend and also approved and used $70 billion share repurchase authorization. Turning to our outlook. I would like to provide some commentary on several factors that will impact our business performance in the second quarter and the remainder of 2025. First, in terms of revenue, I'll highlight a couple of items that we mentioned last quarter that will have an impact on second quarter and 2025 revenue. First, in Google services, advertising revenue in 2025 will be impacted by lapping the strength we experienced in the financial service vertical throughout 2024. Second, in cloud, we're in a tight demand supply environment and given that revenues are correlated with the timing of deployment of new capacity, we could see variability in cloud revenue growth rates depending on capacity deployment each quarter. We expect relatively higher capacity deployment towards the end of 2025. Moving to investments, starting with our expectation for CapEx for the full year 2025. We still expect to invest approximately $75 billion in CapEx this year. The expected CapEx investment level may fluctuate from quarter-to-quarter due to the impact of changes in the timing of deliveries and construction schedules. In terms of expenses. First, as I mentioned on our previous earnings call, the significant increase in our investments in CapEx over the past few years will continue to put pressure on the P&L, primarily in the form of higher depreciation. In the first quarter, we saw 31% year-on-year growth in depreciation from the increase in technical infrastructure assets placed in service. given the increase in CapEx investments over the past few years, we expect the growth rate in depreciation to accelerate throughout 2025. Second, as we've previously said, we expect some head count growth in 2025 in key investment area. As we've disclosed previously, due to a shift in the timing of our annual employee stock-based compensation awards begin in 2023. Our first quarter stock-based comp expenses is relatively lower compared to the remaining quarters of the year. </chunk> <chunk> [Document ID: Index]: [86:11] Ticker: GOOGL Publication Date: 2025-04-24 Section: qa Doc Type: earnings-call-transcript Period: Q1 2025 Highlighted Text: Eric Sheridan (analyst) First, maybe for Sundar. When you look across the consumer AI landscape today, how are you thinking about continuing to drive differentiation for Gemini as a platform through the lens of usage, utility or putting product innovation at the forefront of driving consumer habits. And then the second one, maybe for Anat, if the macro environment were to change and become more downwardly volatile, how should investors think about the investments that are must make this year almost fixed in nature versus where there might be more flexibility to alter the investment priorities of the company if the macro environment were to worsen? Sundar Pichai (executive) Thanks, Eric. Obviously, it's an exciting moment on the AI front. I think the foundation for everything is obviously the Frontier model progress we are seeing and particularly with 2.5 pro and flash. I think we're well positioned. We are seeing tremendous reception from developers, enterprises and consumers too. And obviously, we are delivering consumer AI experiences across our product portfolio, including the primary way people experience it is obviously in search with AI Overviews and very early days with AI mode, but that will be a consumer AI forward experience. And we're already seeing very positive feedback. Queries are -- people are typing in roughly 2x longer queries compared to a traditional search. So there's a lot of excitement there. And in the Gemini app, which you asked about, we've really seen increased momentum, particularly over the last few weeks as we've rolled out just the newer models, but we are seeing users are really responding well to all the innovation Gemini Live which is based on Project Astra has been very well received, deep research. I think based on 2.5 Pro is Sota and that's been well received in Canvas, we've had a lot of traction as well. And so we are definitely investing more. We have recently organized ourselves better to capitalize on this momentum, and I'm excited about our road map there. Anat Ashkenazi (executive) And on the investments this year and overall, should there be any macroeconomic changes as I said, we're still planning to invest approximately $75 billion in CapEx this year. we do see a tremendous opportunity ahead of us across the organization, whether it's to support Google services, Google Cloud and Google DeepMin. Recall stated on the Q4 call that we exited the year in cloud specifically with more customer demand than we had capacity. And that was the case this quarter as well. So we want to make sure we ramp up to support customer needs and customer demands. Having said that, we're investing in long term, and we're investing in innovation. That's the essence of our business. and we want to do it in a responsible fashion. So you've seen us over the past couple of years, and we're continuing to do this, and you're seeing this in our results, drive efficiency and productivity throughout the business. And we've announced things such as consolidation of teams, which helps not just with cost, but with velocity and speed. We're able to get things to market faster. So that's one of the areas we're focused on. You heard from Sundar in the last couple of calls and just a rapid pace of innovation we're bringing to the marketplace. So the way we're doing this across the business to drive productivity and efficiency should help us have a more resilient organization irrespective of macroeconomic condition. But certainly, we don't ignore that. We always look at what's happening outside the organization as well as inside but invest appropriately to drive both the short-term growth as well as the long-term growth. Operator Our next question comes from Ross Sandler from Barclays. </chunk> <chunk> [Document ID: Index]: [86:11] Ticker: GOOGL Publication Date: 2025-04-24 Section: qa Doc Type: earnings-call-transcript Period: Q1 2025 Highlighted Text: Eric Sheridan (analyst) First, maybe for Sundar. When you look across the consumer AI landscape today, how are you thinking about continuing to drive differentiation for Gemini as a platform through the lens of usage, utility or putting product innovation at the forefront of driving consumer habits. And then the second one, maybe for Anat, if the macro environment were to change and become more downwardly volatile, how should investors think about the investments that are must make this year almost fixed in nature versus where there might be more flexibility to alter the investment priorities of the company if the macro environment were to worsen? Sundar Pichai (executive) Thanks, Eric. Obviously, it's an exciting moment on the AI front. I think the foundation for everything is obviously the Frontier model progress we are seeing and particularly with 2.5 pro and flash. I think we're well positioned. We are seeing tremendous reception from developers, enterprises and consumers too. And obviously, we are delivering consumer AI experiences across our product portfolio, including the primary way people experience it is obviously in search with AI Overviews and very early days with AI mode, but that will be a consumer AI forward experience. And we're already seeing very positive feedback. Queries are -- people are typing in roughly 2x longer queries compared to a traditional search. So there's a lot of excitement there. And in the Gemini app, which you asked about, we've really seen increased momentum, particularly over the last few weeks as we've rolled out just the newer models, but we are seeing users are really responding well to all the innovation Gemini Live which is based on Project Astra has been very well received, deep research. I think based on 2.5 Pro is Sota and that's been well received in Canvas, we've had a lot of traction as well. And so we are definitely investing more. We have recently organized ourselves better to capitalize on this momentum, and I'm excited about our road map there. Anat Ashkenazi (executive) And on the investments this year and overall, should there be any macroeconomic changes as I said, we're still planning to invest approximately $75 billion in CapEx this year. we do see a tremendous opportunity ahead of us across the organization, whether it's to support Google services, Google Cloud and Google DeepMin. Recall stated on the Q4 call that we exited the year in cloud specifically with more customer demand than we had capacity. And that was the case this quarter as well. So we want to make sure we ramp up to support customer needs and customer demands. Having said that, we're investing in long term, and we're investing in innovation. That's the essence of our business. and we want to do it in a responsible fashion. So you've seen us over the past couple of years, and we're continuing to do this, and you're seeing this in our results, drive efficiency and productivity throughout the business. And we've announced things such as consolidation of teams, which helps not just with cost, but with velocity and speed. We're able to get things to market faster. So that's one of the areas we're focused on. You heard from Sundar in the last couple of calls and just a rapid pace of innovation we're bringing to the marketplace. So the way we're doing this across the business to drive productivity and efficiency should help us have a more resilient organization irrespective of macroeconomic condition. But certainly, we don't ignore that. We always look at what's happening outside the organization as well as inside but invest appropriately to drive both the short-term growth as well as the long-term growth. Operator Our next question comes from Ross Sandler from Barclays. </chunk>

Based on the most recent earnings calls, all major hyperscalers consistently describe demand for compute capacity significantly exceeding current supply:

Amazon (AWS)

AWS CEO Andy Jassy stated clearly: "We have more demand than we have capacity at this point" [1018724_2047440_10]. He identified multiple constraint areas with power being the single biggest constraint, followed by intermittent issues with chips and server components [1018724_2047440_10]. Jassy explicitly noted: "I don't believe that we will have fully resolved the amount of capacity we need for the amount of demand that we have in a couple quarters. I think it will take several quarters" [1018724_2047440_10]. AWS operates at a $123B annual revenue run rate [1018724_2047440_8].

Microsoft (Azure)

Microsoft reported bringing additional data center capacity online in Q4 2025 but emphasized "demand remains higher than supply" [789019_2043806_6]. CFO Amy Hood guided that they "expect to remain capacity constrained through the first half of our fiscal year" (H1 FY2026) [789019_2043806_8]. She noted they expected better supply-demand balance by June but now hopes for improvement by December, stating: "that's not because we slowed CapEx...we are still seeing demand improve" [789019_2043806_13]. Microsoft stood up more than 2 gigawatts of new capacity over the past 12 months [789019_2043806_1] and has $368B in contracted backlog [789019_2043806_5].

Google Cloud

CFO Anat Ashkenazi described being "in a tight demand supply environment" [1652044_GOOGL_3423209_7]. She noted they "exited the year in cloud specifically with more customer demand than we had capacity. And that was the case this quarter as well" [1652044_GOOGL_3423209_11]. Google expects "variability in cloud revenue growth rates depending on capacity deployment each quarter" with relatively higher capacity deployment towards end of 2025 [1652044_GOOGL_3423209_7]. Full year 2025 CapEx is approximately $75B [1652044_GOOGL_3423209_11].

Meta

Meta is focused on ensuring sufficient capacity for internal use cases including ads ranking, recommendation engines, and frontier AI model training [1326801_2043767_13]. CEO Mark Zuckerberg announced building multi-gigawatt clusters: "Prometheus cluster is coming online next year, and we think it's going to be the world's first gigawatt plus cluster. We're also building out Hyperion, which will be able to scale up to five gigawatts over several years" [1326801_2043767_1]. CFO Susan Li guided to CapEx of $66-72B in 2025 with "another year of similarly significant CapEx dollar growth in 2026" [1326801_2043767_7], suggesting spending exceeding $100B.

Oracle

Oracle CTO Larry Ellison highlighted extreme demand, particularly for inferencing: "People are running out of inferencing capacity" [1341439_2134105_5]. He described receiving an unprecedented call: "someone called us, we'll take all the capacity you have that's currently not being used anywhere in the world. We don't care. I'd never gotten a call like that" [1341439_2134105_5]. Oracle has $455B in remaining performance obligations [1341439_2134034_2].

Summary

The universal message across hyperscalers is clear: demand substantially exceeds supply, with constraints expected to persist for multiple quarters despite massive capital investments ($30B+ quarterly for some providers). All are aggressively building capacity but acknowledge demand continues outpacing their ability to bring new infrastructure online.