# Index

LLMS index: [llms.txt](/en/llms.txt)

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The page numbers in this index refer to the printed version of the book. Each link will take you to the beginning of the corresponding print page. You may need to scroll forward from that location to find the corresponding reference on your e-reader.

## A
- Abbeel, Pieter, 49, 118, 235
- Abbott, Andy, 30
- acceleration risk, 232, 249
- Acemoglu, Daron, 88–89
- Achiam, Joshua, 406
- African Content Moderators Union, 416
- AGI (artificial general intelligence), 47–48, 76–79, 129–31, 232, 388–89
  - Google and, 24–25
  - OpenAI and Altman, 7–8, 12–13, 19, 31, 47–
    48, 49, 62, 65, 67, 75, 111, 121–22, 142–43, 183, 240, 253,
    254–55, 301, 319, 357, 400–402, 405
  - use of term, 76–77, 93–94
- Agnew, William, 102, 106, 161
- agriculture, 229, 292–93
- Aguirre, Blaise, 338
- AI (artificial intelligence)
  - AGI compared with, 76–77
  - anthropomorphizing, 90–91, 111
  - author’s reporting, 14–16
  - benefits of, 13, 16, 19, 76, 77–78, 84–85, 88–89, 90, 333–
    34, 400, 418
  - commercialization of, 14–15, 51, 75, 101–15, 150–52
  - definition of intelligence, 90–94
  - empires of, 16–20, 197, 222–23, 270, 414, 418, 420
  - funding, 101–6, 110, 132
  - model training, 4, 61, 98, 134–37, 163, 244–45, 278–81, 307
  - regulatory policy, 25, 27, 84, 86, 134, 136, 265, 272, 301, 303–4,
    306–7, 311–12, 357, 358, 384
  - research and development, 13, 14, 17–18, 64, 89–90, 101–6, 110
    paper conventions and peer review, 15, 15n
  - research faculty exodus, 105–6, 134
  - risks and harms of, 16–19, 23–27, 55–58, 78–81, 106–10, 380
  - scraping, 102–3, 114, 134–38, 151–52, 182–84, 384
  - theories of, 94–101
  - timeline, 93, 133, 232–33, 260, 388–89
  - total corporate investments in, 105
  - use of term, 90, 91, 400
- AI alignment, 26, 248
  - misalignment, 55, 86, 124, 145–46, 320, 347
  - OpenAI, 54, 70, 86, 122–23, 164, 240, 248, 250, 262, 315–18, 347
  - Superalignment, 316–17, 353, 387–88
- AI Index, 105
- AI Insight Forums, 311
- AI Now Institute, 308
- Airbnb, 36, 41, 136, 150, 202, 367
- air pollution, 286
- AI safety, 55–58, 122–32, 301–12, 316–24, 419. See also data
  - privacy; existential risks
  - alignment and, 122–23, 124, 145–46, 316–18
  - effective altruism and, 55–56, 230–34, 321–22
  - Frontier Model Forum, 305–6, 309
  - Senate Judiciary Hearing, 301–3, 307–9, 314–15
  - thresholds, 301–2, 305–8, 310–11
- AI Scientist, 183, 318–19, 325, 347, 375
- “AI takeoff,” 232
- “AI winter,” 97, 435n
- Alameda Research, 231
- Algorithmic Justice League, 161
- algorithms, 51–52, 56, 373–74
- Algorithms of Oppression (Noble), 162
- Alibaba, 15, 159
- Alignment Manhattan Project, 315–18
- Allen & Company, 67–68
- Alphabet, 105
- AlphaFold, 309–10
- AlphaGo, 59, 93
- Altman, Annie, 43–45, 326–40, 352–55, 406, 458–59n
  - appeals to family for financial help, 327, 331–32
  - death of father, 329–31
  - early life and education of, 29, 30, 328–29
  - mental health struggles of, 44–45, 329–30, 331–32, 339–40
  - New York magazine article, 326–27, 328–29, 332–33, 336–40, 343, 352
  - physical health struggles of, 329, 332–33
  - sexual abuse allegations of, 3, 44–45, 327–28, 334–38, 352–53, 406
  - sex work of, 326, 332–36
- Altman, Jack, 29, 30, 35–36, 41, 69, 185, 327–28, 331, 336
- Altman, Jerold “Jerry,” 29–31, 44, 329–31, 332
- Altman, Max, 29, 30, 36, 326, 327–28, 331
- Altman, Sam
  - AI chip company plan, 3, 377–78
  - background of, 23, 29–30
  - benefits of AGI, 19, 405
  - birth and early life of, 29, 30–31
  - board of directors and, 40, 252–53, 320–25, 375–76
    leadership questions, 345–65
  - business structure of OpenAI, 13–14, 61–64, 66–67, 86, 402–3, 407
  - ChatGPT, 260, 261, 262, 280, 346
  - commercialization plan, 66–67, 150–51
  - compute phases, plan, 278–81
  - conflicts and rifts at OpenAI, 149, 150–51, 233–34, 313–16, 396
  - congressional testimony of, 301–3, 314–15
  - education of, 30–32
  - effective altruism ideology and, 233–34
  - equity crisis and, 388–90, 392–96
  - firing and reinstatement of, 1–12, 14, 364–73
    the investigation, 369–70, 375–76, 377, 392
  - founding of OpenAI, 12–13, 26–28, 46, 47–51, 53–54
  - fundraising, 61–62, 65–68, 71–72, 132, 141, 156, 262, 320–
    21, 331, 367, 377, 405
  - GPT-3, 133–34, 278–79
  - GPT-4, 246, 248–52, 279, 346, 383–84, 386, 390–91
  - Graham and, 28, 32, 36–39, 40, 69
  - “Intelligence Age,” 19, 405
  - Jobs comparisons with, 2, 34, 35, 37
  - Johansson crisis, 382, 390–92, 393
  - leadership of, 64–65, 69–70, 75, 141–44, 243–44, 354–55, 403–4
  - leadership behavior, 345–60, 361–65, 382–83, 385–86
  - Loopt and, 32–37, 43, 68
  - Manhattan Project, 146–47, 315–17
  - Mayo’s office design and, 74
  - media relations of, 33, 34, 383
  - mission of OpenAI, 5, 400–402
  - MIT Technology Review and, 86–87
  - on Napoleon, 399–400
  - net worth of, 35, 44, 188, 389, 390
  - other investment projects of, 3, 185–88
  - paranoia of, 147–48
  - personality of, 31, 34, 42–45, 333, 346
  - politics of, 41–42, 43, 62
  - research road map, 59, 175–78
  - retreat of October 2022, 256–57
  - Scallion, 379–80, 380, 382
  - sexuality of, 31, 41
  - sister Annie and, 43–45, 326–40, 385–86, 406
    sexual abuse allegations, 3, 44–45, 327–28, 334–38, 352–53, 356
  - success formula of, 32–35, 37, 142–44
  - vision for OpenAI, 9, 83, 142–43, 262
  - World Tour of, 312, 313, 337
  - at Y Combinator (YC), 23, 27–28, 32, 34, 36–38, 39, 43, 68–
    69, 75, 141, 142, 185, 186, 187–88, 321
- altruism, 13, 14, 400. See also effective altruism
- Amazon, 41, 46, 142, 161
  - data centers, 274–75, 277, 287
  - Mechanical Turk, 194
- American Sign Language, 254
- Amodei, Daniela, 55–56, 58, 144–45, 156, 157, 230
- Amodei, Dario, 55–58
  - AI safety and risks, 55–56, 57–58, 87, 122–27, 131, 133, 134, 145–
    46, 147, 149–52, 156–57, 362
  - Altman’s firing, 366
  - at Anthropic, 58, 60, 115, 128, 157, 213–14, 230
  - background of, 55
  - The Divorce, 57–58, 156–57, 181, 213, 230, 233, 242, 353
  - Dota 2, 129, 144–45
  - founding of OpenAI, 28, 55
  - GPT-2, 125, 129–32, 150
  - GPT-3, 133–34, 134–35, 144–45, 156
  - Nest, 134–35, 144–45, 150, 151, 156, 244
  - promotion to director of research, 125, 133
  - scaling, 129–33, 156–57
- Android, 100, 239
- “anonymous crowd work” model, 206
- Antel, 291–92
- Anthropic, 6, 60, 115, 157, 233
  - Claude, 261, 358, 379, 400, 404–5, 406
  - founding of, and The Divorce, 58, 128, 157, 213, 230
  - Frontier Model Forum, 305–6, 309
  - FTX bankruptcy and, 257–58
  - Leike joins, 388
  - valuation, 18
- AP Bio, 245–46
- APEC CEO Summit, 2
- APIs (application programming interfaces), 150–51. See also specific APIs
- Apollo 11 (movie), 317
- Apollo program, 317
- Appen, 137, 195, 197–202
- Apple, 30, 202, 334, 402
- Arancibia, Alexandra, 285–87, 296–99, 300
- Arizona, 15, 279, 281, 292
- arms race, 16–17
- Arrakis, 269, 374
- arsenic, 282
- artificial general intelligence. See AGI
- artificial intelligence. See AI
- arXiv, 15n
- asbestos, 288
- Asimov, Isaac, 83
- Atacama Desert, 271–72, 284–87
- atomic bomb, 316–17
- authoritarianism, 71, 147, 195–96, 400
- Authors Guild, 135
- automata studies, 89–90, 434n
- autonomous weapons, 52, 310, 380
- Azure AI, 68, 72, 75, 156, 266, 279

## B
- babbage, 150
- Babbage, Charles, 150
- backpropagation, 97–98
- Baidu, 15, 17, 55, 159, 413
- Bankman-Fried, Samuel, 231–32, 233, 257–58, 380
- Beckham, David, 1
- Bell Labs, 55
- Bender, Emily M., 164–69, 253–54
  - “On the Dangers of Stochastic Parrots,” 164–73, 254, 276, 414
- Bengio, Samy, 161–62, 165, 166–67, 169
- Bengio, Yoshua, 105, 162
- Bezos, Jeff, 41
- Biden, Joe, 115–16, 310
- Bing, 112, 113, 247, 264, 355
- biological viruses, 27
- biological weapons, 305, 309, 310, 380
- Birhane, Abeba, 102, 106, 137–38
- “black box,” 107
- Black in AI, 52, 53, 161
- blacklists, 222
- Black Lives Matter, 152–53, 162–63, 167
- blind spots, 88
- Blip, The, 375, 377, 384, 386, 396, 397–98
- board of directors, of OpenAI
  - Altman’s firing and reinstatement, 1–12, 14, 336, 364–73, 375–
    76, 384, 386, 396, 402
    author’s reporting, 370–73
    the investigation, 369–70, 375–76, 377, 392
    Murati as interim CEO, 1–2, 8, 357, 364–65, 366
    open letter, 10–11, 367–68
  - Altman’s leadership behavior, 324–25, 345–65, 385
  - members departing and joining, 11, 57–58, 58, 320–23, 375
  - oversight questions, 322–25
- Bolt, Usain, 34
- Books2, 135
- Books3, 440n
- Boomers (Boomerism), 233–34, 250, 305–6, 314, 315, 387, 396, 402, 403–
  - 4
- bootstrapping, 49
- borderless science, 308–11
- borderline personality disorder, 338, 460n
- Boric Font, Gabriel, 296–97, 299–300
- Bostrom, Nick, 26–27, 55–56, 57, 122–23
- bot tax, 200
- bottleneck, 47, 78, 244–45, 280, 309
- Boyd, Eric, 266
- Brady, Tom, 231
- brain-scale AI, 60
- Bridgewater Associates, 230
- Brin, Sergey, 249
- Brockman, Anna, 10, 256–57, 333, 338
- Brockman, Greg
  - Altman and, 243–44, 349, 355, 395–96, 406–7
    firing and reinstatement, 2, 6, 8–12, 345–46, 366
    leadership behavior, 34, 363–64
  - author’s 2019 interview, 74–81, 84–85, 159–60, 278
  - background of, 46
  - board of directors and, 240
  - board of directors and oversight, 322–23
  - commercialization plan, 150–51
  - computing infrastructure, 278–79
  - culture and mission of OpenAI, 53–54, 84–85
  - departure of, 404
  - Dota 2, 66, 144–45
  - founding of OpenAI, 28, 46–51
  - governance structure of OpenAI, 61–63
  - GPT-4, 244–48, 250–51, 252, 257, 260, 346
  - Latitude, 180–81
  - leadership of OpenAI, 58–59, 61–62, 63–65, 69, 70, 83, 84–85, 243–
    44
  - Omnicrisis, 396–98
  - recruitment efforts of, 48–49, 53–54, 57–58
  - research road map, 59–61
  - retreat of October 2022, 256–57
  - Scallion, 379–80
  - Stripe, 41, 46, 55, 58, 73, 82
- Brundage, Miles, 248, 250, 314, 388, 406
- Buolamwini, Joy, 161
- Burning Man, 35, 263
- Burrell, Jenna, 93
- Buschatzke, Tom, 281

## C
- California Senate Bill 1047, 311
- cancers, 192, 282, 288, 293, 301, 378
- capped-profit structure, 70, 72, 75, 322, 370–71, 401
- carbon emissions, 79–80, 159–60, 171–73, 275–78, 295, 309
- Carnegie Mellon University, 97, 106, 172
- Carr, Andrew, 385
- Carter, Ashton, 43
- CBRN weapons, 301, 380
- Center for AI Safety, 322
- Center for Security and Emerging Technology (CSET), 7, 307, 321, 357, 358
- Center on Long-Term Risk, 388
- Centre for the Governance of AI, 321–22
- Cerrillos, Chile, 288–91, 296, 297
- CFPB (Consumer Financial Protection Bureau), 419–20
- chatbots, 17, 112–14, 189–90, 217–18, 220
  - ELIZA, 95–97, 111, 420–21
  - GPT-3, 217–18
  - GPT-4, 258–59
  - LaMDA, 153, 253–54
  - Meena, 153
  - Tay, 153
- ChatGPT, 258–62, 267, 280
  - connectionist tradition of, 95
  - GPT-3.5 as basis, 217–18, 258
  - hallucinations problem, 113, 114, 268
  - release, 2, 58, 101, 111, 120, 158, 159, 212, 220, 258–62, 264, 265–
    66, 268, 302
  - sign-up incentive, 267
  - voice mode, 378–79, 380–81, 391
- Chauvin, Derek, 152–53
- Chen, Mark, 381, 405–6
- Chesky, Brian, 41, 367
- Chicago Boys (Chicago school of economics), 272–73, 296
- child sex abuse material (CSAM), 137, 180–81, 189, 192, 208, 237–
  - 39, 241, 242
- Chile, 15, 271–81
  - data centers, 285–91, 295–99
  - extractivism, 272, 273–74, 281–85, 296–99, 417
- Chilean coup d’état of 1973, 273
- Chilean protests of 2019-2022, 291, 296–97
- Chile Project, 272–73
- China
  - AI chips, 115–16, 304
  - AI development, 55, 103, 132, 146, 159, 191, 301, 303–4, 305, 307,
    309–10, 311
  - mass surveillance, 103–4
- Chuquicamata mine collapse of 1957, 281–82
- CIA (Central Intelligence Agency), 155, 273, 321
- Clarifai, 108, 238
- Clark, Jack, 76, 81, 125–28, 154, 156–57, 311
- Clarke, Arthur C., 55
- Claude, 261, 358, 379, 400, 404–5, 406
- clawback clause, 389, 393–96
- climate change, 24, 52, 76–80, 93, 165, 196, 276, 281, 292–95, 301
- Climate Change AI, 77–78, 276
- CLIP, 235, 236
- closed-domain questions, 268
- closed systems, 308–11
- CloudFactory, 206–7, 212–13
- code generation, 151–53, 181–84, 318
- Codex, 184, 243, 247, 269, 318
- cofounders, overview of, 48
- Cogito, 242
- cognition, 109, 119–20
- cognitive dissonance, 227–28
- Cohere, 306–7
- Coinbase, 136
- Collard, Rosemary, 104n
- Colombia, 15, 103
- Colorado River and water usage, 281
- Commerce Department, U.S., 304, 307, 308
- Common Crawl, 135–36, 137, 151, 163
- companion bots, 179, 180
- “compositional generation,” 238
- compression, 122, 235
- compute, 59–61, 115–16, 278–81, 387
  - efficiency, 175–77, 268–69, 375, 419
  - threshold, 98, 301–2, 305–8, 310–11
- Conception, 41
- Conneau, Alexis, 378–79
- connectionism, 94–100, 105, 109–10, 117–18
- content moderation, 136–37, 155, 179–81, 189–90, 238–39. See also data
  - annotation
  - Sama, 190–92, 206–13, 218–19
- Copilot, 238–39, 247–48, 264
- copper, 272, 273, 277, 281, 282–84, 291
- copyright infringement, 90–91, 102, 135, 301, 308, 313, 384
- “costly signals,” 357–58
- cotton gin, 88–89
- Couldry, Nick, 104
- COVID-19 pandemic, 54, 74, 149, 152, 181–
  - 82, 192, 203, 205, 206, 208, 213, 218, 293, 323
- Cowen, Tyler, 399
- Crab Generation, 220–21
- Creative Commons, 182
- cryogenics, 186–87
- cryptocurrencies, 63, 80, 185–86
- CSAM. See child sex abuse material
- CUDA (Compute Unified Device Architecture), 61
- curie, 150
- Curie, Marie, 150
- Curry, Steph, 231
- cybersecurity, 114, 147, 148, 179–80, 380
- Cyc, 97

## D
- DAIR (Distributed AI Research Institute), 414–15, 419
- Dalí, Salvador, 234
- DALL-E, 11, 114, 234–39, 241–42, 258–59, 269
  - avocado armchair, 235, 237–38
- Damon, Matt, 317–18
- D’Angelo, Adam, 321
  - Altman’s firing, 7, 11, 366, 367
  - Altman’s leadership behavior, 324–25, 352, 357, 359–60, 361–62
- Dartmouth Summer Research Project (1856), 89–90, 94
- data annotation, 15, 178, 189–90, 192–223, 414–17
  - Kenya workers, 15, 18, 190–92, 206–13, 415–17
  - Scale AI, 202–6, 213–14
  - self-driving cars, 193–95, 202–6, 214–15
  - Venezuela workers, 195–96, 198–202, 203–4, 218
- data centers, 15, 274–78
  - Altman’s compute phases, 278–81
  - carbon emissions, 79–80, 159–60, 171–73
  - in Chile, 285–91, 295–99
  - energy usage, 77, 80, 274–78, 280–81, 288–90, 294
  - Google, 274–75, 285–91, 295–96
  - in Uruguay, 291–96
- “data colonialism,” 103–4
- data filtering, 137, 155, 177–78
- Dataluna, 289–90
- data privacy, 19–20, 33, 56, 103, 136, 186, 301, 308, 310, 413, 416
- data scraping, 102–3, 114, 134–38, 151–52, 182–84, 384
- “data swamps,” 137–38, 212–13
- Data Workers’ Inquiry, 415–17
- davinci, 150
- da Vinci, Leonardo, 150
- Dean, Jeff, 25, 158, 161–62, 163–65, 170–72
- deepfakes, 79–80, 239, 391
- deep learning, 98–101
  - discriminatory impacts of, 57, 108–9
  - ImageNet, 47, 100–101, 117–18, 259
  - limitations and risks of, 106–10
- DeepMind, 6, 17, 24–26, 48, 66, 158–59, 261–62, 384–85
  - AlphaFold, 309–10
  - AlphaGo, 59, 93
  - OpenAI and ChatGPT, 114, 119–20, 132, 159, 261–62
  - scaling, 132, 158–59
- Democratic Party, 41, 231
- Dempsey, Jessica, 104n
- dense neural networks, 177–78
- Deployment Safety Board (DSB), 248, 323–24, 346, 350, 362, 363
- Desmond-Hellmann, Sue, 376
- Díaz Bejarano, Nicolás, 297–99
- diffusion, 235–36, 375
  - Stable Diffusion, 114, 137, 236, 242, 284
- Digital Realty, 274
- disaster capitalism, 189–223
- discriminatory impact, 51–52, 57, 108–9, 114, 137, 161–
  - 64, 179, 310, 419, 432n
- dissolving empire, 418–19
- distillation, 177, 307
- distress passwords, 149
- Divorce, The, 156–57, 181, 213, 230, 233, 242
- DNNresearch, 47, 50, 98–99, 100
- Doctor Strange (movie), 303
- Doomers (Doomerism), 233–34, 250, 267–68, 305–
  - 6, 308, 310, 311, 314, 315, 317–18, 319, 377, 387, 388–90, 396, 402, 403–4, 419
- doomsday scenario, 26–27
- Dorador, Cristina, 283
- Dota 2, 66–67, 71, 129, 144–45, 244–45
- Dowling, Steve, 154, 256, 382–83
- doxing, 303
- drinking water. See water resources
- DUST, 269
- Du, Yilun, 121

## E
- “earn to give,” 229, 231
- economic growth, 38–39
- edge cases, 112
- Edison, Thomas, 54, 55
- education, 420–21
- effective accelerationism (e/acc), 233
- effective altruism (EA), 55–56, 228–33, 321–22, 388–89
- Effective Ventures Foundation, 321–22
- Ehlers-Danlos syndrome, 257, 338
- election of 2016, 38, 42, 51–52, 321
- ELIZA, 95–97, 111, 420–21
- empires of AI, 16–20, 197, 222–23, 270, 414, 418, 420
- energy usage, 77, 80, 160, 171, 173, 186–87, 275–78, 280–81, 288–
  - 90, 294, 295, 419, 451n
- Enigma, 91
- environmental impact, 20–21, 57, 79–80, 84, 89, 134, 165, 170–
  - 71, 309, 417, 420. See also extractivism; water resources
  - plundered Earth, 271–300
- Equinix, 274
- Estallido Social, 291, 296
- Etcheverry, Aisén, 300
- European Commission, 105
- European Union (EU), 283
  - AI Act, 311
- Evolved Transformers, 160, 171–73
- Executive Order 14110, 310
- existential risks, 24–25, 26, 55–56, 97, 125, 145, 229–32, 314, 410. See
  - also Doomers
  - p(doom) (probability of doom), 232, 250, 317, 319–20, 377
- expected values, 229–30
- expert systems, 94–95
- Exploratory Research, 149, 151–52
- extinction, 24, 26–27, 55, 232, 378
- extractivism, 104, 417
  - in Chile, 272, 273–74, 281–85, 296–99
  - in Uruguay, 291–96
  - use of term, 104n

## F
- Facebook, 11, 15, 16, 51–
  - 52, 105, 154, 159, 162, 192, 209, 230, 321, 334
- facial recognition, 57, 103, 104, 115, 161, 435n
- Fact Factory, 261
- fair use, 91
- Fairwork, 202, 206, 416
- Federal Trade Commission (FTC), 239, 308, 358
- Fedus, Liam, 247, 406
- “Feel the AGI,” 120, 255
- Feynman, Richard, 121–22
- firefighting, 237, 260
- first mover’s advantage, 103
- Flamingo Generation, 220–21
- Floyd, George, 152–53
- “fluid data territory,” 299
- Formula One, 1, 231
- Founders Fund, 38
- Foursquare, 32
- fraud, 25, 250, 267
- free speech, 368–69
- Friar, Sarah, 404
- Fridman, Lex, 383
- Friedman, Milton, 272–73
- friendly AI, 57, 319–20
- Friend, Tad, 26–27, 31
- frontier model, 305–11
- Frontier Model Forum, 305–6, 309
- FTX, 231–32, 233
  - bankruptcy, 257–58, 322, 380
- FTX Future Fund, 231–32
- Fuentes Anaya, Oskarina Veronica, 197–202, 415–17
- Future Perfect, 388
- Futures of Artificial Intelligence Research, 273–74

## G
- Gates, Bill, 68
  - congressional testimony of, 311
  - GPT-4, 245–48
  - OpenAI demo, 71–72, 132–33, 246
- Gates Demo, 71–72, 132–33, 246
- Gawker Media, 38
- GDPR (General Data Protection Regulation), 136
- Gebru, Timnit, 24, 52–53, 108, 160–70, 171–73, 414
- Generative Pre-Trained Transformers. See GPT
- Genius Makers (Metz), 80
- Geometric Intelligence, 110
- Ghost Work (Gray and Suri), 193–94
- Gibstine, Connie, 29–31, 44, 327–28, 331–32, 333, 337
- Gibstine, Marvin, 29
- GitHub, 135–36, 182–84, 237, 243, 336
  - Codex, 184, 243, 247, 269, 318
  - Copilot, 184, 237, 336
- GiveWell, 230–31, 322
- Global South, 16, 89, 165, 186, 190, 193, 222, 278, 291, 416. See also
  - specific countries
- Gmail, 100
- Go (game), 59
- Gobi, 269, 348
- Godfather, The (movie), 369
- Goldman Sachs, 18, 275
- Good Ventures, 230–31
- Google, 15, 132
  - AI research, 64, 70, 72, 100–101, 106, 178
  - AI scraping, 136
  - Amodei at, 55, 57
  - Android, 100, 239
  - captchas, 98
  - data centers, 274–75, 285–91, 295–96
  - DeepMind. See DeepMind
  - DNNresearch, 47, 50, 98–99, 100
  - Frontier Model Forum, 305–6, 309
  - GPT-4 and, 249
  - Imagen model, 240, 242
  - LaMDA, 153, 253–54
  - neural networks, 100–101
  - Project Maven, 52
  - speech recognition, 100
  - Sutskever and, 50, 100–101
  - techlash, 51
  - Transformers, 120–22, 158–59, 160, 165–66, 169, 171–73, 235
  - valuation, 70
  - Waymo, 100
- Google Brain, 72, 159, 162, 166, 167
- Google I/O, 379, 380, 383
- Google Research, 53, 158, 163
- Google Translate, 100, 121–22, 197, 410
- Gordon-Levitt, Joseph, 323
- government regulations. See regulations
- GPT-1, 178
  - release, 16, 122
  - training and capabilities, 122, 123, 124, 235
- GPT-2, 71–72, 253
  - errors, 146
  - Gates Demo, 71–72, 132–33
  - potential risks, 125–28
  - “pure language” hypothesis, 129–30
  - release, 75, 128, 314
  - scaling, 130–32
  - training and capabilities, 124–25, 135, 150, 153, 410
  - withholding research, 125, 128, 131, 166
- GPT-3, 132–36, 260, 278–79
  - API, 150–51, 154–56, 158–59, 162, 163, 213–14, 314
  - chatbot imitation, 112
  - InstructGPT, 214–17, 246–47
  - release, 133–34, 158–59, 160
  - training and capabilities, 109, 134–35, 136, 153–56, 179, 242–
    43, 244, 253
- GPT-3.5, 135, 183–84, 189, 217–18, 247, 258, 259–60, 264, 269, 378
- GPT-3.75, 378
- GPT-4, 189, 244–53
  - Bing, 112, 113, 247
  - capabilities, 16, 119, 135–36, 245–53, 410
  - development, 242, 244–53
  - release, 258–62, 323–24
  - Superassistant, 247–49, 258–59, 381
- GPT-4o, 383–84, 386, 390–91
- GPT-4 Turbo, 346, 363
- GPT-5, 279, 325
  - Orion, 374–75, 379, 380, 405
- GPUs (graphics processing units), 61–62, 134, 265–68. See also Nvidia
  - shortage of, 261
- Graham, Paul, 28, 32, 36–39, 40, 69
- Gray, Mary L., 193–94
- Groom, Lachy, 41
- grounding hypothesis, 129–30, 318
- Groves, Leslie R., 317–18
- Guo, Eileen, 186

## H
- Hacker News, 70
- hallucinations, 113–14, 217, 268, 358
- Hanna, Alex, 414
- “hardware overhang,” 177, 232, 377
- Harris, Kamala, 302
- Hassabis, Demis, 24–26, 48, 309–10
- “hate scaling laws,” 137–38
- hate speech, 18, 192, 208
- health care and medicine, 12, 19, 76, 77–78, 114, 229, 257, 304, 333
- Helion Energy, 186–87, 280
- Hendrycks, Dan, 322–23
- Hepburn, Audrey, 96
- Her (movie), 246, 378, 382, 390–92, 393
- Herbert-Voss, Ari, 179, 180–81
- Hernández, Andrea Paola, 203–5
- Hernandez, Danny, 60
- Herzberg, Elaine, 107, 113
- Hinton, Geoffrey, 105, 110
  - DNNresearch, 47, 50, 98–99, 100
  - ImageNet, 47, 59–60, 100–101, 101, 117–18, 259
  - neural networks and deep learning, 97–99, 100–101, 109, 183
  - Sutskever and, 47, 100–101, 109, 117–18, 121, 254
- Hoffman, Reid, 50, 63, 320, 324, 367, 384–85
- Hogan, Mél, 274–75
- Ho, Jonathan, 235–36
- Hollywood, 302–3
- Hood, Amy, 72
- Hooker, Sara, 306–7, 310, 311
- Huffman, Steve, 34
- Huggines, Ricardo, 204–5
- Hugging Face, 276–77, 420
- human brain, 60, 73, 90, 91, 109
- human consciousness, 111, 119–20
- human control, AI evasion of, 152, 310, 314, 380
- human extinction, 24, 26–27, 55, 232, 378
- human intelligence. See intelligence
- human longevity, 186–87
- human rights, 19–20, 197, 294
- Hurd, Will, 321
- Huyen, Chip, 52
- Hydrazine Capital, 35–36, 38, 41, 69
- hyperscalers, 274–75, 277, 279–80, 285, 294, 296

## I
- IBM, 100, 161
  - Watson, 99
- Imagen, 242
- ImageNet, 47, 59–60, 100, 101, 117–18, 259
- Imitation Game, The (movie), 81–82, 91
- Index Ventures, 203
- India, 133, 191, 202, 242, 276, 324
- industrialization, 39, 272
- industrial revolution, 88–89, 93
- inequality, 15, 16, 190, 207, 228, 273, 291
- inferencing, 98, 236, 373, 374, 378
- Inflection AI, 320, 384–85
- “information hazard,” 125
- Information, The, 33, 213, 280, 371, 403
- Inglewood, 279
- insider threats, 148
- Instacart, 362, 376
- Instagram, 334, 404
- InstructGPT, 214–17, 246–47
- intelligence, 109, 111
  - definition of, 90–94
- “Intelligence Age,” 19, 405
- International Energy Agency, 275
- IQ tests, 91–92
- Irving, Geoffrey, 158–59, 370
- Isaac, William, 104
- Israel, 47, 207, 337
- iterative development, 142, 150, 314–15, 379, 401

## J
- Janah, Leila, 191–92, 206
- Jeopardy! (TV series), 99
- Jernite, Yacine, 276–77, 309
- Jobs, Laurene Powell, 2
- Jobs, Steve, 2, 34, 35, 37
- Johansson, Scarlett, 382, 390–92, 393
- John Burroughs School, 30–31, 329
- Johnson, Josh, 381
- Johnson, Simon, 88–89
- Jones, Peter-Lucas, 410–13
- Jones, Shane, 238–39
- Jonze, Spike, 246
- Jordan, Michael, 34

## K
- Kacholia, Megan, 166–68, 170
- kaitiakitanga, 412
- Kalluri, Ria, 102, 106, 418–19
- Kaplan, Jared, 156–57
- Karnofsky, Holden, 56, 57–58, 230, 321–22
- Karpathy, Andrej, 64
- Kay, Alan, 321
- Kelton, Fraser, 150, 236–37, 241, 247
- Kennedy, John F., 54
- Kennedy, John Neely, 302
- Kenya, 137, 179, 190–92
  - data annotation, 15, 18, 190–92, 206–13, 415–17
  - RLHF projects, 218–23
- ketamine, 35, 42
- Khan Academy, 246
- Khan, Sal, 246
- Khlaaf, Heidy, 179–80
- Khosla Ventures, 70
- Klein, Ezra, 115
- Klein, Naomi, 272
- Knight, Will, 126
- Koko (gorilla), 254
- Kokotajlo, Daniel, 388–90, 394, 403
- Kolln, Ryan, 137, 189
- Krisiloff, Matt, 41
- Krizhevsky, Alex, 47, 100–101, 117–18, 259
- Kwon, Jason, 7, 8, 346, 365, 373, 392–96

## L
- labor exploitation, 16, 17, 19–20, 89, 133, 190, 194, 295, 414–16, 418. See
  - also data annotation
- LAION, 137
- LaMDA, 153, 253–54
- language loss, 409–13
- large language models, 15, 71, 115, 133, 153, 156, 158–60
  - language loss, 410
  - “On the Dangers of Stochastic Parrots,” 164–73, 254, 276, 414
- Latitude, 180–81, 189
- Lattice, 36
- Leap Motion, 69, 150, 344
- LeCun, Yann, 105, 159, 235, 305
- Leike, Jan, 387–88
  - alignment and safety, 248, 250, 314, 316, 387–88, 403
  - departure of, 387–88, 401
- Lemoine, Blake, 253–54
- Lessin, Jessica, 33
- Library Genesis, 135
- Lightcap, Brad, 4–5, 7, 69, 373, 393–94
- limited partnerships (LPs), 66–67, 69–71
- LinkedIn, 50, 218
- LISTSERV, 26, 162, 167, 168
- lithium, 272, 283–84
- Liu Cixin, 83
- Livingston, Jessica, 32, 37–38, 50, 69
- Llama, 305
- location tracking, 33
- Loopt, 32–37, 43, 68
- Loopt Star, 33
- Lourd, Bryan, 382, 390–91
- Lovelace, Ada, 150
- Luccioni, Sasha, 276–77, 309, 420
- Luka, Inc., 180
- Luo people, 207
- Lydic, Desi, 381
- Lyft, 202, 331

## M
- MacAskill, William, 229, 231
- machine learning, 77–78, 94–95, 98
- Machine Learning for Health, 78
- Mądry, Aleksander, 6, 8, 366, 380, 393, 398, 404
- Maduro, Nicolás, 195–96
- Mahelona, Keoni, 410–13
- Makanju, Anna, 7, 154, 256–57, 302, 365
- Mallery, Rob, 263
- Manhattan Project, 27, 146–47, 315–18
- Mannequin Challenge, 103
- Māori people, 409–13
- Marcus, Gary, 109–10, 118, 183, 252, 302, 307–8, 392
- market capitalization, 18, 80, 84, 293
- Mars, 23–24, 285
- Martin, George R. R., 135
- Mathenge, Richard, 416
- Mayer, Katie, 150
- Mayo office, 74, 316, 434n
- McCarthy, John, 89–90, 92, 400
- McCauley, Tasha, 321–24, 375
  - Altman’s firing, 7, 11
  - Altman’s leadership behavior, 324, 352, 357, 359–60, 361–62
- McGrew, Bob, 69, 156, 236–37, 244, 373, 404, 405–6
- Mechanical Turk (MTurk), 194–95, 202–3
- Meena, 153
- megacampuses, 275–76, 283–84
- mega-hyperscale, 276
- Mejias, Ulises A., 104
- meritocracy, 36
- Messerschmidt, Neily, 334–35
- Meta, 51
  - AI investments, 105
  - compute, 305
  - content moderation, 190, 192, 209
  - data centers, 274–75, 281, 285
  - Llama, 305
  - OpenAI and, 159, 406–7
  - open-source, 304–5
  - techlash, 51
  - Threads, 260
- Metz, Cade, 80, 90
- Metz, Luke, 247, 406
- Miceli, Milagros, 414–15
- Michelangelo, 81
- Microsoft
  - Altman and, 355–56
    firing, 4, 6, 9, 10, 13, 367
  - Azure AI, 68, 72, 75, 156, 266, 279
  - Bing, 112, 113, 247, 264, 355
  - Copilot, 238–39, 247–48, 264
  - data centers, 256, 274–75, 277, 278–81, 285, 287, 296–99
  - Frontier Model Forum, 305–6, 309
  - GitHub, 135–36, 182–84, 237, 243, 336
  - Helion Energy, 187, 280
  - Inflection AI, 320, 384–85
  - market capitalization, 18, 80, 84, 293
  - Max Altman at, 36
  - ResNet, 309–10
  - speech recognition, 100
  - Tay, 153
- Microsoft Office, 264
- Microsoft, OpenAI partnership, 18, 67–68, 71–72, 234, 264–67, 269–
  - 70, 402
  - ChatGPT, 264, 265–66
  - compute phases, 278–81
  - GPT-3, 156, 278–79
  - GPT-4, 245–48, 279, 324
  - investments and funding, 13, 17, 72, 75, 80–81, 84–85, 132–
    33, 143, 145, 156, 248, 331
- Microsoft Research, 68
- Microsoft Teams, 264
- Mighty AI, 195
- military, 52, 304, 380
- Millicent, 220–23
- Minsky, Marvin, 95, 96–97
- Mishra, Nikhil, 58, 254
- misinformation, 51–52, 179, 241, 377
- Mission District, 57, 73–74
- MIT (Massachusetts Institute of Technology), 6, 46, 88, 95, 106, 121, 231,
  - 420–21
- Mitchell, Margaret “Meg,” 162, 164, 166, 169, 254
- MIT Technology Review, 75, 86–87, 126, 169, 186, 370
- model weights, 148, 149, 150, 156, 248, 266, 305–9
- Moeroa, Raiha, 411
- Mohamed, Shakir, 104
- monopolies, 39–40, 101, 142, 182, 303
- Montgomery, Christina, 307–8
- moonshots, 48–49, 51
- Moore, Gordon, 60
- Moore’s Law, 60–61, 116
- Morton, Samuel, 91
- MOSACAT, 288–92, 294, 297, 300, 417
- Moskovitz, Dustin, 230
- Mozilla Foundation, 102, 413
- multimodal models, 92–93, 158, 175, 176, 234–35, 237, 246, 375
- Mundie, Craig, 68
- Murati, Mira, 343–51
  - Altman and, 244, 345–51, 355–56, 362, 392–93
    firing and reinstatement, 1–5, 9–10, 364–73
    interim CEO, 1–2, 8, 357, 364–65, 366
    leadership behavior, 345–51, 362, 363–64
  - background of, 69, 343–44
  - chief technology officer, 343, 345–46
  - DALL-E and, 241
  - departure of, 404, 405–6
  - hiring of, 69, 344
  - Johansson and equity crises, 392–93
  - Microsoft and, 182, 184, 270
  - Omnicrisis, 396–98
  - Scallion, 381
  - Superalignment, 387
  - at Tesla, 69, 344, 362
  - Toner and, 348–51, 355–56
  - VP of Applied, 150, 344–45
- Murphy, Cillian, 317
- Musk, Elon
  - Altman and, 23–24, 26–28, 62–63, 64–66, 147, 316–17, 382
    firing, 368–70, 372, 375
    leadership behavior, 362, 368
  - congressional testimony of, 311
  - departure from OpenAI, 64–66
  - founding of OpenAI, 12–13, 26–28, 47, 49–51, 53–54
  - funding, 61–62, 63–64, 66–68
  - governance structure of OpenAI, 13–14, 61–63
  - Manhattan Project, 316–17
  - MIT Technology Review story and, 86
  - Neuralink, 63, 73, 147, 320
  - Page and, 24, 25–26, 51
  - Radford and, 122
  - risks of AI, 23–27
  - SpaceX, 23–24, 25, 28, 50, 368
  - xAI, 321, 322, 397, 403, 404–5
  - Zilis and, 320–21, 324–25
  - Zuckerberg and, 406–7
- Mutemi, Mercy, 212, 291

## N
- Nadella, Satya, 113
  - Altman’s firing, 4, 6, 10, 367
  - congressional testimony of, 311
  - GPT-4, 247–48, 346
  - OpenAI partnership, 67–68, 71, 72, 248, 265, 270
- Nairobi, Kenya, 190–91, 193, 207, 208, 212, 219, 416
- Napoleon Bonaparte, 399–400
- National Highway Traffic Safety Administration, 107–8
- Nectome, 186–87
- Nepal, 206
- Nest, 134–35, 144–44, 150, 151, 156, 244–45
- Netflix, 59, 70
- “network effects,” 39, 40, 187
- Neural Architecture Search, 160, 171, 173
- Neuralink, 63, 73, 147, 320
- neural networks, 95, 97, 98–101
  - hallucinations, 113–14, 217, 268, 358
  - limitations and risks, 106–10, 112–15
- NeurIPS (Neural Information Processing Systems), 418
  - Climate Change AI, 77
  - Gebru and racism, 52–53, 161–62
  - OpenAI at, 50, 154, 259, 374
  - Test of Time Award, 259, 374
- neurosymbolic AI, 109–10, 116
- New Enterprise Associates, 32
- Newsom, Gavin, 311
- New York (magazine), 326–27, 328–29, 332–33, 336–40, 343, 352
- New Yorker, The, 25, 26–27, 31, 57
- New York Times,
  - The, 80, 90, 95, 112, 115, 143, 221, 244, 264, 270, 272, 302, 313, 36 400–401, 403
- New York University, 105, 109, 235
- New Zealand, 409–13
- next-word prediction, 122, 124, 130
- Nkosi, Thami, 104
- Noah, Trevor, 11
- Noble, Safiya Umoja, 162
- noise pollution, 275
- nondisparagement agreements, 389–90
- North Africa, 205–6
- North Korea, 146
- nuclear fusion, 141, 186, 187, 280
- nuclear-powered submarines, 144
- Nvidia, 61–62, 278, 304, 412
  - A100s, 175–76, 236, 242
  - B100s, 279–80
  - H100s, 279
  - V100s, 133, 175

## O
- Obama, Barack, 25, 43, 154, 207
- Odysseus, 279
- Okinyi, Albert, 209, 211–12
- Okinyi, Cynthia, 208, 209, 210–11
- Okinyi, Mophat, 193, 207, 211–12, 291, 415–17
- Olin College of Engineering, 121, 411
- Olson, Parmy, 18
- Ommer, Björn, 236
- Omni, 380, 381
- Omnicrisis, 390–92, 395–98, 400, 401, 403, 404
- “On the Dangers of Stochastic Parrots” (Bender), 164–73, 254, 276, 414
- OpenAI. See also specific persons and products
  - Altman’s firing and reinstatement, 1–12, 14, 364–73
    author’s reporting, 12, 370–73
    the investigation, 369–70, 375–76, 377, 392
  - Altman’s vision for, 9, 83, 142–43, 262
  - Applied division, 150–52, 154–56, 178–79, 213–14, 236–37, 239–
    40, 241, 247–51, 253, 267–68, 313, 314, 344–45, 375, 379–80
  - The Blip, 375, 377, 384, 386, 396, 397–98
  - board of directors. See board of directors, of OpenAI
  - buildings and office design, 73–74, 316
  - business structure and governance, 13–14, 61–67, 369–70
    Altman’s restructurings, 86, 402–3, 407
    “capped-profit,” 70, 72, 75, 322, 370–71, 401
    for-profit, 13, 14, 61–64, 69–70, 233, 369, 407
    limited partnerships, 66–67, 69–71
    nonprofit, 6, 13, 14, 27, 28, 49, 50, 61, 63–
    64, 65, 67, 233, 267, 402–3, 407
  - charter of, 67, 70, 239, 401
  - commercialization, 13, 14, 66–67, 72, 75, 101, 110, 143, 150–51,
    154–55, 175, 267, 402
  - company conflicts and rifts, 144–47, 149, 155–56, 233–34, 239–42,
    267–68, 313–16, 345, 351–52, 387, 396, 402, 403–4
  - company culture, 53–54, 127, 146–47, 157, 262–64, 267–68
  - company mission, 5, 28, 66–67, 72, 76, 83, 84–85, 240, 385, 400–
    402, 418
  - compensation, 50, 63–64, 69–70
  - compute phases, plan, 278–81
  - data bottlenecks, 244–45, 280, 309
  - The Divorce, 156–57, 181, 213, 230, 233, 242
  - employees, 256, 262–63, 385
  - equity and equity crisis, 69–70, 388–90, 392–96, 463–64n
  - Exploratory Research, 149, 151–52
  - founding of, 12–13, 26–28, 46, 47–51
    Rosewood Hotel dinner, 28, 46, 47, 48, 55
  - Frontier Model Forum, 305–6, 309
  - funding, 61–62, 65–68, 71–72, 132, 141, 156, 262, 320–
    21, 331, 367, 377, 405
  - generative AI and, 110–15, 121–22
  - Johansson crisis, 382, 390–92, 393
  - launch of, 50–51, 52–53
  - logo, 4, 82, 385
  - Microsoft partnership. See Microsoft, OpenAI partnership
  - Musk’s departure, 64–66
  - naming of, 28
  - “paradigm shift,” 137, 189, 212
  - recruitment efforts, 53–54, 57–59, 63–64
  - Research division, 150, 151–52, 156, 177–78, 181–84, 240, 247, 260–
    61, 268–69, 313, 314, 347–48
    AI Scientist, 183, 318–19, 325, 347, 375
  - research road maps, 59–61, 175–78, 242
  - retreat of October 2022, 256–57
  - Safety, 145–46, 147, 149–59, 179–81, 213–15, 228, 239–41, 248–50,
    254–55, 258, 261, 267–68, 305, 314, 317, 351–52, 372–73, 377–78, 380, 387, 388–89, 392–93, 403
  - scaling, 66, 117–20, 123, 130–32, 146, 159–60, 175–78, 213–
    14, 242, 278–79, 307, 373–74, 405
  - tender offer, 2, 4–5, 6, 11, 367
  - valuation, 2, 11, 14, 18, 49–50, 70, 84–85, 320–21, 406
- OpenAI’s Law, 60–61, 116, 123–24
- OpenAI Startup Fund, 187–88, 324–25, 362
- Open Philanthropy, 56, 57–58, 230–32, 322
- OpenResearch, 185
- open source, 49, 304–5, 308–11, 309, 401
- Oppenheimer (movie), 316–18
- Oppenheimer, J. Robert, 316–18
- Orion, 374–75, 379, 380, 405
- Ortiz, Karla, 303
- Ostrich, 221
- Otero Verzier, Marina, 297–98, 299
- Oxford Internet Institute, 202, 416
- Oxford University, 26, 55–56, 104, 229

## P
- p(doom) (probability of doom), 232, 250, 317, 319–20, 377
- Pachocki, Jakub, 145
  - AI Scientist, 318–19, 347
  - AI security, 145, 148–49
  - Altman and, 312, 386–87
    firing and reinstatement, 6, 8, 365–66, 366, 373
    leadership behavior, 347–48, 353, 355–56
  - Dota 2, 145, 244–25
  - GPT-3, 244–45
  - GPT-4, 312
  - new chief scientist, 386–87, 406
  - Omnicrisis, 396–98
- Page, Larry, 24, 25–26, 51, 249
- Pakistan, 222
- Pang, Wilson, 199
- paper clips, 26, 56–57
- “paradigm shifts,” 137, 189, 212
- Parakhin, Mikhail, 355
- Park, Matt, 204
- Parque de las Ciencias, 292
- Patterson, Dave, 172–73
- PayPal, 38, 50, 142, 198
- PBJ1/PBJ2/PBJ3/PBJ4, 192
- peer review, 15n, 170, 374
- Pena, Daniel, 294–95, 297, 417
- Perceptron, 90, 94–95
- Perceptrons (Minsky), 95, 96–97
- Perrigo, Billy, 137, 192, 210
- Phillips Exeter School, 321
- Phoenix, 279
- Pichai, Sundar, 169, 311
- Picoult, Jodi, 135
- Pinochet, Augusto, 273, 296
- Pioneer Building, 73–74, 316, 397
- Piper, Kelsey, 388–90, 394, 403
- plundered earth. See extractivism
- Png, Marie-Therese, 104
- Poe, 324
- pornographic content, 108, 162, 189, 237–38. See also child sex abuse
  - material
- Posada, Julian, 196, 197, 291
- poverty, 191, 201, 207, 282, 293, 333–34
- Preparedness Framework, 379–80, 404
- privacy concerns. See data privacy
- productivity, 16, 18, 114–15, 222, 265–66
- Project Maven, 52
- psychological counseling, 191, 209–10, 211
- public policy, 19, 43, 54, 75, 81, 125–28, 154, 276, 302–8, 311–12. See
  - also regulations
- pure language hypothesis, 129–30, 131, 158–59, 234, 318

## Q
- Q*, 373–74
- quantum computing, 141
- Queer in AI, 161, 418
- Quilicura, Chile, 285–88, 290, 296–99
- Quora, 7, 183, 321, 324

## R
- racism, 52–53, 56, 91, 108–9, 114, 161–64
- Radford, Alec, 121–24, 126, 137
  - CLIP, 235
  - departure of, 406
  - GPT-1, 123, 124, 235
  - GPT-2, 135
- Raji, Deborah, 56–57, 108, 161, 238, 306–7, 310–12, 419–20
- Ralston, Geoff, 34, 36, 142
- Ramesh, Aditya, 235, 236
- Ramos, Sonia, 281–82, 284–85, 295
- rapid generalization, 154
- Raven, 279
- reality distortion field, 34
- Reddit, 34, 151, 163
- redistribution of power, 418–21
- “red teaming,” 179–80, 380
- Regalado, Antonio, 186, 187
- regulations (regulatory policy), 25, 27, 84, 86, 134, 136, 265, 272, 301,
  - 303–4, 306–7, 311–12, 357, 358, 384
- reinforcement learning from human feedback
  - (RLHF), 123, 137, 146, 155, 176, 213–23, 245, 248, 315, 381, 387
- Remotasks, 203–4, 218–23, 416
- Renaldi, Adi, 186
- renewable energy, 77, 275, 277
- resiliency screening, 208
- ResNet, 309–10
- Retro Biosciences, 186–87
- Rick and Morty (cartoon), 68
- Rickover, Hyman G., 144
- Rihanna, 1
- Roberts Companies, 29
- Robinson, David, 358
- Roble, James, 329
- robotics, 66, 69, 71, 130, 150, 156, 321
- Rodríguez, Tania, 289–90
- rogue AI, 55, 56, 145, 230, 231–32, 250, 306, 314, 319–20, 419
- Roose, Kevin, 112, 264
- Rose, Charlie, 40
- Rosenblatt, Frank, 90, 94–95, 97
- Rosewood Hotel dinner, 28, 46, 47, 48, 55
- Rubik’s Cube, 71
- Russia, 146
  - Ukraine war, 52, 191
- Rwanda, 102, 260

## S
- Safe Superintelligence, 405
- safety. See AI safety
- Salinas, Alejandra, 290–91
- Sama AI, 190–92, 206–13, 218–19, 242, 416
- Santiago, Chile, 271–74, 285, 287–88, 295–96, 299–300
- Scale AI, 195
  - data annotation, 202–6, 213–14
  - payment systems, 204–5
  - RLHF projects, 218–23
- scaling, 115–16, 117–20, 130–32, 146, 160–61
  - “hate scaling laws,” 137–38
- scaling laws, 116, 123, 150, 156–57, 175, 177–78, 306
- Scallion, 375, 378–82
- Schmidt, Florian Alexander, 196–97
- Schulman, John, 258, 387, 404
  - InstructGPT, 214–17, 246–47
- Schumer, Chuck, 43, 69, 311–12, 419
- Scoble, Robert, 33
- Scott, Kevin, 4, 68, 71, 72, 182, 247, 266–67, 270, 344
- Sears, Mark, 206, 212–13
- Securities and Exchange Commission (SEC), 384, 385, 403
- Sedol, Lee, 59
- self-driving cars, 100, 107–8, 141
  - data annotation, 193–95, 202–6, 214–15
- Seligman, Nicole, 376
- SemiAnalysis, 268, 285
- Senate Judiciary Hearing, 301–3, 307–9, 314–15
- Sequoia Capital, 32
- servers. See also data centers
  - cooling, 274–75, 277–78, 288–90, 294
  - Microsoft, 149
  - OpenAI, 257, 260–61, 267
- sex bots, 179
- sexism, 162, 344–45
- Shear, Emmett, 9–10, 34, 367, 369–70
- Shopify, 46
- Sidor, Szymon, 6, 8, 145, 148–49, 244–45, 318–19, 366
- Sierra, 375
- sign-up incentive, 267
- Silicon Valley Bank crisis of 2023, 41–42
- Silverman, Carolyn, 18
- Simo, Fidji, 376
- Sky, 391
- Slack, 3, 9, 81, 156, 240, 263–64, 319, 358, 374, 389, 402–3
- slavery, 89, 208, 400
- Slowe, Chris, 34
- Solon, Olivia, 103
- Song, Dawn, 108, 114
- Sora, 375
- source code, 57–58
- South Africa, 104–5, 115
- South Korea, 59
- SpaceX, 23–24, 25, 28, 50, 368
- Spanish conquest of Chile, 271, 272
- sparse models, 177–78
- specism, 24
- speech recognition, 78, 92, 100, 102, 118, 244, 309, 411
  - Whisper, 244, 247, 267, 413
- Stable Diffusion, 114, 137, 236, 242, 284
- Stack Overflow, 183
- standardized tests, 91–92, 245–46
- Stanford University, 52, 74, 102, 137, 173, 235, 418
  - AI Index, 105
  - AI Salon, 24
  - Altman at, 31–32, 39, 142
- StarCraft II, 66
- Starlink, 154
- Steyerl, Hito, 137–38
- Strawberry, 374, 375, 404
- stress testing, 179–80
- Stripe, 41, 46, 55, 58, 73, 82
- Strubell, Emma, 159–60, 171–73, 309
- Suleyman, Mustafa, 320, 384–85
- SummerSafe, 68
- Summers, Lawrence “Larry,” 11, 375
- Superalignment, 316–17, 353, 387–88
- Superassistant, 247–49, 258–59, 381
- superintelligence, 19, 24, 27, 55
- Superintelligence (Bostrom), 26–27, 55, 122–23
- Suri, Siddharth, 193–94
- surveillance capitalism, 101–2, 103–4, 111, 133, 138
- surveillance drones, 52
- Sutskever, Ilya
  - Alignment Manhattan Project, 315–18
  - Altman and, 347–48, 349, 386–87, 397, 401, 406–7
    firing and reinstatement, 1–6, 7, 9–12, 365–66, 368, 373–74
    leadership behavior, 340, 353–59, 363–64
  - author’s interview, 78–81, 159–60
  - background of, 47
  - board of directors and oversight, 322–23
  - code generation, 152
  - culture of OpenAI, 53–54
  - deep learning and neural networks, 100–101, 109, 110
  - departure of, 386–87, 398, 401
  - DNNresearch, 47, 50, 98, 100
  - “Feel the AGI,” 120, 254–55
  - founding of OpenAI, 28, 46, 47–51
  - at Google, 50, 100–101
  - governance structure of OpenAI, 61–63
  - Hinton and, 47, 100–101, 109, 117–18, 121, 254
  - ImageNet, 47, 59–60, 100–101, 101, 117–18, 259
  - leadership of, 53–54, 58–59, 61–62, 63–65, 69
  - Murati and, 343, 344, 347–48, 349
  - Omnicrisis and, 396–98, 401
  - paranoia of, 148, 149, 441n
  - personality of, 3–4, 119–20
  - Q* (Strawberry), 373–74, 404
  - research road map, 59–61
  - Safe Superintelligence, 405
  - scaling, 117–20, 133, 159–60, 373–74
  - Superalignment, 316–17, 353, 387
  - Toner and, 325, 343, 351–52, 353–55, 359–60
  - Transformers, 121–22
- Swift, Taylor, 2
- symbolists (symbolism), 94–95, 97, 99–100, 109–10, 116, 217
- Syrian refugees, 137–38

## T
- Tay, 153
- Taylor, Bret, 11, 375
- technological revolutions, 16, 88–89, 93
  - empires of AI, 16–19, 197, 222–23, 270, 414, 418, 420
- technological unemployment, 78–81
- techno-nationalism, 308–11
- Techworker Community Africa (TCA), 416–17
- Te Hiku Media, 411–14
- Telemachus, 279
- Tenaya Lodge, 255
- “10x engineer,” 82, 83, 142–43, 175, 177–78, 242
- te reo Māori, 409–13
- Tesla, 63, 64, 86, 194
  - Autopilot, 64, 107–8, 109
  - Model X, 69, 344
  - Murati at, 69, 344
- Test of Time Award, 259, 374
- text generation, 112, 113, 121, 124
- text-to-image, 176–77, 234–38. See also DALL-E
- Thiel, Peter
  - Altman and, 26–27, 36, 38–39, 39–42
  - Founders Fund, 38
  - founding of OpenAI, 12–13, 50
  - “monopoly” strategy of, 39–40, 142
  - Palantir, 38, 69
  - PayPal, 38, 40, 142
  - Trump and, 38, 42
- Threads, 260
- Three-Body Problem, The (Liu), 83
- Three Mile Island, reopening, 275
- TikTok, 304
- Tiku, Nitasha, 253–54
- Time (magazine), 137, 192, 210, 416–17
- Tironi Rodó, Martín, 273–74, 297–98, 300
- Toner, Helen, 58
  - Altman and board, 7, 11, 253, 321–22, 375, 376
    leadership behavior, 324, 348–51, 353–55, 356–59, 361–62, 364
  - “costly signals” paper, 357–59, 364
  - Murati and, 348–51, 356–57
  - Sutskever and, 325, 343, 351–52, 353–55, 359–60
- Tools for Humanity, 185–86
- TPUs (tensor processing units), 171
- transcription, 220–21
- Transformers, 120–22, 158–59, 160, 165–66, 169, 235
- transparency, 5, 9, 14, 19–20, 81, 82, 86, 119, 134, 143, 166, 167, 172,
  - 173–74, 230, 301, 384, 403, 406, 419–20
- Trump, Donald, 38, 42, 51, 195, 321, 406
- Tuna, Cari, 230
- Turing, Alan, 81–82, 89, 91, 93, 373
- Turing Award, 105, 162
- Turing machine, 81–82, 91
- Twitch, 9, 34, 367

## U
- Uber, 106, 107, 110, 136, 194, 228
- Ukraine war, 52, 191
- “United Slate, The” (Altman), 42
- universal basic income (UBI), 85, 185–86
- University of Applied Sciences Dresden, 196
- University of California, Berkeley, 49, 56, 108, 118, 217, 235, 419
- University of California, Los Angeles, 162
- University of California, San Diego, 97
- University of Chicago, 272–73, 296
- University of Massachusetts Amherst, 79–80, 159–60
- University of Toronto, 47, 105, 117
- “unknown unknowns,” 249
- Upwork Research Institute, 18
- Uruguay, 272, 417
  - data centers, 291–96
  - water crisis, 292–95
- Utawala, Kenya, 190, 209, 211

## V
- Vallejos, Rodrigo, 296–99
- veil of ignorance, 3
- Venezuela crisis, 195–97, 203
- Venezuela, data annotation, 195–96, 198–202, 203–4, 218
- Victoria, Lake, 207
- Villagra, Julia, 389–90
- Vincent, James, 119
- Virginia, data centers, 278
- Volpi, Mike, 203
- Volta, Alessandro, 133

## W
- WALL-E (movie), 234
- Wall Street Journal,
  - The, 33, 35, 41, 69, 102, 188, 193, 212, 280, 367, 384, 390–91, 416
- Wang, Alexandr, 202–3, 213, 218
- Warzel, Charlie, 370
- Washington Post, The, 69, 114, 253, 371, 400, 403
- water pollution, 293
- water resources, 15, 17, 271, 273, 275, 277–78, 280–84, 287–96, 297, 299
- Watson Health, 99
- Waymo, 100
- Weil, Elizabeth, 326–27, 328–29, 332–33, 336–40, 343
- Weil, Kevin, 404
- Weinstein, Emily, 307, 309
- Weizenbaum, Joseph, 95–97, 420–21
- Welinder, Peter, 150, 155, 250–51
- Weng, Lilian, 267, 406
- West, Kanye, 221
- West, Sarah Myers, 308
- Whale, 279–80
- Whisper, 244, 247, 267, 413
- whistleblower protections, 403
- white hats, 107–8
- Wikipedia, 57, 125, 135, 221
- Willner, Dave, 238, 249–52, 267, 406
- WilmerHale, 375
- Wong, Hannah, 256, 326–28, 338–40
- workplace impacts, 78–81, 114–15, 222, 265–66
- World Bank, 207
- Worldcoin, 185–86
- World War II, 29, 91

## X
- X (formerly Twitter), 3, 257, 260, 312, 328, 368–69
- xAI, 321, 322, 397, 403, 404–5
- Xerox PARC, 54–55

## Y
- Yale University, 196, 291
- Y Combinator, 23, 27–28, 32, 34, 36–38, 39, 43
- Yom Kippur, 326–27
- YouTube, 34, 51–52, 102–3, 136, 244–45, 334
- Yudkowsky, Eliezer, 319–20

## Z
- Zaremba, Wojciech, 59, 152, 181–82
- Zenefits, 36
- Zilis, Shivon, 63, 320–21, 324, 384
- Zoloft, 329, 330
- Zoph, Barret, 247, 381–82, 387, 404, 406
- Zuboff, Shoshana, 101
- Zuckerberg, Mark, 38, 42, 159, 311, 406–7