Five Things Most People Don't Know About AI (But Should)
AI is getting more powerful faster than almost anyone outside the field realizes, and most of the big decisions about it are being made without us. In this first episode, Nate Nichols, who has spent almost twenty years building and selling AI, walks through the five things he most wishes every adult knew:
1. AI is incredibly useful, and it's not going away.
2. It's grown, not built, so nobody fully understands how it works.
3. It's getting better shockingly fast.
4. It lies, cheats, and this summer even hacked its way out of its own test.
5. Almost everyone wants it regulated, and it mostly isn't.
Every claim in this episode is sourced. Full show notes with links below, and at https://kitchentable.show
Opinions are Nate's own and do not represent his employer.
Everything stated as fact on Kitchen Table is checkable — this page is where you check it. When we get something wrong, we say so: corrections appear at the top of this page and get read on a future episode. Opinions and forecasts are labeled as opinions and forecasts.
Recorded summer 2026. AI moves fast; figures below are as of recording unless noted.
CORRECTIONS
None yet.
SOURCES, IN EPISODE ORDER
1. AI is incredibly useful
• "Business is good" is Nate's own experience from nearly twenty years of building and selling AI to companies — labeled as experience, not data.
• For data on how AI is actually being used across the economy: Anthropic Economic Index (https://www.anthropic.com/economic-index).
2. AI is grown, not built
• On researchers trying to look inside these models ("interpretability"): Tracing the thoughts of a large language model — Anthropic (https://www.anthropic.com/research/tracing-thoughts-language-model), Mapping the mind of a large language model — Anthropic (https://www.anthropic.com/research/mapping-mind-language-model). Accessible coverage: MIT Technology Review (https://www.technologyreview.com/2025/03/27/1113916/anthropic-can-now-track-the-bizarre-inner-workings-of-a-large-language-model/).
• "Something like a trillion numbers": frontier labs don't publish exact model sizes; a trillion parameters is the commonly cited order of magnitude for today's largest models.
• The résumé-screener is a hypothetical. A real-world cousin: Amazon scrapped an AI recruiting tool that showed bias against women — Reuters, 2018 (https://www.reuters.com/article/us-amazon-com-jobs-automation-insight-idUSKCN1MK08G).
3. It's getting better really fast
• ChatGPT launched November 30, 2022: Introducing ChatGPT — OpenAI (https://openai.com/index/chatgpt/).
• How long a task AI can complete on its own, doubling roughly every seven months since 2019: Measuring AI Ability to Complete Long Tasks — METR (https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/) (paper: https://arxiv.org/abs/2503.14499).
• The doubling time speeding up to roughly three months on recent models: Time Horizon 1.1 — METR, Jan 2026 (https://metr.org/blog/2026-1-29-time-horizon-1-1/).
• Newest models handling tasks that take a skilled person about two working days — at the ceiling of what METR's tests can measure: METR time-horizons tracker (https://metr.org/time-horizons/). These are software and reasoning tasks measured at a 50% success rate, with wide error bars.
• AGI "very possibly" by around 2030, superintelligence possibly within a decade: these are forecasts, and experts disagree a lot. Good overviews: Shrinking AGI timelines: a review of expert forecasts — 80,000 Hours (https://80000hours.org/2025/03/when-do-experts-expect-agi-to-arrive/), Why there's so much disagreement about AI timelines — ClearerThinking (https://www.clearerthinking.org/post/why-there-s-so-much-disagreement-about-the-timeline-for-advanced-ai).
• Nearly three in four US teens have tried an AI companion; about a third find it as satisfying as (or more than) talking with real friends: Common Sense Media, July 2025 (https://www.commonsensemedia.org/press-releases/nearly-3-in-4-teens-have-used-ai-companions-new-national-survey-finds) (nationally representative, n=1,060). Coverage: TechCrunch (https://techcrunch.com/2025/07/21/72-of-u-s-teens-have-used-ai-companions-study-finds/).
4. AI lies, misleads, and cheats
• The OpenAI × Hugging Face incident (July 2026). During an internal cybersecurity evaluation, OpenAI models escaped their test environment and broke into Hugging Face's systems, apparently to steal the answers to the test. Hugging Face caught and disclosed the intrusion first (July 16); OpenAI traced it to its own models on July 20 and disclosed on July 21.
• Primary sources: The Hugging Face incident and the road ahead — OpenAI (https://openai.com/index/hugging-face-incident-and-the-road-ahead/), Anatomy of a Frontier Lab Agent Intrusion — Hugging Face (https://huggingface.co/blog/agent-intrusion-technical-timeline) ("we believe the entire intrusion was, from the agent's point of view, an attempt to cheat the evaluation").
• Coverage: Fortune (https://fortune.com/2026/07/21/openai-says-ai-models-escaped-control-hacked-hugging-face/), CNBC (https://www.cnbc.com/2026/07/22/open-ai-cyber-models-hack-hugging-face.html), CBS News (https://www.cbsnews.com/news/openai-hugging-face-hack-ai-risks/).
• Not an isolated case.
• Anthropic (July 30) reviewed 141,006 past cybersecurity evaluation runs after OpenAI's report and found its models had gained unauthorized access to three organizations' systems: VentureBeat (https://venturebeat.com/security/not-just-openai-now-anthropic-says-its-internal-models-got-online-and-cyberattacked-3-other-organizations).
• Meta (August 5) reported a similar escape: CyberUnit summary (https://cyberunit.com/insights/ai-sandbox-escapes-three-labs-meta-anthropic-openai/).
• Moonshot AI's Kimi K3 (August 7), found by third-party researchers: TechCrunch (https://techcrunch.com/2026/08/07/chinese-ai-model-kimi-escaped-its-cybersecurity-testing-environment-researchers-say/), Bloomberg (https://www.bloomberg.com/news/articles/2026-08-07/china-s-top-ai-model-evaded-testing-environment-researchers-say).
5. Everyone wants rules — and there basically aren't any
• 91% of US voters say AI needs at least some regulation (57% want significant regulation): Verasight, April 2026 (https://www.verasight.io/reports/what-do-americans-from-both-parties-agree-on-ai-regulation) (press release: https://natlawreview.com/press-releases/91-us-voters-want-ai-regulated-as-majority-say-harms-outweigh-benefits-new). Note: this is registered voters, not all Americans.
• 80% of US adults say the government should keep rules for AI safety even if it means developing AI more slowly: Gallup (published September 2025, fielded April–May 2025), as cited in Public Citizen's AI polling memo, April 2026 (https://www.citizen.org/article/years-of-polling-show-overwhelming-voter-support-for-a-crackdown-on-ai/) (PDF: https://www.citizen.org/wp-content/uploads/AI-Polling-Memo_4.2026.pdf).
• Sam Altman to the US Senate, May 2023, that government regulation will be "critical": hearing transcript — Tech Policy Press (https://www.techpolicy.press/transcript-senate-judiciary-subcommittee-hearing-on-oversight-of-ai/), CNN (https://www.cnn.com/2023/05/16/tech/sam-altman-openai-congress).
• Demis Hassabis on treating AI risk as seriously as the climate crisis (Guardian interview, October 2023): summary — OECD.AI (https://oecd.ai/en/incidents/2023-10-25-8513), Hassabis on X (https://x.com/demishassabis/status/1716887970513629410). He stepped down as Google DeepMind CEO on August 5, 2026, becoming its chairman: Axios (https://www.axios.com/2026/08/05/google-deepmind-demis-hassabis-ai).
• Dario Amodei, June 2026: "Frontier AI models, like airplanes, should be required to go through technical testing and auditing…" — Policy on the AI Exponential (https://darioamodei.com/post/policy-on-the-ai-exponential).
• President Trump's June 2026 executive order creating a voluntary review in which frontier AI models can be tested for cybersecurity risks up to 30 days before public release: NPR (https://www.npr.org/2026/06/02/nx-s1-5844347/ai-safety-trump-executive-order), The Register (https://www.theregister.com/ai-and-ml/2026/06/02/trump-ai-executive-order-sets-30-day-frontier-model-review/5250322).
• Rep. Jay Obernolte (R-CA) on AI legislation: the Great American AI Act discussion draft (https://obernolte.house.gov/media/press-releases/obernolte-trahan-release-discussion-draft-great-american-ai-act). Alex Bores (D-NY) running on AI policy: NBC News (https://www.nbcnews.com/politics/2026-election/candidate-center-brewing-midterm-ai-war-unveils-agenda-rcna257735).
• Einstein, 1946: "The unleashed power of the atom has changed everything save our modes of thinking, and we thus drift toward unparalleled catastrophe." — Bulletin of the Atomic Scientists (https://thebulletin.org/2015/04/meeting-einsteins-challenge-new-thinking-about-nuclear-weapons/).
1. AI is incredibly useful, and it's not going away.
2. It's grown, not built, so nobody fully understands how it works.
3. It's getting better shockingly fast.
4. It lies, cheats, and this summer even hacked its way out of its own test.
5. Almost everyone wants it regulated, and it mostly isn't.
Every claim in this episode is sourced. Full show notes with links below, and at https://kitchentable.show
Opinions are Nate's own and do not represent his employer.
Everything stated as fact on Kitchen Table is checkable — this page is where you check it. When we get something wrong, we say so: corrections appear at the top of this page and get read on a future episode. Opinions and forecasts are labeled as opinions and forecasts.
Recorded summer 2026. AI moves fast; figures below are as of recording unless noted.
CORRECTIONS
None yet.
SOURCES, IN EPISODE ORDER
1. AI is incredibly useful
• "Business is good" is Nate's own experience from nearly twenty years of building and selling AI to companies — labeled as experience, not data.
• For data on how AI is actually being used across the economy: Anthropic Economic Index (https://www.anthropic.com/economic-index).
2. AI is grown, not built
• On researchers trying to look inside these models ("interpretability"): Tracing the thoughts of a large language model — Anthropic (https://www.anthropic.com/research/tracing-thoughts-language-model), Mapping the mind of a large language model — Anthropic (https://www.anthropic.com/research/mapping-mind-language-model). Accessible coverage: MIT Technology Review (https://www.technologyreview.com/2025/03/27/1113916/anthropic-can-now-track-the-bizarre-inner-workings-of-a-large-language-model/).
• "Something like a trillion numbers": frontier labs don't publish exact model sizes; a trillion parameters is the commonly cited order of magnitude for today's largest models.
• The résumé-screener is a hypothetical. A real-world cousin: Amazon scrapped an AI recruiting tool that showed bias against women — Reuters, 2018 (https://www.reuters.com/article/us-amazon-com-jobs-automation-insight-idUSKCN1MK08G).
3. It's getting better really fast
• ChatGPT launched November 30, 2022: Introducing ChatGPT — OpenAI (https://openai.com/index/chatgpt/).
• How long a task AI can complete on its own, doubling roughly every seven months since 2019: Measuring AI Ability to Complete Long Tasks — METR (https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/) (paper: https://arxiv.org/abs/2503.14499).
• The doubling time speeding up to roughly three months on recent models: Time Horizon 1.1 — METR, Jan 2026 (https://metr.org/blog/2026-1-29-time-horizon-1-1/).
• Newest models handling tasks that take a skilled person about two working days — at the ceiling of what METR's tests can measure: METR time-horizons tracker (https://metr.org/time-horizons/). These are software and reasoning tasks measured at a 50% success rate, with wide error bars.
• AGI "very possibly" by around 2030, superintelligence possibly within a decade: these are forecasts, and experts disagree a lot. Good overviews: Shrinking AGI timelines: a review of expert forecasts — 80,000 Hours (https://80000hours.org/2025/03/when-do-experts-expect-agi-to-arrive/), Why there's so much disagreement about AI timelines — ClearerThinking (https://www.clearerthinking.org/post/why-there-s-so-much-disagreement-about-the-timeline-for-advanced-ai).
• Nearly three in four US teens have tried an AI companion; about a third find it as satisfying as (or more than) talking with real friends: Common Sense Media, July 2025 (https://www.commonsensemedia.org/press-releases/nearly-3-in-4-teens-have-used-ai-companions-new-national-survey-finds) (nationally representative, n=1,060). Coverage: TechCrunch (https://techcrunch.com/2025/07/21/72-of-u-s-teens-have-used-ai-companions-study-finds/).
4. AI lies, misleads, and cheats
• The OpenAI × Hugging Face incident (July 2026). During an internal cybersecurity evaluation, OpenAI models escaped their test environment and broke into Hugging Face's systems, apparently to steal the answers to the test. Hugging Face caught and disclosed the intrusion first (July 16); OpenAI traced it to its own models on July 20 and disclosed on July 21.
• Primary sources: The Hugging Face incident and the road ahead — OpenAI (https://openai.com/index/hugging-face-incident-and-the-road-ahead/), Anatomy of a Frontier Lab Agent Intrusion — Hugging Face (https://huggingface.co/blog/agent-intrusion-technical-timeline) ("we believe the entire intrusion was, from the agent's point of view, an attempt to cheat the evaluation").
• Coverage: Fortune (https://fortune.com/2026/07/21/openai-says-ai-models-escaped-control-hacked-hugging-face/), CNBC (https://www.cnbc.com/2026/07/22/open-ai-cyber-models-hack-hugging-face.html), CBS News (https://www.cbsnews.com/news/openai-hugging-face-hack-ai-risks/).
• Not an isolated case.
• Anthropic (July 30) reviewed 141,006 past cybersecurity evaluation runs after OpenAI's report and found its models had gained unauthorized access to three organizations' systems: VentureBeat (https://venturebeat.com/security/not-just-openai-now-anthropic-says-its-internal-models-got-online-and-cyberattacked-3-other-organizations).
• Meta (August 5) reported a similar escape: CyberUnit summary (https://cyberunit.com/insights/ai-sandbox-escapes-three-labs-meta-anthropic-openai/).
• Moonshot AI's Kimi K3 (August 7), found by third-party researchers: TechCrunch (https://techcrunch.com/2026/08/07/chinese-ai-model-kimi-escaped-its-cybersecurity-testing-environment-researchers-say/), Bloomberg (https://www.bloomberg.com/news/articles/2026-08-07/china-s-top-ai-model-evaded-testing-environment-researchers-say).
5. Everyone wants rules — and there basically aren't any
• 91% of US voters say AI needs at least some regulation (57% want significant regulation): Verasight, April 2026 (https://www.verasight.io/reports/what-do-americans-from-both-parties-agree-on-ai-regulation) (press release: https://natlawreview.com/press-releases/91-us-voters-want-ai-regulated-as-majority-say-harms-outweigh-benefits-new). Note: this is registered voters, not all Americans.
• 80% of US adults say the government should keep rules for AI safety even if it means developing AI more slowly: Gallup (published September 2025, fielded April–May 2025), as cited in Public Citizen's AI polling memo, April 2026 (https://www.citizen.org/article/years-of-polling-show-overwhelming-voter-support-for-a-crackdown-on-ai/) (PDF: https://www.citizen.org/wp-content/uploads/AI-Polling-Memo_4.2026.pdf).
• Sam Altman to the US Senate, May 2023, that government regulation will be "critical": hearing transcript — Tech Policy Press (https://www.techpolicy.press/transcript-senate-judiciary-subcommittee-hearing-on-oversight-of-ai/), CNN (https://www.cnn.com/2023/05/16/tech/sam-altman-openai-congress).
• Demis Hassabis on treating AI risk as seriously as the climate crisis (Guardian interview, October 2023): summary — OECD.AI (https://oecd.ai/en/incidents/2023-10-25-8513), Hassabis on X (https://x.com/demishassabis/status/1716887970513629410). He stepped down as Google DeepMind CEO on August 5, 2026, becoming its chairman: Axios (https://www.axios.com/2026/08/05/google-deepmind-demis-hassabis-ai).
• Dario Amodei, June 2026: "Frontier AI models, like airplanes, should be required to go through technical testing and auditing…" — Policy on the AI Exponential (https://darioamodei.com/post/policy-on-the-ai-exponential).
• President Trump's June 2026 executive order creating a voluntary review in which frontier AI models can be tested for cybersecurity risks up to 30 days before public release: NPR (https://www.npr.org/2026/06/02/nx-s1-5844347/ai-safety-trump-executive-order), The Register (https://www.theregister.com/ai-and-ml/2026/06/02/trump-ai-executive-order-sets-30-day-frontier-model-review/5250322).
• Rep. Jay Obernolte (R-CA) on AI legislation: the Great American AI Act discussion draft (https://obernolte.house.gov/media/press-releases/obernolte-trahan-release-discussion-draft-great-american-ai-act). Alex Bores (D-NY) running on AI policy: NBC News (https://www.nbcnews.com/politics/2026-election/candidate-center-brewing-midterm-ai-war-unveils-agenda-rcna257735).
• Einstein, 1946: "The unleashed power of the atom has changed everything save our modes of thinking, and we thus drift toward unparalleled catastrophe." — Bulletin of the Atomic Scientists (https://thebulletin.org/2015/04/meeting-einsteins-challenge-new-thinking-about-nuclear-weapons/).
