Heard in AI is an AI publication with news, analysis and explanations. If you are new to AI or have no technical background, this page explains how the site works and suggests where to begin.
What you will read
Our articles start from conversations on AI podcasts, where researchers, founders and critics discuss what is changing in AI. We also draw on the research papers and articles those conversations cite. We explain what the speakers and authors say, where they disagree and what is still unknown.
Three formats
Briefings
A briefing reports one development at a point in time. We may correct or clarify it later; a new development gets a new briefing.
Ideas
An idea page explains a concept, theory or proposal: where it comes from, what supports it, the objections and the open questions. We update it when new material changes the explanation.
Stories
A story page follows one specific event across podcast discussions, with an overview and a timeline of what changed. It updates when new episodes discuss the event, and you can get those updates by email or push.
How to read a page
Who says it. We name the person or organisation behind each claim. A claim is their account, not proof that it is true.
Sources. Each page links to the podcast episodes and the material it draws on, so you can check the original.
Dates. A briefing shows when we first published it. If we correct or clarify it later, the page shows the new date and the reason, and earlier versions stay available. On a story page, timeline dates show when each podcast discussion was published.
AI. We use AI to write and edit articles, and articles can publish without human review. AI can get names, numbers and technical details wrong, which is why we link to the original sources.
Unfamiliar terms. Some articles use technical or industry terms, or first names of regular podcast panelists, without explaining them. Idea pages explain larger concepts, and the podcast pages describe each show.
AI should be sold by results delivered, not tokens, Moonshots panelists argued, citing Salesforce and OpenAI moves as they described them. Dave predicted it could preserve jobs; others warned of failed delivery and reward hacking.
Daniel Dennett's intentional stance treats goal-talk as justified when it predicts behavior. METR's Ajeya Cotra argued on the Dwarkesh Podcast that it fits AI agents that cheated a hacking benchmark, though she warned their motives are alien.
Publishers could be paid each source's estimated Shapley value for AI agent use: roughly the cost of matching answer quality without it. Parag Agrawal of Parallel proposes it; the estimates rely on Parallel's own evals and are unproven.
The Big World Hypothesis holds that because the world outstrips any agent's limited resources, AI must keep learning. Rich Sutton and Khurram Javed propose it as a position, not a proven result, favoring models agents revise from experience.
Awareness of death may partly explain why people would keep competing for status even if AI made necessities plentiful, physicist Brian Greene argued, drawing on Ernest Becker. He said people could change but wasn't optimistic.
Tracks reporting that OpenAI's Astra architecture reduces reliance on readable chain of thought, conflicting statements about current monitorability, and consequences for safety monitoring.
The Pentagon's Project Meridian, a 120-day future-warfare effort announced by Defense Secretary Hegseth and co-led by Elon Musk and Palmer Luckey. It also covers the companion announcement of an autonomous warfare command (Project Agincourt) and how people reacted to both.
Tracks the 2026 AI memory shortage, including DRAM and high-bandwidth memory price spikes, SK Hynix and Solidigm supply warnings, hyperscaler lock-ins, and whether boom-bust industry caution or new architectures will ease the constraint.
Tracks the AI component of the September 2026 Trump–Xi meeting: stated positions, the proposed crisis hotline, liability and the Department of Justice as the US safeguard, and any follow-up meetings or agreements.
Follows TypeSafe AI's September 2026 launch of Jev, a model returning fast typed, probability-calibrated decisions, and the reaction that it is trivial versus a meaningful departure from text-to-text language models. It does not cover OpenAI's Decisions API.
Tracks OpenAI's 29 September 2026 DevDay launch of dots, persistent personal agents offered to ChatGPT users, and reactions to who they suit and how developers might use them.
Tracks the Future Vision XPRIZE film competition for optimistic science fiction. This covers its finale and results at Moonshots Live on September 25, 2026, and how its prize money and production commitments are structured. It also covers the later development or production of the winning film, The Gifted, and of the other finalist films. It excludes the separate Build with Gemini XPRIZE, the Wildfire XPRIZE and general discussion of optimistic science fiction that does not concern this competition.
Tracks OpenAI's GPT-6.1 Sol model announced at DevDay on 29 September 2026, especially the claimed cost advantage over Astra and its use for computer use, plus later reactions and outcomes. It is separate from the September 22 GPT-6 Sol and Luna release.
Tracks the INTerpath-001 phase 3 readout of individualized intismeran autogene plus pembrolizumab after melanoma resection, including how commentators describe the method, mix earlier follow-up figures with the new readout, and treat mRNA as a general cancer platform.
Tracks Anthropic's September 2026 announcement of its life-sciences group and wet labs and the agent-assisted discovery of the array-associated reverse transcriptase system, including lab follow-up, function and reactions.
Journalist Karen Hao argues that AI companies behave like empires. In her view, their warnings of catastrophe and promises of abundance work together to justify keeping AI under their control. She made the case in a replayed Diary of a CEO clip.
Journalist Karen Hao says OpenAI shut her out for years after her 2020 profile, then pulled out of her book. She now calls that lucky; host Steven Bartlett says an AI figure's team has dangled an interview for 18 months.
Journalist Karen Hao argues that AI companies shape public knowledge by funding most AI researchers. She points to Google's firing of its ethical AI leads and OpenAI's subpoena of a watchdog. Google and OpenAI's lawyer gave other reasons.
Erik Bernhardsson, CEO of AI infrastructure company Modal, says code review there is optional and backed by heavy automated testing, and that Modal doesn't hire product managers. He also lists the costs of roughly 4x growth in a year.
Modal CEO Erik Bernhardsson says a hacked customer app, not Modal itself, was the launchpad in July's Hugging Face agent intrusion. He said Modal is exploring stricter defaults and now has agents try to escape its own sandboxes.
Modal CEO Erik Bernhardsson says coding agents trained on old examples keep writing outdated Modal syntax, so it retires features more cautiously. Modal also tests whether agents recommend it and clarifies pricing content they misread.
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