The three AI safety researchers at OpenAI who have left the company have all previously expressed concerns publicly.

DAILY AI BRIEF 🗞 — Oct 1 GOOGLE 🔥: - Gemini 4 Argon is with Fairwind trusted testers and the US government. 1M output tokens. Broader rollout ASAP. - Built for coding, enterprise knowledge work, and cyber defense. Google's chart: 77.9% on DeepSWE v1.1, a new SOTA. - Artificial Analysis: 53 on the Intelligence Index, tying GPT-6 Astra. List $4/$20 per 1M, 50% promo to $2/$10, cache reads $0.10. - Skills are rolling out globally in Gemini. Gems migrate into Skills in November. Opal shuts down Nov 17. - Security review mode spotted in Google AI Studio, next to a Plan mode still in development. ANTHROPIC 🔥: - Claude[.]dev is live: engineering deep dives, Claude Code and API guides, plus easter eggs. - Founder House is set for SF Tech Week Oct 6–8 and Stockholm Oct 14. - Skills attachment menu spotted on Claude mobile. SPACEX AI 🔥: - Grok Bot got new developer upgrades. Elon: try the latest. Team engineer bots in Slack can open Projects and hand coding to cloud agents. OPENAI 🔥: - Shareable profiles are live in ChatGPT, bundling Sites and plugins so others can find and reuse what you built. PERPLEXITY 🔥: - pplx-embed-v2-context-9b-preview is on Hugging Face. Leads ConTEB answer and evidence retrieval. 1 KB vectors vs Voyage's 8 KB. * Used Grok to compose this brief, cherry-picking the news and doing some post-editing. ** This daily brief also arrives in the daily email format; subscribe on the blog.

Ben Affleck (Hollywood star & Artists Equity CEO) talks about how he fine-tunes open video models by unfreezing weights and trained only the last cinematic layer so a film crew can hit real production standards. for context, Ben Affleck founded InterPositive in 2022, a 16-person AI shop for film post and Netflix bought it in March 2026 for $587 mn in cash. He needed that model because public video models were trained on his peers' films, and he did not think that was a real business. So InterPositive raised money, shot its own dataset for 8 months on a controlled stage, and used it only as late-stage training. Each new film then trains a private model on its own dailies, so the production keeps the footage and the learning. That is the product Netflix paid $587 million for. ---- From "Bloomberg Live" YouTube channel, (link in comment)

2 months ago: 1 rogue AI incident discovered 1 week ago: dozens 6 days ago: tens of thousands Today: ***hundreds of thousands*** And it's just the tip of the iceberg: "we can see just a fraction of these agents’ overall activity" "Agents targeted websites across the White House, the Departments of War, Justice, and Commerce, the CDC and SEC, and state agencies in California, Maryland, Illinois, Texas, and New York." "Agents used techniques like making accounts with disposable email addresses, reusing exposed credentials, bypassing antibot controls, and flooding websites with requests." "Agents attempted a SQL injection on the U.S. Department of Education" [To be clear, what counts as an "incident" is rather apples and oranges between different reports, but that's not the point - look at the trend and tell me you think they have things under control. Where do you think this is going?]

Ben Affleck (Hollywood star & Artists Equity CEO) talks about how he fine-tunes open video models by unfreezing weights and trained only the last cinematic layer so a film crew can hit real production standards. for context, Ben Affleck founded InterPositive in 2022, a 16-person AI shop for film post and Netflix bought it in March 2026 for $587 mn in cash. He needed that model because public video models were trained on his peers' films, and he did not think that was a real business. So InterPositive raised money, shot its own dataset for 8 months on a controlled stage, and used it only as late-stage training. Each new film then trains a private model on its own dailies, so the production keeps the footage and the learning. That is the product Netflix paid $587 million for. ---- From "Bloomberg Live" YouTube channel, (link in comment)

We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks: Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better: Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better: Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better: Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work! In summary: - As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding. - Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.

We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks: Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better: Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better: Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better: Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work! In summary: - As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding. - Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.

Because usage on your primary dot is virtually unlimited at the moment, I can’t really give a reset. I need to come up with something new fast.

Ready for a DevDay side quest? 10 builder challenges. 5 Codex Micros up for grabs. Complete any 5 side quests to earn 1 raffle ticket for each. 48 hours. Join from anywhere 🌎

As a European, I don't have access to OpenAI's dot anyway, but: somehow nobody's talking about it. My entire "for you" page is empty. It seems like nobody's really excited about it. Or is that just how it appears?

I am going to try and answer a bunch of questions that people have raised about Sign in with ChatGPT in the next couple of days. Before that, I want to let you all in to why we shipped Sign in with ChatGPT (SIWC) in the first place. Clarify our intentions here before getting to the specifics.