Joe Cheuk

I quit @GoogleDeepMind to build a marketing team that never stops working. Today, we're launching @HelloPomo. Your marketing, from insight to execution, unified. Pomo watches everything happening across your market, tells you exactly what to do next (the budget shift to make, the trend to jump on, the buyer to answer), then prepares the assets for your approval. @JoeC7007 and I have raised a $4.5M Seed led by @KindredVentures (@stevejang ), with backing from @SevenStars_VC (@stevenl ), @svangel (@AndreaShuyuWang ), @databricks, Timeless (@gauravahuja, @eshan_shetty), @645Ventures, @scottbelsky, @mghissassi & @mascarom. Reply with your website. We'll run Pomo for 10 companies and show you the growth opportunities it finds and the work it creates.

I quit @GoogleDeepMind to build a marketing team that never stops working. Today, we're launching @HelloPomo. Your marketing, from insight to execution, unified. Pomo watches everything happening across your market, tells you exactly what to do next (the budget shift to make, the trend to jump on, the buyer to answer), then prepares the assets for your approval. @JoeC7007 and I have raised a $4.5M Seed led by @KindredVentures (@stevejang ), with backing from @SevenStars_VC (@stevenl ), @svangel (@AndreaShuyuWang ), @databricks, Timeless (@gauravahuja, @eshan_shetty), @645Ventures, @scottbelsky, @mghissassi & @mascarom. Reply with your website. We'll run Pomo for 10 companies and show you the growth opportunities it finds and the work it creates.

ANTHROPIC ENGINEER: "FABLE 5 IS ALREADY SMARTER THAN WE KNOW HOW TO USE. THE BOTTLENECK WAS NEVER THE AI. IT'S YOU." In 20 minutes he shows exactly how to build an agent that improves itself. No extra tools. No extra cost. Most people are still doing all of this by hand, one prompt at a time. Watch the session, then save the guide below. Bookmark this. Follow @cyrilXBT

I benchmarked the new models (Sol, Terra, Luna, Fable 5, Meta Muse Spark 1.1, Grok 4.5) on an induction reasoning task. This is an updated table from yesterday, and my benchmark is described as spotlight in ICML '26. How to read the table: The models are given several small graphs (6-10 graphs, each with 8-10 elements), in which some nodes are designated. They must return a first-order formula that describes properties of the designated nodes simultaneously for all graphs. The benchmark has 64 such problems (a subset of the bigger benchmark). Correct: how many formulas correctly describe the designated nodes. Holdout correct: a number of additional graphs, with the same underlying property, are held out. This is to test the ability of the model's correct formulas to generalize. For instance, if a formula is a big case split rather than the underlying simple graph property, it won't generalize. Formula complexity (in AST): mean and median size of the correct model's formulas. A few observations and experiment notes: - All new models are remarkably good. Even Luna and Muse Spark outperforms GPT 5.4. - Some models are better in returning simple formulas that generalize well. - Fable 5 was extremely hard to get results from. I first ran it with higher thinking effort levels, in which case it charged for max tokens per problem and returned all "" responses. The only settings in which it returns non-"" responses are medium and low. My method for running it was to call it on medium, then call it again on medium, then on low. - GPT 5.5 is absent because it had the same non-return behavior as Fable 5 above, but even worse. So bad that I couldn't get almost any results and would have wasted too much $$ on empty responses. Happy to see that the new OpenAI models are "cured" of this GPT 5.5 issue. - I had observed that Grok 4 >> Grok 4.1 Fast > Grok 4.20 >> Grok 4.3. Finally, this downward trend of XAI has been reversed and Grok 4.5 is now a contender. - Meta Muse Spark 1.1 is a big surprise. It beat GPT 5.4 on this task! - The paper is out and the benchmark is public: icml.cc/virtual/2026/e…

Encore un scandale. On accuse Elon Musk sans arrêt de se servir de Grok pour faire passer ses idées. Pourtant, le @neutralityorg vient de sortir The Neutrality Project : une étude indépendante qui prouve l’inverse. Sur 18 modèles IA testés, 54 positions sur 60 atterrissent à gauche du centre. Moyenne globale : -0.41 (biais progressiste massif, surtout environnement et valeurs sociales). Et Grok 4.5 ? -0.02. Le modèle le plus neutre de tout le benchmark. Le seul vraiment proche du centre. Pendant ce temps, les autres boîtes injectent massivement leur idéologie de gauche dans des IA qui répondent à des milliards de questions par jour. Manipulation des masses à grande échelle. C’est absolument scandaleux. Ça devrait être un scandale mondial. x.com/neutralityorg/…