Anthropic: "We do not plan to make Claude Mythos Preview generally available" A big line, buried quite deep. Possible reasons? So many, inc: 1) The model is expensive (25/125), not far off GPT 4.5, which became commercially unviable. Less likely, given the claims about Mythos. 2) They genuinely are worried about unleashing cybersecurity choas on the world. 3) They don't have capacity to serve it at scale yet. 4) They will quickly distil the early access outputs of Mythos into a lighter model, so no need to release the bigger model when a more cost efficient one coming imminently. 5) Other. Not read the 250 page report yet, but will do.

Nano Banana Pro drew an admirably edgy Rake's Progress, 2025-edition.

If you use GPT-5 Pro for coding, you will swiftly realize that it will never agree to anything, even its own suggestions, without adding 'two quick tweaks'. It's a pathological perfectionist. *Still very useful, just strange in this particular way. **Gave Pro this tweet and it suggested this new version, with 'two tweaks': "If you use GPT‑5 Pro for coding, you’ll quickly realize it never accepts anything—even its own suggestions—without adding “two quick tweaks.” It’s a pathological perfectionist. Still useful, just strange in this particular way." ***Gave Pro that tweet, and it had 'two tiny notes': "When posting, drop the outermost quotation marks (they’re just framing here). Check you’re within the 280‑character limit (~229 chars, including line breaks)."

2 quick updates, and look-ahead, exactly a year on from first testing models on Simple-Bench: 1) Claude 4 busted our rate limits, and my entreaties to @AnthropicAI (to allow us to spend more money!) have yet to bear fruit. A shame, as am fairly confident Opus 4 would be SOTA. 2) Gemini 2.5 Pro 05-06 and Flash 05-20 (the latest versions) are actually a slight downgrade in both performance and instruction-following and the one full run we got out of 2.5 Pro got 46% (below the previous version's 51%). We would prefer to get an AVG@5, for fairness, before posting on the leaderboard. Thoughts: RL becoming 20% of the compute spend for frontier models may have more strange side effects than labs were anticipating. 'Over-eagerness' over simply following commands seems barely under control. On Simple, I had been fairly confident it would be saturated (>80-85%) by the end of the year. Now I think it is more like 50-50, and progress could instead slow for a while, as models become relentlessly optimised for dollar-maximising tasks, like software engineering, over general nous. Spatial intelligence, like spotting that the glove would fall onto the road, in the question pasted at the bottom of this tweet, is simply not yet as lucrative. As ever, grateful to @weights_biases and @Ag_Mlynarczyk in particular for keeping the show on the road. Q. A luxury sports-car is traveling north at 30km/h over a roadbridge, 250m long, which runs over a river that is flowing at 5km/h eastward. The wind is blowing at 1km/h westward, slow enough not to bother the pedestrians snapping photos of the car from both sides of the roadbridge as the car passes. A glove was stored in the trunk of the car, but slips out of a hole and drops out when the car is half-way over the bridge. Assume the car continues in the same direction at the same speed, and the wind and river continue to move as stated. 1 hour later, the water-proof glove is (relative to the center of the bridge) approximately? Models (super-trained on HS Math): 4km East

The shift from a cautious, collaborative attitude wrt China not long ago to a zero-sum competitive outlook today - by both Dario and Sam - has been very disappointing - and they’ve offered no explanation for the change!

🪄 Think you’re an AI wizard? Prove it. We’ve partnered w/ @AIExplainedYT to launch the Simple Bench Evals Competition—a challenge so tough, he said: “If anyone gets 20/20 with a general-purpose prompt, I would be truly shocked.” 😳 Details below 👇

A shot of the AI Explained studio in the Shard, London...(courtesy of Veo 2)