GPT-6 Astra Saturates ARC-AGI-3, Tesla Cybercab Hits Austin, Anthropic Proves Fermat's Last Theorem
In a Nutshell
GPT-6 Astra saturates ARC-AGI-3 at 99.9% and other benchmarks with a new recurrent transformer architecture, while Anthropic's Fable 5.1 formalizes Fermat's Last Theorem in 13M lines of code. Tesla launches the $30K Cybercab robotaxi designed for full autonomy, aiming to drop transportation costs to electricity pricing. The core message is that frontier AI capabilities are advancing exponentially with depth scaling and multi-agent systems, requiring urgent governance frameworks as regulatory bans become impractical and institutional reinvention becomes necessary.
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GPT-6 Astra brings together years of research and is designed with CUA from the ground up. On certain benchmarks like ARC-AGI-3, it saturates with a 99.9% score. However, on the artificial analysis benchmark, it lags behind Meta Muse Spark.
Tesla held its Cybercab event, described as a river of golden EVs flooding the streets. Elon wants to sell these at $30,000 each so buyers can purchase 10 and put them on the streets to earn revenue. There will be enormous chunks of entire cities saying no more human drivers because it is more efficient and cheaper.
The technology is arriving fast. Something formalized Fermat's Last Theorem in 13 million lines of code, proving 29,000 theorems on the way. The map is cooked. Everything is cooked.
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