Big release out of Japan’s Sakana AI. Its Fugu and Fugu Ultra models use agent orchestration of a variety of other models to reach Fable/Mythos levels on several benchmarks
MACHINE LEARNING
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User hopes 5.6 brings impressive math solving abilities.
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I just hope 5.6 comes with some mad Math solving skills. Don’t really care about how much better of a coding model it’s gonna be.
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50 Steps to Master AgenticAI in 2025-26
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50 Steps to Master #AgenticAI in 2025-26
by @ingliguori #LLM #GenerativeAI #ArtificialIntelligence #MachineLearning -
AI ARR triples to $500M, Firefly reaches $300M
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Their AI-focused ARR tripled year over year to surpass $500 million. Very few enterprise software companies report this level of direct, paid AI adoption. The engine of this breakthrough is Firefly, which now reaches $300 million.
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Sakana Fugu uses multi-agent orchestration of LLMs recursively
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How does it work? Sakana Fugu is itself an LLM, trained to call various LLMs in an agent pool, including instances of itself recursively. Fugu dynamically orchestrates the world's best models to tackle complex, multi-step tasks. As shown in this figure, Fugu is a multi-agent
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Fugu Matches Top Models; Orchestration Models Next Frontier
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Fugu stands shoulder-to-shoulder with leading models like Fable and Mythos across the industry's most rigorous engineering, scientific, and reasoning benchmarks. Read the full blog: https://
sakana.ai/fugu-release Beyond Bigger Models: Why are Orchestration Models the Next Frontier -
Question on DiffusionGemma’s transparency and hidden reasoning
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What is the transparency of DiffusionGemma? Given how diffusion language models (Diffusion LMs) denoise tokens instead of generating them left to right, there is a concern about how reasoning will be hidden in
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11 Free Google AI Tools You Need to Try
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11 Free Google #AI Tools You Need to Try.
by @genamind #ArtificialIntelligence #MachineLearning #ML #Technology -
LLMs prove reasoning can emerge from language statistics
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I am not garymarcusing here. LLMs are proof that it is possible to distill intelligent reasoning behavior by doing statistics over human language patterns
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Learning world models from dropping a cup of water
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When @olivercameron was the first to teach us about world models (he just collected $300 million investment last week) in my head I was thinking: "If I drop a cup on the ground, with some water in it, and film that with a high speed camera, the world model would learn a lot about