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LLMS
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Agentic AI Playbook 2026: Turning LLMs into Reliable Agents
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The Agentic AI Playbook 2026 Edition Turns LLMs into Reliable AI Agents: http://
amzn.to/49zjzId -
Design Multi-Agent AI Systems — New Packt Release
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New release from @PacktDataML available at: http://
amzn.to/40Sp4O9 "Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based Agentic AI Framework with tool use, memory, and multi-agent workflows" Table of Contents:
Introduction to Generative AI and AI -
Chronological list of baffling OpenAI model names
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The great thing is that the names are so baffling that the most important models OpenAI released were names davinci-002, GPT-3.5, GPT-4, o1-preview, o3, GPT-5 Pro, and you would never know the ways they are connected (my listing was chronological)
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Custom CUDA Kernels for TwELL Format on H100 GPUs Released
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If you want to look under the hood at the actual custom CUDA kernels and see exactly how we implemented the TwELL format for H100 GPUs, we’ve released the reference code. GitHub: https://
github.com/SakanaAI/spars
er-faster-llms
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Blog: https://
pub.sakana.ai/sparser-faster
-llms/
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New AI-Driven Workflow for HTML Generation
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Anthropic's Thariq's article on HTML from yesterday blew up, with 1.5M reads. It looks like it's talking about formatting aesthetics, but actually he's describing an entirely new workflow. Picking out a few of the points with the most technical depth. First, HTML isn't a
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Sakana AI Accelerates Sparse LLMs with NVIDIA
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Sakana AIは、@NVIDIAとの共同研究で、スパースなTransformer言語モデルの推論・学習を高速化する新しいGPUカーネルとデータ形式を開発しました。
— Sakana AI (@SakanaAILabs) 9 mai 2026
ブログ：https://t.co/fMARMRFsJJ
LLMのコストの大部分を占めるフィードフォワード層では、実は各トークンに対して大半の活性がほぼゼロで無駄な計算に… https://t.co/nTMg0QgdSrSakana AI has developed new GPU kernels and data formats that accelerate inference and training of sparse Transformer language models through joint research with @NVIDIA
. Blog: https://
pub.sakana.ai/sparser-faster
-llms/
… In the feedforward layers, which account for the majority of LLM costs, most -
Claude Mythos Preview snapshot outperforms next best model by 2x
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An early Claude Mythos Preview snapshot we provided METR has a time horizon of more than 2x the next best model on their 80% success rate benchmark
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ChatGPT 5.5’s Math Skills Analyzed
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I write about this in more detail in a blog post with a guest contribution from Isaac Rajagopal, a student at MIT on whose work ChatGPT built, who gives his assessment of the level of mathematical ability displayed by the model. https://
gowers.wordpress.com/2026/05/08/a-r
ecent-experience-with-chatgpt-5-5-pro/
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DeepMind solves 48% of a complex math benchmark
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Google DeepMind's AI co-mathematician just scored 48% on FrontierMath Tier 4, a new high on a benchmark of 50 research-level math problems some professors expected AI wouldn't touch for decades. The system generated a proof so flawed its own reviewer flagged it as wrong. But