0% markup + automatic model routing is the part people should pay attention to. The winner won’t be the app using the biggest model for everything.
It’ll be the one that knows when not to.
LLMS
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Optimizing AI Application Performance via Intelligent Model Routing
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Optimizing Throughput for Large MoE Models on GB 200 Hardware
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GB 200s change how one does the prefill and decode disaggregation when serving large MoEs like Qwen. We’ve published details of our stack quantifying the throughput benefits compared to serving on Hoppers.
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NVIDIA GB200 Architecture Optimized for Large-Model Inference
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This NVIDIA remains the strongest platform for large-model inference at scale. Prefill/decode disaggregation, Blackwell-native quantization, custom kernels, and rack-scale NVLink turn GB200 into faster answers lower serving cost. Read the full paper here
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Performance Benchmarks: NVIDIA H200 vs GB200 for AI Workloads
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The benchmarks show the gap. NVLS all-reduce latency drops from 586.1µs on H200 to 313.3µs on GB200. In MoE prefill at EP=4, combine falls from 730.1µs to 438.5µs. For decode, GB200 sustains much higher throughput at high token speeds.
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Research on Serving Qwen3 235B Models on NVIDIA GB200 Racks
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We published new research on how we serve post-trained Qwen3 235B models on NVIDIA GB200 NVL72 Blackwell racks. GB200 is a major step up over Hopper for high-throughput inference on large MoE models, not just a training platform.
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Debating the economic ROI of major AI labs
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that’s actual speculative; so far OpenAI and Anthropic have lost money and most businesses have not gotten significant RoI
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Google Gemini Omni Video Generation Model Leaks Ahead of I/O
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🤯Google vient de leaker son prochain monstre.
— VISION IA (@vision_ia) 12 mai 2026
Gemini Omni : un modèle de génération vidéo qui vient d'apparaître chez certains utilisateurs Gemini, juste avant Google I/O (19-20 mai).
Les premiers résultats sont bluffants, un utilisateur a demandé "un professeur qui écrit une… pic.twitter.com/U86extcaNFGoogle vient de leaker son prochain monstre. Gemini Omni : un modèle de génération vidéo qui vient d'apparaître chez certains utilisateurs Gemini, juste avant Google I/O (19-20 mai). Les premiers résultats sont bluffants, un utilisateur a demandé "un professeur qui écrit une
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Evolution of Excel: From Early ML to LLMs
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excel didn’t have LLMs in the 90s (it did have some ML, which I have praised, but not that far back).
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Analyzing o3, Grok 4, and Claude Code
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start with https://
open.substack.com/pub/garymarcus
/p/how-o3-and-grok-4-accidentally-vindicated?r=8tdk6&utm_medium=ios
… and my substack piece on Claude Code and then read my 2001 book The Algebraic Mind -
Claude Code and the Neurosymbolic Approach to LLM Limitations
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claude code is an immense neurosymbolic effort to ward off the failure of pure LLMs. you sir are lost.