Prefill and decode stress hardware differently. Prefill is compute-bound, so Blackwell Tensor Cores, memory bandwidth, NVLink, and SHARP reductions help. Decode is latency/memory-bound, where GB200’s rack-scale NVLink domain opens up parallelism Hopper could not.
AI HARDWARE
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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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The Economic Gamble of AI Compute Infrastructure
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Compute is scarce and has to be bought years in advance, before companies know whether revenue will ever catch up.
— Gary Marcus (@GaryMarcus) 11 mai 2026
That is exactly the nature of the largest gamble in history.
Heaven help the global economy if it’s wrong. https://t.co/CqM7vcac34Compute is scarce and has to be bought years in advance, before companies know whether revenue will ever catch up. That is exactly the nature of the largest gamble in history. Heaven help the global economy if it’s wrong.
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Hardware Considerations for Running Local AI
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If you’re interested in Local AI, I highly recommend reading those 2 articles BEFORE making any hardware purchases Find them under the articles tab on my profile
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Developer burns full transformer into FPGA at 50K tokens/sec
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/1 Developer implements a full transformer model in FPGA hardware, achieving 50,000 tokens per second without a GPU. What if an AI model ran with zero software? No Python, no GPU, no runtime—just logic etched into a chip. That’s exactly what TALOS-V2 does. TALOS-V2 explores what happens when a small…
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Controlling a Robotic Arm With Thought via Machine Learning
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Controlling a #Robotic Arm With Thought Alone
— Ronald van Loon (@Ronald_vanLoon) 11 mai 2026
by @IntEngineering#Robots #MachineLearning #ArtificialIntelligence #ML pic.twitter.com/OuqVyv5I5cControlling a #Robotic Arm With Thought Alone
by @IntEngineering #Robots #MachineLearning #ArtificialIntelligence #ML -
Students build AI financial service using custom Mac Studio cluster
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Un groupe d’étudiants chinois a acheté 7 Mac Studio sur eBay pour un total de 3 600 $, les a reliés via Ethernet pour former un seul système, puis a ouvert un cabinet financier basé sur l’IA directement dans leur chambre universitaire.
— Jouhatsu | AI Influence Operator (@Jouhatsu_ai) 10 mai 2026
Leur premier client payait un conseiller… https://t.co/INA2WhAhlc pic.twitter.com/ovdfcIOJlNUn groupe d’étudiants chinois a acheté 7 Mac Studio sur eBay pour un total de 3 600 $, les a reliés via Ethernet pour former un seul système, puis a ouvert un cabinet financier basé sur l’IA directement dans leur chambre universitaire. Leur premier client payait un conseiller
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NVIDIA and Corning Partner to Advance AI Infrastructure Manufacturing
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Corning – NVIDIA and Corning Announce Long Term Partnership To Strengthen U.S. Manufacturing for AI Infrastructure! $500 million – Strategic investment NVIDIA is making a major strategic investment in Corning to secure advanced optical connectivity for AI infrastructure.
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Running local AI agents reveals hardware compute bottlenecks
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running agents on my laptop is the first time in a long time where i feel my computer is underpowered i could actually consume way more RAM and GPU if it was available
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MiniCPM-o 4.5 for omni-modal interactions
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MiniCPM-o 4.5 Towards Real-Time Full-Duplex Omni-Modal Interaction paper: https://
huggingface.co/papers/2604.27
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