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Perfect use case for Think Deeper: what's a topological qubit? https://t.co/4z6Lur3H7c pic.twitter.com/MkwSGI7sAe
— Mustafa Suleyman (@mustafasuleyman) 21 février 2025
Perfect use case for Think Deeper: what's a topological qubit? https://
aka.ms/AAu76rr
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Take it from @techradar SambaNova runs @deepseek_ai R1 at 198 tokens/sec using 16 custom chips! Our SN40L RDU chip is 3X faster & 5X more efficient than GPUs 5X speed boost coming soon, with 100X capacity on cloud. https://
bit.ly/3Xatj6k
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@techradar reported that SambaNova’s @deepseek_ai
-R1 achieved industry-first #AI performance with 95% fewer chips. @RodrigoLiang told @Waynewill1
: “We’re collapsing inference costs and slashing hardware demands—from 40 racks to just one.” #GPU #DeepSeek
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Microsoft’s ‘topological qubit’ is seven years late and a million bits short Microsoft told me they would have a “topological qubit” in 2018. It’s only just arrived this week — maybe. There’s skepticism among scientists as to whether Microsoft’s paper in Nature actually proves
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The number of H100 GPUs used for training helps estimate parameters, data size, and training duration, so it’s an important detail. But Grok’s team hasn’t been clear about key factors like benchmark performance and the exact number of GPUs used for training, which leads to
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I want to clarify this. Was Grok-3 trained on 200k H100s, or is it being served using them? I remember hearing in the live Q&A that it was trained on 100k H100s.
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Microsoft Says It Has Created a New State of Matter to Power Quantum Computers
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The AI CUDA Engineer: Agentic CUDA Kernel Discovery, Optimization and Compositionhttps://t.co/fMDhdIkNIo
— hardmaru (@hardmaru) 20 février 2025
In principle, AI can be as resource-efficient as our brains 🧠. To achieve this, we can use AI to make AI more efficient! Eventually, AI will become a million times faster. https://t.co/84rZGBKHns
The AI CUDA Engineer: Agentic CUDA Kernel Discovery, Optimization and Composition https://
pub.sakana.ai/ai-cuda-engine
er/paper/
… In principle, AI can be as resource-efficient as our brains . To achieve this, we can use AI to make AI more efficient! Eventually, AI will become a million times faster.
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Artificial Intelligence Is Putting Ever-Increasing Demands on Our Resources
#AI #AIio #BigData #ML #NLU #Futureofwork @lexfridman @sama @kaifulee @ID_AA_Carmack @karpathy @2morrowknight @ylecun
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What a breakthrough! Published in Nature today, this is "a new state of matter" to power the first topological qubits. With scalable quantum computing, we'll soon be able to solve previously impossible problems in chemistry, biology and life sciences. Truly exciting times.