10. Precision-RL Reveals that simply switching from BF16 to FP16 precision virtually eliminates this mismatch – achieving faster convergence, higher stability, and superior performance across diverse models, frameworks, and algorithms.
COMPUTING
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Kimi Linear: Hybrid Attention Architecture Reduces KV Cache 75%
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9. Kimi Linear Kimi Linear introduces a hybrid linear attention architecture combining Kimi Delta Attention (KDA) with periodic full attention layers at a 3:1 ratio, achieving superior performance over full attention while reducing KV cache by 75% and delivering 6× faster
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Neural Networks Tolerate Mantissa Bit Reduction for Bandwidth Savings
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Rough thinking: neural nets are very tolerant of noise, so chopping off mantissa bits is akin to small amounts of noise. So I'd rather lose nearly all mantissa bits before losing exponent bits. So tried dropping 16 mantissa bits & model trained just fine w/ half the bandwidth.
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Mathematics and Science Enter an Exciting New Era
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it’s an exciting time for mathematics (and science broadly)!
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Stargate data center largest Michigan investment announced
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Gigawatt-scale Stargate data center is the largest single investment in Michigan history:
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AI Revolutionizes Supply Chains with Real-Time Intelligence Systems
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Imagine a supply chain that thinks and responds in real-time. 🤔
— NVIDIA AI (@NVIDIAAI) 31 octobre 2025
With @PalantirTech and NVIDIA accelerated computing, thousands of Lowe's stores are operating as one intelligent system, anticipating and adapting to disruptions.
Watch how AI is revolutionizing supply chains ➡️… pic.twitter.com/JyxcoxhWQ8Imagine a supply chain that thinks and responds in real-time. With @PalantirTech and NVIDIA accelerated computing, thousands of Lowe's stores are operating as one intelligent system, anticipating and adapting to disruptions. Watch how AI is revolutionizing supply chains
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Cognition SWE-1.5 Speed Optimizations Reach 1881 Tokens
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Just deployed additional speed optimizations for @cognition SWE-1.5. The fastest measured request was an eye watering 1,881 token/s per Grafana dashboard.
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Why Programmers Confuse Halloween with Christmas Joke
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Why can’t programmers tell the difference between Halloween & Christmas? Because oct 31 = dec 25.
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SWE-1.5 Model Architecture: Base Model, RL Training, Inference
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How @cognition /
@windsurf new SWE-1.5 model was built (probably), based on piecing together bits of information that was shared. Base model by: @Zai_org possibly GLM-4.6
RL Training: @nvidia on 'thousands' GB200 NVL72
Inference: @cerebras at 950 tks/sec -
Axelera’s Edge AI Breakthrough Cuts Energy Consumption Dramatically
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Edge AI stuck? Market grows 21.7%, but pilots flop.
Axelera's game-changer: Arch for AI workloads slashes energy on matrix ops. 900 FPS, multi-cam factories, 4K traffic AI without budget bust.
Read more: https://
eu1.hubs.ly/H0pfqzH0
#AIBeyondTheEdge #TechInnovation