ML isn’t magic — it’s a workflow. 1. understand data 2. choose right algorithm 3. train 4. test 5. optimize 6. deploy + monitor + retrain The winners are the teams who run this loop consistently. #MachineLearning #AI #DataScience #MLops
RESEARCH
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Kimi Proposes Solution to LLM Prefill-Decode KV Cache Transfer Problem
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A new paper just exposed how much money AI labs waste on GPUs. Running LLMs at scale hits a wall when prefill and decode share one datacenter. The KV cache transfer between them is massive. This forces expensive RDMA networks and identical hardware everywhere. Kimi proposes
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Autonomous Driving AI Safety and Performance Improvements Debate
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I totally disagree. You have zero experience with it. When you do you will see how wrong you are. It will save MANY lives for instance. But it is way way way way way smoother and better than you are at driving. Already. And it is improving.
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AI Model Performance Gap Narrows: Grok-4.20 and GPT-5.4 Converge
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The gap at the top of AI is closing fast. Multiple models now score at the same level with Grok-4.20 Expert Mode and GPT-5.4 Pro (Vision) leading the latest benchmark. But the bigger signal isn’t who’s #1. It’s how quickly performance is converging. When top models are
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DeepSeek Delivers Open-Source Model Rivaling OpenAI at Lower Cost
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Maybe… but that’s a different discussion. The real point is that DeepSeek seems to be delivering a fully open-source model for free, on par with OpenAI’s most expensive models, … and doing it with far fewer resources! 🙂
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Generative AI Stochastic Thermodynamics Book Pre-order Now
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Our book on Generative AI and Stochastic Thermodynamics can be pre-ordered with a 20% discount until July 31 2027. (All proceeds from the authors will be donated to the African Institute for Mathematical Sciences).
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European AI Development: A Sarcastic Take on Progress
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The OP is sarcasm about the state of AI in Europe
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Exponential AI Growth: Doubling Every 31 Steps
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If you double a penny 31 times you end up with about $11 million dollars. No doubles = one penny
1 doubles = two pennies
2 doubles = four pennies
3 doubles = eight pennies
4 doubles = 16 pennies
5 doubles = 32 pennies Which is where we are right now. Guess what comes next? 64 -
Google DeepMind Relocates LLM Team from UK to California
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Google DeepMind is an American company. The LLM people (Gemini) have moved to California. I was part of AlphaGo (
https://
arxiv.org/pdf/1812.06855), Alphacode, Gato, Veo, etc, all built in the UK, but all that is now past. -
Statistical facts about humanity and ethical implications in AI discourse
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I reject the notion that factual statistical statements about humanity constitute normative claims and are furthermore impermissible on moral grounds, but I freely offer my contempt to you if helps you