The Chinese AI model ecosystem is moving so fast. Curious how GLM-5 stacks up for coding or even writing quality!
@whats_ai
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DSPy Achieves Real Enterprise Adoption Milestone
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Super cool to see DSPy getting real enterprise adoption!
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Native 2K Support Delivers 5x Performance Improvement
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5x faster with native 2K is incredible. Super excited to test its limits 😀
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The Sycophancy Problem in AI Models: Why Flattery Signals Useless Answers
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The sycophancy problem is so real haha. Every time a model starts with "What a great question!" I already know the answer is going to be useless.
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AI-Science Feedback Loop: Models and Scientists Advancing Together
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The feedback loop between domain experts and AI engineers is exactly what makes AI for science so exciting. The model gets better from the scientist, the scientist gets to explore more because of the model.
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French Synthetic Data at Scale: Regional Variation Challenges
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Super cool to see French-grounded synthetic data at this scale! As a French-Canadian, curious how the demographic distributions handle regional French variations 🙂 It's usually pretty bad especially voice generation haha.
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30x Faster: Breakthrough ML Performance Results
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30x over cuML and 200x over FAISS is incredible. Congrats on the paper!
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2026 AI: Chaos or Plateau? Evaluating Current Model Capabilities
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2026 is either going to be chaos or a full plateau haha. We're already struggling to evaluate and fully understand the capabilities of the current models to best leverage them..!
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How Do AI Models Learn: Brain Changes vs Temporary Information
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New video out! Are we actually changing the model’s brain, or are we just giving it temporary information? That's what we are answering this week! Check it out:
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Restrictions Drive Innovation: Tech’s Recurring Pattern
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Every time there's a restriction, there's an innovation to work around it. That pattern keeps repeating in tech. Starting to think we need restrictions so that we are forced to find ways arround and innovate vs. exploiting what works haha