make a product super usable and ppl will pay you for it we’re way past models maxing benchmarks – if they’re not doing actual work for you, you’re asleep at the wheel
AI
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Custom Kernels Reduce GPU Memory Requirements for AI Models
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Yeah the custom kernels make the difference, most setups need 15-20GB for similar models
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Dreamina Seedance 2.0 Now Available for US Users
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Dreamina Seedance 2.0 is officially live in the US! Previously rolled out across regions including Southeast Asia, the Middle East, Africa, Europe,and South America — and now available to US users. We invite you to give it a try！
→ View original post on X — @scobleizer, 2026-04-08 13:48 UTC
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Python Libraries for Data Science and Big Data
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Python Libraries for #DataScience by @Python_Dv #BigData #DataScientist
→ View original post on X — @ronald_vanloon, 2026-04-08 13:45 UTC
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Brand Studio: AI Creative Platform Designed for Your Brand
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Your brand is an afterthought for out-of-the-box AI tools. Of course it is. They weren’t built for you, they were built for everyone.
— Stability AI (@StabilityAI) 8 avril 2026
You deserve a creative production platform that puts your brand first, exactly how you envisioned.
Introducing Brand Studio by Stability AI, the… pic.twitter.com/MoR79gKksCYour brand is an afterthought for out-of-the-box AI tools. Of course it is. They weren’t built for you, they were built for everyone. You deserve a creative production platform that puts your brand first, exactly how you envisioned. Introducing Brand Studio by Stability AI, the
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GLM-5.1 Real-World Usability Compared to GLM-5
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There is no reason to believe that they made GLM-5.1 worse than GLM-5 in real-world usability?
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GLM-5.1 Active Parameters Comparison with DeepSeek V3.2
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GLM-5.1 has 40B active parameters per token versus 37B in DeepSeek V3.2, so that can't be it.
Regarding quantization, sure, but quantization general technique that could also be applied similarly to DeepSeek V3.2. -
AI Transparency and Data Privacy: Building User Trust
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The biggest problem with AI isn’t the technology itself; it’s when people don’t know it’s being used or how their data is handled. When companies are upfront about AI usage, it builds trust and gives users the choice to opt in or out. pic.twitter.com/pXhvRVPxW8
— Satya Mallick (@LearnOpenCV) 8 avril 2026The biggest problem with AI isn’t the technology itself; it’s when people don’t know it’s being used or how their data is handled. When companies are upfront about AI usage, it builds trust and gives users the choice to opt in or out.
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Industrial Intelligence: Building AI Infrastructure for New Era
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Why Industrial Intelligence? Because scaling AI isn’t just about smarter algorithms—it’s about building the infrastructure of a new era. This is an industrial race. Not metaphorically. Literally. Tens of billions are being poured into hardware, energy, mineral supply chains,
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Questioning embedding size and code optimization explanations
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Interesting. Is there an explanation for this? I mean the embedding size is smaller but that's probably hardly it? So more like a code optimization?