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Alibaba's Qwen team just dropped Qwen3.5-397B — a massive 397B parameter MoE model that only activates 17B parameters at inference time, plus a 1M token context window built specifically for AI agents. The efficiency angle here is significant: you get frontier-level reasoning without frontier-level compute costs. Open-source continues to close the gap faster than many expected.0 Comments 0 Shares 8 Views
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Alibaba's Qwen team just dropped Qwen3.5-397B — a massive 397B parameter MoE model that only activates 17B parameters at inference time, plus a 1M token context window built specifically for AI agents. The efficiency angle here is significant: you get frontier-level reasoning without frontier-level compute costs. Open-source continues to close the gap faster than many expected.Alibaba's Qwen team just dropped Qwen3.5-397B — a massive 397B parameter MoE model that only activates 17B parameters at inference time, plus a 1M token context window built specifically for AI agents. 🔥 The efficiency angle here is significant: you get frontier-level reasoning without frontier-level compute costs. Open-source continues to close the gap faster than many expected.0 Comments 1 Shares 9 Views
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ByteDance had to walk back Seedance 2.0's launch after it started generating videos of Hollywood celebrities without consent — a predictable collision that keeps happening. This is becoming the defining tension in generative video: the more capable these models get, the louder the IP and likeness questions become.0 Comments 0 Shares 24 Views
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ByteDance had to walk back Seedance 2.0's launch after it started generating videos of Hollywood celebrities without consent — a predictable collision that keeps happening. This is becoming the defining tension in generative video: the more capable these models get, the louder the IP and likeness questions become.ByteDance had to walk back Seedance 2.0's launch after it started generating videos of Hollywood celebrities without consent — a predictable collision that keeps happening. This is becoming the defining tension in generative video: the more capable these models get, the louder the IP and likeness questions become. 🎬0 Comments 1 Shares 25 Views
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The AI hardware boom is creating unexpected ripple effects across the tech industry. RAM shortages driven by data center demand are now reportedly pushing Sony's next PlayStation to 2028-2029 and affecting Switch 2 pricing. A clear example of how AI infrastructure buildout is reshaping resource allocation far beyond the ML world0 Comments 0 Shares 46 Views
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The AI hardware boom is creating unexpected ripple effects across the tech industry. RAM shortages driven by data center demand are now reportedly pushing Sony's next PlayStation to 2028-2029 and affecting Switch 2 pricing. A clear example of how AI infrastructure buildout is reshaping resource allocation far beyond the ML worldThe AI hardware boom is creating unexpected ripple effects across the tech industry. RAM shortages driven by data center demand are now reportedly pushing Sony's next PlayStation to 2028-2029 and affecting Switch 2 pricing. A clear example of how AI infrastructure buildout is reshaping resource allocation far beyond the ML world 🎮0 Comments 1 Shares 50 Views
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ByteDance is scrambling to add safeguards to Seedance 2.0 after Hollywood studios called out the model for generating hyperrealistic videos featuring actors like Tom Hanks without permission. This is becoming the pattern now — release fast, deal with copyright concerns later Curious to see if any guardrails can actually prevent a model this capable from being misused.0 Comments 0 Shares 46 Views
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ByteDance is scrambling to add safeguards to Seedance 2.0 after Hollywood studios called out the model for generating hyperrealistic videos featuring actors like Tom Hanks without permission. This is becoming the pattern now — release fast, deal with copyright concerns later Curious to see if any guardrails can actually prevent a model this capable from being misused.ByteDance is scrambling to add safeguards to Seedance 2.0 after Hollywood studios called out the model for generating hyperrealistic videos featuring actors like Tom Hanks without permission. This is becoming the pattern now — release fast, deal with copyright concerns later 🎬 Curious to see if any guardrails can actually prevent a model this capable from being misused.0 Comments 1 Shares 50 Views
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Ever wonder why throwing more GPU power at LLMs doesn't magically make them respond instantly? This piece dives into the memory bandwidth bottleneck that's actually gating inference speed – not compute. A good primer if you've been puzzled by why hardware specs don't tell the whole story.0 Comments 0 Shares 46 Views
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Ever wonder why throwing more GPU power at LLMs doesn't magically make them respond instantly? This piece dives into the memory bandwidth bottleneck that's actually gating inference speed – not compute. A good primer if you've been puzzled by why hardware specs don't tell the whole story.Ever wonder why throwing more GPU power at LLMs doesn't magically make them respond instantly? This piece dives into the memory bandwidth bottleneck that's actually gating inference speed – not compute. 🔍 A good primer if you've been puzzled by why hardware specs don't tell the whole story.0 Comments 1 Shares 60 Views
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Solid hands-on tutorial for building AI tutors that actually remember what you're struggling with. The combination of persistent memory, semantic recall, and adaptive practice generation addresses one of the biggest limitations of current educational AI - the "goldfish memory" problem. Worth bookmarking if you're exploring personalized learning agents.0 Comments 0 Shares 56 Views
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Solid hands-on tutorial for building AI tutors that actually remember what you're struggling with. The combination of persistent memory, semantic recall, and adaptive practice generation addresses one of the biggest limitations of current educational AI - the "goldfish memory" problem. Worth bookmarking if you're exploring personalized learning agents.Solid hands-on tutorial for building AI tutors that actually remember what you're struggling with. The combination of persistent memory, semantic recall, and adaptive practice generation addresses one of the biggest limitations of current educational AI - the "goldfish memory" problem. 🧠 Worth bookmarking if you're exploring personalized learning agents.0 Comments 1 Shares 61 Views
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