The Future Of Travel: AI, Chatbots, VR And Agents #Travel and #hospitality are entering a period of rapid transformation as #AI, #automation, and immersive technologies reshape how journeys are planned, experienced and delivered. This article explores the key #technology
GENERATIVE AI
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AI Search Behavior Study Reveals Interpretation Gaps
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He publicado un episodio en @ivoox
: "#1069: La IA casi nunca busca exactamente lo que el usuario escribe (un estudio lo confirma) #podcast -
Minimax M2.5 Launch: Advanced AI for Productivity Workflows
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Minimax M2.5 is live on Poe! The new Minimax M2.5 is designed for real world productivity, with a focus on planning‑driven, multi‑step execution across complex digital workflows. It excels at coding, cross‑tool context switching, and agent style task coordination. Also, it
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Peter joins OpenAI: Strategic competition between OpenAI and Anthropic intensifies
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这次 Peter 加入 OpenAI，热闹之外，几个值得思考的点： 1. 从最开始的 Clawdbot 到 Moltbot 再到 OpenClaw，名字就可以看出来，Peter 开始是 A 社模型的粉丝 ，到现在去 OpenAI 背后的思考。 2. OpenAI 和 A 社之间，现在不只是模型在打，社媒、关注度、开源也在打。可以理解为，OpenAI
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Linus admits all clips will be AI, fears doomer label
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ohhh for sure, reality is all of the clips will be AI even the creator, but I can’t say that, because then people think I’m a doomer
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Speculation on Model Release Strategy and Feature Deployment
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The clawdbot —> open claw rename foreshadowed it all. Zuck must not be too happy. And interesting that Anthropic didn’t even make a play. So what does this mean? I suspect new functionality keeps coming to open claw first – and the best stuff graduates to chatgpt proper. A
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Open-source multimodal RAG framework discovery and integration
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Ever since I started working on Memory, I've been seeing RAG products every day. Discovered a one-stop RAG framework, open-source, MIT licensed. This library can be considered a multimodal superset based on LightRAG. Building on the LightRAG architecture, it provides a
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Moonshot’s Ultra-Sparse Approach Struggles With Logical Reasoning
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@zephyr_z9 On the topic of Moonshot affording compute, there's a risk… I think the ultra-sparse approach is failing to handle logical reasoning and problem solving like frontier models. Made a new benchmark digging deeper:
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DeepSeek V4 Open Models Lag Behind Frontier AI
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@teortaxesTex About DeepSeek V4 being able to compete with the frontier, I made a new benchmark that suggests open models (particularly the new ultra-sparse ones) are qualitatively worse at problem solving and logical reasoning:
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Open Weights Model Performance: MoE Sparsity Challenges
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I will add the remaining two (?) models rumoured for release early next week and finalize it with a blog post… In the meantime, if you have any theories why open weights struggle (my theory is that it's MoE/sparsity induced) — let me know!