Learning from Trials and Errors Reflective Test-Time Planning for Embodied LLMs
GENERATIVE AI
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Query-Focused Memory-Aware Reranker for Long Context
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Query-focused and Memory-aware Reranker for Long Context Processing
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New Edition: Learn Generative AI, RAG, and AI Agents
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New updated 2nd Edition, by @keithbourne v/ @PacktDataML "Unlocking Data with Generative AI and RAG — Learn AI Agent Fundamentals with RAG-powered Memory, Graph-based RAG, and Intelligent Recall" Get the book here: http://
amzn.to/49zsIkb -
New book: Agentic Architectural Patterns for Multi-Agent AI Systems
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New release from @PacktDataML @PacktPublishing at http://
amzn.to/3MaHy8T "Agentic Architectural Patterns for Building Multi-Agent Systems: Proven design patterns and practices for GenAI, agents, RAG, LLMOps, and enterprise-scale AI systems" 𝕋𝕒𝕓𝕝𝕖 𝕠𝕗 ℂ𝕠𝕟𝕥𝕖𝕟𝕥𝕤: -
News anchors now explain language model distillation better than experts
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Even news anchors now know what language model distillation is. In fact, they explain it better than I do Thanks to Anthropic 😀
→ View original post on X — @skathirmani, 2026-02-25 13:08 UTC
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Creativity through constraint and surprise
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Let me tell why this works… Creativity = constraint + pressure + surprise. Generic prompts remove all three. This structure injects all three simultaneously. Here.. you are not asking the LLM to be creative, you're building a box so specific that the only way out is through
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Why ‘Be Creative’ Fails in AI
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First, understand WHY "be creative" fails. AI creativity is probabilistic. It defaults to the most statistically common answer. "Be creative" has no constraints.
No constraints = no creative pressure.
No pressure = average output. The fix isn't less structure. It's MORE of the -
Framework for AI Creativity
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Asking AI to "be creative" is the laziest prompt you can write. And it produces the laziest output. After 3 years of daily ChatGPT use, I cracked the structure that actually unlocks original, unexpected, usable creative work. Here's the exact framework
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The Hidden Truth Behind 2026’s Massive Context Windows
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Everyone's bragging about 200k, 1M, even 10M token context windows in 2026. Nobody's talking about what actually happens inside them. I just fell down this rabbit hole and I can't stop thinking about it: A new paper published January 2026 tested hundreds of thousands of data
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40 years of code: Generative AI, time-saving but errors
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Dear Rafik, I've been coding for 40 years, I'm 52 years old and I started at 12. I use all generative AI coding tools daily, I admit it's fantastic, I save an incredible amount of time, it's undeniable, but they all code with errors, I have to go over everything,