Files are long term memory. Context windows are working memory. That's all you need.
LLMS
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ConceptMoE: Adaptive Token-to-Concept Compression for Computing
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ConceptMoE Adaptive Token-to-Concept Compression for Implicit Compute Allocation
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Scaling Embeddings Outperforms Scaling Experts in Language Models
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Scaling Embeddings Outperforms Scaling Experts in Language Models
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Plain English as the Natural Interface for Data Tools
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Plain English to insights is the interface data tools should've had all along.
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Technology for AGI: beyond content creation
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I see, but beware, this technology is designed to eventually train AGI. For content creation it's overkill. The ultimate engineering goal here is not to create content on demand (even if that will be possible) but rather to see the limits of models for
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Understanding What Large Language Models Actually Are
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A lot of folks without much background in building LLMs misunderstand what an LLM actually is.
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LLMs as Part of Intelligent Systems
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Yes very exciting direction – an LLM can be part of a *system* that could be very helpful.
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Scobleizer on world models vs LLMs and video training
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I've been yelling and screaming that the future is world models after Oliver Cameron showed me how. World models are not LLMs (large language models). World models are trained mostly with video data or other kinds of data that isn't really text.
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LLM Engineer’s Handbook for Training and Production
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LLM Engineer's Handbook — Master the art of engineering Large Language Models #LLMs from concept to production: http://
amzn.to/4dUQrv6 v/ @PacktDataML Implement robust data pipelines and manage LLM training cycles Create your own LLM and refine with the help of hands-on -
Reasoning Models: The Next AI Leap Toward Inspectable Thinking
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Why Reasoning Models Are The Next Leap In AI #Reasoning models mark a critical step forward in #AI, moving systems from fluent prediction toward structured #thinking that can be inspected and trusted. Work coming out of #MBZUAI shows how open, sovereign models could shape the