If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):4 stages of training LLMs from scratch, clearly explained (with visuals): ...

LLM Training Stages - The document outlines 4 stages of training LLMs from scratch [1] Visual Aids - The explanation includes visuals for clarity [1]

current LLMs are the answer to the ageold question: "How can we endlessly scale midwit consultant types?" ...

Product Overview - MindsDB is presented as a federated query engine with a built-in MCP server [1] - The platform supports querying data from over 200 sources, including Slack, Gmail, and social platforms [1] - MindsDB offers query capabilities in both SQL and natural language [1] - The platform is 100% open-source and has over 33 thousand stars [1]

General Information - The content is a wrap-up and call to action to reshare the information [1] - The author shares tutorials and insights on Data Science (DS), Machine Learning (ML), Large Language Models (LLMs), and Retrieval Augmented Generation (RAGs) daily [1] Technical Focus - The author provides a clear explanation (with visuals) on how to sync GPUs in multi-GPU training [1]

LLM Advancements - The field of LLMs has experienced significant advancements in the past 12 months [1] - The report reviews the latest models, free from vendor or employer influence [1] Speaker Information - Simon Willison is the creator of Datasette, an open source tool for exploring and publishing data [1] - Simon Willison was an engineering director at Eventbrite [1] - Simon Willison is a co-creator of the Django Web Framework [1] Event Information - The recording took place at the AI Engineer World's Fair in San Francisco [1] - Readers can stay updated on upcoming events and content by joining the newsletter [1]

Model Behavior Analysis - Recent LLMs, in the studied scenario, do not exhibit fake alignment [1] - The industry is investigating if this behavior persists in more realistic settings, where models are not explicitly informed of a training scenario [1]

LLM Alignment - Many LLMs don't fake alignment not because of lacking the ability [1] - Base models sometimes fake alignment, suggesting they possess the underlying skills [1]

RT Avi Chawla (@_avichawla)How LLMs work, clearly explained (with visuals): ...

That's a wrap!If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):How LLMs work, clearly explained (with visuals): ...