Read All the Good News That's Fit to Print in this week's Weekly Dose from @notboringco
. This is one of the wildest weeks in recent memory, so we added seven Extra Doses for not boring world members:
MACHINE LEARNING
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Weekly Dose: AI and Tech News Roundup This Week
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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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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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Rapid progress from seven-fingered hands to cinematic movies
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Yeah, we're in the black and white TV era of this new form of media. It'll improve; it'll just take time. It's not much time, either. You know, 24 months ago, the models could only create hands with seven fingers; now they're creating cinematic movies and things like that. In
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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
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Architecting AI Software Systems: A Guide to Scalable Integration
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"Architecting AI Software Systems: Crafting robust and scalable AI systems for modern software development" at http://
amzn.to/4oMi9Ag v/ @PacktDataML 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Learn to integrate AI with traditional software architectures, enabling architects to design -
New Edition of Graph Machine Learning Book Released
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2nd Edition — now at http://
amzn.to/45Y3LyI v/ @PacktDataML Graph Machine Learning — Latest advancements in Graph Data to build robust #MachineLearning algorithms 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Master new graph ML techniques through updated examples using PyTorch Geometric and -
Resource for Developing and Debugging Machine Learning Models
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Develop and Debug high-performance, low-bias, and explainable #MachineLearning and #DeepLearning Models with #Python : http://
amzn.to/3u2JiIB by @AliMLearning via @PacktDataML —————
#DataScientist #DataScience #AI #XAI #ML #PyTorch -
Guide to Building Custom RAG Pipelines
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RAG-Driven #GenerativeAI — Build custom Retrieval Augmented Generation pipelines: http://
amzn.to/3MWnIek v/ @PacktDataML ——
#AI #MachineLearning #DataScience #GenAI #LLMs
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𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Implement RAG’s traceable outputs, linking each response to its source