"Building AI Agents with LLMs, RAG, and Knowledge Graphs — A practical guide to autonomous and modern AI agents" See it at http://
amzn.to/4622k2h via @PacktDataML
LLMS
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Practical Guide to Building AI Agents with LLMs and RAG
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δ-mem: Efficient Online Memory for Large Language Models
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“δ-mem: Efficient Online Memory for Large Language Models” LLMs need long-term memory, but extending context is expensive and often doesn’t mean the model actually uses the history well. What this paper did is to store past information in a tiny 8×8 associative memory state,
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Efficient LLM Pre-Training Using Token Superposition
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“Efficient Pre-Training with Token Superposition” LLM pretraining is bottlenecked by how many useful tokens you can consume per FLOP. This paper temporarily merge nearby tokens into averaged embedding bags, train the model to predict the next bag, then switch back to normal
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Building an AI-Powered File Reader using RAG and LLMs
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RAG with LLM: Creating an AI-Powered File Reader! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding
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Announcing Agentic Generative AI for Autonomous LLM Systems
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Announcing Agentic Generative AI to Build Autonomous AI Systems with LLM! @SantaClaraUniv #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless
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Advancement of Autonomous AI Cyber Capabilities at the Frontier
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How Fast is Autonomous AI Cyber Capability Advancing at the Frontier? #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux
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Scaling 48 Stack Language Model for Zero Shot Learning
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GPT XL: Scaling 48 Stack Language Model for Zero Shot Learning! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming
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User Compares Claude 4.6 and 4.7 AI Model Performance and UI
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Claude 4.6 was much better than 4.7. It used to build features without any bugs. And the UI use to be very good. 4.7 Am i the only one who feels like this? #Anthropic #vibecoding
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AI video agent automates TikTok ad creation
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Most “AI video” tools still make you be the project manager.@higgsfield_ai Supercomputer flips that. It’s a cloud-native, self-learning agent that takes a brief like “a week of TikTok ads for this product” and handles planning, model selection, and rendering across 30+… pic.twitter.com/0LBpGi1nWl
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 15 mai 2026Most “AI video” tools still make you be the project manager. @higgsfield_ai Supercomputer flips that. It’s a cloud-native, self-learning agent that takes a brief like “a week of TikTok ads for this product” and handles planning, model selection, and rendering across 30+
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Second Scaling Law: Thinking tokens boost LLM performance without plateau
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The Second Scaling Law remains undefeated. If you want better hacking (or math, or science, or crossword puzzle solving) out of an LLM, just add thinking tokens. There doesn't seem to be any plateau so far.