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
LLMS
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Training AI on Amazon Reviews with Python for Natural Language Processing
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Training AI on Amazon Electronic Reviews Using #Python for Natural Language! – by – @gp_pulipaka
! JupyterLab/Jupyter Notebook WordNet, Lexical Semantic Relation Analyzer
Thesaurus, 155,000 Words
Synset 115,000, 205,000 word-Sense Pair. NLTK Library, spaCy, TextBlob -
Technical Discussion on LLM Reasoning and Architectural Iteration
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literally i didn’t say that. adding “reasoning” already borrows tools like iteration and evaluation from classical AI and isn’t a pure LLM. and the reasoning has all kinds of problem. and i didn’t say “just”; i was careful to say “basically”, suggesting an approximation.
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Debating LLM scaling versus symbolic integration for AI progress
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this is a such a muddle. (at least relative to my views) LLMs are more or less just autcomplete, but (as I have always said) they have their uses. And the real progress now is coming from adding new (symbolic) techniques to the mix, not from pure scaling.
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Critique of pure LLM architecture and the role of symbolic integration
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I love AI, it’s pure LLMs I hate. Pure LLMs *are* basically just autocomplete. Recent progress (e.g. Claude Code) doesn’t show otherwise Rather, lot of the progress in the last two years has come from *introducing* other things – mainly classic symbolic techniques and tools,
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Microsoft missed AI wave, Copilot struggles, NPUs no killer app
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Former Microsoft VP says Microsoft missed the AI wave like the internet and mobile, as Copilot scales back in Windows 11 Microsoft spent $37.5B per quarter on AI. Less than 3.3% of Microsoft 365 users pay for Copilot. OEMs stuffed NPUs into every laptop, and not a single k1ller
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IndiaAI and Meta Launch Foundational Course on LLMs for Developers
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The LLM for Young Developers: Foundational Course by IndiaAI in collaboration with @Meta , supported by @AICTE_INDIA and implemented by 1M1B introduces learners to the fundamentals of LLM for young developeers. Built to make advanced AI concepts more accessible for emerging
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50 Machine Learning Projects for Understanding LLMs and Transformers
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50 ML projects to understand LLMs — Investigate transformer mechanisms through data analysis, visualization, and experimentation: https://
amzn.to/3P8ztDt via @PacktPublishing @PacktDataML —————
#AI #GenAI #MachineLearning #DataScientist #DataScience -
Technical challenges in deploying H100 clusters for AI development
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I was recording my nanochat video when I realized that “first boot up an 8XH100 from your favorite provider!” would instantly get everyone stuck on step 1 of the video
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Notion integrates AI agents and custom code for automated workflows
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Notion quietly became a developer platform this week
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 18 mai 2026
→ Workers: deploy custom code inside Notion
→ External Agent API: connect AI agents to live data
→ Database sync for multi-step automated workflows
Your docs just became your ops layer.https://t.co/zG8Vmp2CPbNotion quietly became a developer platform this week → Workers: deploy custom code inside Notion → External Agent API: connect AI agents to live data → Database sync for multi-step automated workflows
Your docs just became your ops layer.