Solid breakdown, Sumanth. I'm playing with MaxClaw, so far so good.
@akshay_pachaar
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QueryWeaver GitHub Project Promotes AI-Related Categories
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QueryWeaver GitHub: (don't forget to star )
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Open-Source Text-to-SQL Solution Tackles LLM and Schema Issues
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Finally! A Text-to-SQL solution that actually works!
— Akshay 🚀 (@akshay_pachaar) 2 mars 2026
(and it's open-source)
When Text-to-SQL doesn’t work, we often blame the LLM or poor prompt engineering.
But the real issue is usually the schema.
Let me explain:
You ask: “Which publishers have received royalty payments… pic.twitter.com/OCa7S8Z3v0Finally! A Text-to-SQL solution that actually works! (and it's open-source) When Text-to-SQL doesn’t work, we often blame the LLM or poor prompt engineering. But the real issue is usually the schema. Let me explain: You ask: “Which publishers have received royalty payments
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Understanding Temperature in AI Models: Beyond Creativity vs. Determinism
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Great breakdown! One thing worth adding: temperature isn't just about creativity vs. determinism. It fundamentally reshapes the probability distribution over the entire vocabulary. A practical tip: instead of jumping straight to high temperature for 'creativity,' try
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The Evolution of AI Agents: From RAG to Memory-Based Systems
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RAG was never the end goal.
— Akshay 🚀 (@akshay_pachaar) 1 mars 2026
Memory in AI agents is where everything is heading. Let me break down this evolution in the simplest way possible.
RAG (2020-2023):
– Retrieve info once, generate response
– No decision-making, just fetch and answer
– Problem: Often retrieves… pic.twitter.com/nU36jH3yVMRAG was never the end goal. Memory in AI agents is where everything is heading. Let me break down this evolution in the simplest way possible. RAG (2020-2023): – Retrieve info once, generate response
– No decision-making, just fetch and answer
– Problem: Often retrieves -
Cognee AI Tool Supports OWL Ontologies for Domain-Specific Memory
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I have been using Cognee for a few weeks now. One thing I like about Cognee is that it also supports OWL ontologies for domain-specific memory. You can pass an ontology file to the same cognify method you mentioned here in the post and it'll structure the graph according to
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Insights and Tutorials on LLMs, AI Agents, and Machine Learning
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If you found it insightful, reshare with your network.
— Akshay 🚀 (@akshay_pachaar) 28 février 2026
Find me → @akshay_pachaar ✔️
For more insights and tutorials on LLMs, AI Agents, and Machine Learning!https://t.co/zXfH6v9gfyIf you found it insightful, reshare with your network. Find me → @akshay_pachaar For more insights and tutorials on LLMs, AI Agents, and Machine Learning!
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Fixing a Major Blind Spot in HuggingFace’s LLM Fine-Tuning Skill
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I just fixed a major blind spot in HuggingFace's fine-tuning skill!
— Akshay 🚀 (@akshay_pachaar) 28 février 2026
HuggingFace released a skill you can plug into Claude or any coding agent that lets you fine-tune open-source LLMs with plain English.
The agent handles GPU selection, job submission, monitoring, and pushes the… pic.twitter.com/vjNydrkap4I just fixed a major blind spot in HuggingFace's fine-tuning skill! HuggingFace released a skill you can plug into Claude or any coding agent that lets you fine-tune open-source LLMs with plain English. The agent handles GPU selection, job submission, monitoring, and pushes the
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YOLO26: A Faster, NMS-Free AI Model for Real-Time Object Detection
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Real-time object detection will never be the same.
— Akshay 🚀 (@akshay_pachaar) 28 février 2026
Traditional YOLO needs NMS to remove duplicate boxes; it's slow and inconsistent.
YOLO26 skips it entirely: single-pass predictions, faster inference and up to 300 detections per image.
Download model: https://t.co/vI1ZyYyEzM https://t.co/tRd6B3L758 pic.twitter.com/u53I4HbmL9Real-time object detection will never be the same. Traditional YOLO needs NMS to remove duplicate boxes; it's slow and inconsistent. YOLO26 skips it entirely: single-pass predictions, faster inference and up to 300 detections per image. Download model: http://
platform.ultralytics.com/ultralytics/yo
lo26?utm_source=infl&utm_medium=general&utm_campaign=yolo26&utm_term=ap
…