When a manufacturing AI project underdelivers, the bottleneck is rarely the model. It is usually the data the model never had.
MACHINE LEARNING
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LangSmith Fleet Template: TavilyAI Competitor Research Agent
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LangSmith Fleet template spotlight: @TavilyAI Competitor Research Researches companies and summarizes findings in a concise report. A research agent that takes a list of company names, digs deep across the web, and drops findings straight into Slack threads. Try it today:
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Most AI Agents Fail in Production Because They’re Built Backward
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Most AI Agents Fail in Production Because They’re Built Backward! #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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NVIDIA AI for Media: Synthetic Video Detector and RTX Upscaling
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NVIDIA AI for Media is bringing real-time AI performance into live and on-demand media workflows. Synthetic Detector delivers up to 92% accuracy with latency as low as 22 ms for AI video authenticity checks. RTX Super Resolution and Frame Generation upscale
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AI Engineering Toolkit: 100+ Libraries for LLMs, RAG, AI Agents
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AI Engineering Toolkit! I have curated a list of 100+ libraries and frameworks for training, fine-tuning, building, evaluating and deploying LLMs, RAG, and AI Agents. Categories of LLM Libraries include: • Vector Databases – Store and retrieve embeddings efficiently.
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Paper’s artifact claim: editable skill files, not agent action, behavioral fidelity frontier.
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Right, that gap is the paper's own point. It claims an artifact (editable skill files), not that the agent acts on the judgment, and calls it the behavioral fidelity frontier, with no fidelity eval.
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GLM 5.1 outperforms Kimi 2.6, Composer 2.5 smarter but with RL-fried issues
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A note about why GLM 5.1 over Kimi 2.6. I found the former to be more capable on domains I'm working on, significantly so. Composer 2.5 seems smarter than Kimi, but exhibits RL-fried behavior, which causes much friction in interactive coding…
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Learn AI Engineering: 435 Lessons, 320h, Python, Rust, MCP, Free
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Learn AI engineering from scratch with this repository: → 435 lessons
→ 320 hours of content
→ Python, TypeScript, Rust…
→ Prompts, skills, agents, and MCP servers Practical exercises in each lesson
100% open source
Free Link below -
Google I/O Conversation on Gemma, Open Models, and AI Future
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At @Google I/O, I sat down with @osanseviero and @DynamicWebPaige from Google DeepMind to talk about Gemma, open models, AI Studio, on-device AI, sovereign AI and the future of AI development.
— Chubby♨️ (@kimmonismus) 2 juin 2026
A great conversation on how building with AI is becoming more open, local and… pic.twitter.com/Wk0rU5ZUMjAt @Google I/O, I sat down with @osanseviero and @DynamicWebPaige from Google DeepMind to talk about Gemma, open models, AI Studio, on-device AI, sovereign AI and the future of AI development. A great conversation on how building with AI is becoming more open, local and
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AI is a process: 8 steps for real value
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AI isn’t magic. It’s a process. 8 steps:
define problem
collect/prepare data
choose model
train
evaluate
fine-tune
deploy
ensure ethics & safety Real value comes from running this loop well. #AI #MachineLearning #DataScience #ResponsibleAI