We all know these models are trained on the internet. And the internet is full of spam, duplicates, toxic text, and personal data nobody should be memorizing. So how does any of that turn into a model that actually works? It doesn't go in raw. The data runs through a pipeline
MACHINE LEARNING
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One prompt turns AI into a technical co-founder for real apps
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Almost every "build an app with AI" attempt ends the same way: a nice-looking mockup that breaks the second you click anything real. This one prompt fixes that. It turns ChatGPT, Claude, or Gemini into a technical co-founder that builds a real, working product with you across 5
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Inverse scaling: weak model gains from harness patching runtime gaps
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Exactly the inverse-scaling point. The weak model gained most because the harness patched gaps it couldn't fix on its own. Cheaper to evolve the runtime than to scale the model, and you keep the smaller footprint at inference.
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Indian AI startups showcase global innovations at VivaTech 2026
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What does AI innovation from India look like on the global stage?
— IndiaAI (@OfficialINDIAai) 17 juin 2026
At @VivaTech 2026, founders from Flaunt, InLustro and Daten & Wissen share how they are building AI solutions in trend intelligence, workforce readiness and enterprise computer vision—and taking them to the world… pic.twitter.com/xISma4lx5UWhat does AI innovation from India look like on the global stage? At @VivaTech 2026, founders from Flaunt, InLustro and Daten & Wissen share how they are building AI solutions in trend intelligence, workforce readiness and enterprise computer vision—and taking them to the world
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Frustration with explaining ML for tabular data
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Every time someone tries to explain to me ML for tabular data. @trainxgb @tabul_ai
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AI Wardrobe App Picks Outfit Based on Weather and Schedule
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#AI Wardrobe App Picks Your Outfit Based on Weather and Schedule
— Ronald van Loon (@Ronald_vanLoon) 17 juin 2026
by @jayhxmo#ArtificialIntelligence #MachineLearning #ML pic.twitter.com/zxv2Cm6IU0#AI Wardrobe App Picks Your Outfit Based on Weather and Schedule
by @jayhxmo #ArtificialIntelligence #MachineLearning #ML -
NVIDIA’s LocateAnything speeds object detection 10x by fixing coordinate bottleneck
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🚨 @NVIDIA just dropped LocateAnything, making object detection ~10x faster by fixing one core bottleneck:
— Charly Wargnier (@DataChaz) 17 juin 2026
How the model writes coordinates.
Standard AI models do visual grounding the slow way.
They predict coordinates piece by piece: Token 1, Token 2, Token 3, Token 4 etc.… pic.twitter.com/GAyr0taCbX@NVIDIA just dropped LocateAnything, making object detection ~10x faster by fixing one core bottleneck: How the model writes coordinates. Standard AI models do visual grounding the slow way. They predict coordinates piece by piece: Token 1, Token 2, Token 3, Token 4 etc.
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Kimi K2.7 Release Advances Long Context Reasoning and LLM Efficiency
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Kimi K2.7 Release: Advancing Long Context Reasoning and LLM Efficiency! #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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A Coding Implementation on Spatial Graph Neural Networks for Urban Function Inference
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A Coding Implementation on Spatial Graph Neural Networks for Urban Function Inference Using CityGraph, OSMnx, and PyTorch Geometric! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #GeoSpatial #Mathematics #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java