yeah this 2023 babyagi diagram was on point 🙂 thx! seems like if you keep going meta, you'll end up with something like activegraph, lots of ppl seem to have been circling similar ideas
RESEARCH
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Common Misconceptions About How LLMs Actually Work
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Most people, including really accomplished people, don't have an accurate mental model of how LLMs operate (and why would they?) You see this in wide beliefs that AI is just copying from known sources, or that it only produces average answers, or that it can't generate new ideas
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Maxime Labonne recommends Rasbt’s Build a Large Language Model
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Thanks! I'd recommend @rasbt
's Build a Large Language Model (From Scratch) -
Ideogram Releases Latest v4 Image Model with Open Weights
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Ideogram just released their latest and best v4 image model open weights
— Hugging Face (@huggingface) 3 juin 2026
State of the art and open weights go well together 🤗
Model: https://t.co/DUcL7BBH7D
Demo: https://t.co/fIc26kF6Ky https://t.co/aw1S88Vx00 https://t.co/iD0FWyIgVsIdeogram just released their latest and best v4 image model open weights State of the art and open weights go well together Model: https://
huggingface.co/ideogram-ai/id
eogram-4-nf4
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Demo: https://
huggingface.co/spaces/multimo
dalart/ideogram4
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New Gemma 4 12B available on Huggingface under Apache 2.0 license
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GOOGLE : A new Gemma 4 12B is now available on Huggingface under Apache 2.0 license! > Built with the same multimodal functionality as Gemma 4 E2B and E4B (text, audio, image, and video inputs), it brings native audio and vision understanding directly to local environments
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Develop Physical AI Reasoning, World, and Action Models with NVIDIA
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Develop Physical AI Reasoning, World, and Action Models with NVIDIA! #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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NVIDIA presents three physical AI papers including GraspGen-X at CVPR2026
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This week at #CVPR2026, NVIDIA Research is presenting three papers across physical ai that offer groundbreaking solutions for training at scale across diverse applications:
— NVIDIA (@nvidia) 3 juin 2026
→ GraspGen-X: the first foundation model for zero-shot grasping, trained on billions of simulated grasps… pic.twitter.com/IJlIHR4olXThis week at #CVPR2026, NVIDIA Research is presenting three papers across physical ai that offer groundbreaking solutions for training at scale across diverse applications: → GraspGen-X: the first foundation model for zero-shot grasping, trained on billions of simulated grasps
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Primer on post-training reasoning data synthesis
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Nice primer on post-training reasoning data. (bookmark it) This is one of the first primers to pull the scattered post-training reasoning-data literature into one place, synthesizing over 150 public studies and system reports that previously lived across dataset papers, RL
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New paper: Image generators cheat with near-duplicate outputs
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Image generators look impressive but quietly cheat. They score well on FID by producing near-duplicate outputs. The catch is mode collapse hiding behind a clean number. Coverage of the real data distribution suffers in silence. A new paper introduces the Recursive Token
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Visual Para-Thinker Uses Parallel Reasoning to Overcome AI Visual Plateaus
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Why do AI models hit a wall in visual reasoning? Researchers from Zhejiang University, Hunan University, and Xiaomi introduce Visual Para-Thinker. It uses parallel divide-and-conquer reasoning to avoid sequential thinking plateaus. Outperforms on V*, CountBench, RefCOCO, and