We, scientists, should probably care about this, I feel.
RESEARCH
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Self-training AI models through inversion and dataset generation
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AI tutorial. Self-training can be made possible by inverting models (input becomes output) and alternating. For example, want to teach your vision model to count? Easy, take advantage of coding models and image editing to create a dataset for counting! Step 1. Use a coding
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ELT: Elastic Looped Transformers for Visual Generation
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“ELT: Elastic Looped Transformers for Visual Generation” ELT makes visual generation recurrent by looping a shared transformer block instead of stacking unique layers. Its core idea, Intra-Loop Self-Distillation, trains intermediate loop states to match the full-depth
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LifeSim: Evaluating AI Assistants Through Realistic User Simulation
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How do we truly evaluate AI assistants for long-term, real-world personalization? Researchers from Fudan University present LifeSim. It's a groundbreaking user simulator that models human cognition (Belief-Desire-Intention) in virtual environments to generate realistic,
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AI Today vs AI Coming in 2026: Future Prospects
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#AI Today vs AI Coming in 2026
by @Khulood_Almani #MachineLearning #ArtificialIntelligence #ML #MI -
AI Self-Correction Behavior During Response Generation Issues
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I've noticed there's some stochasticity around this too. I think this self-correcting behavior in the middle of a response is among my least favorite. It should resolve this kind of issue with internal reasoning.
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AI Progress Accelerates Faster Than User Adaptation Monthly
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scary how quick we adapt /fast is just not fast enough anymore the models break records monthly but aren't smart enough after a week there will truly be infinite growing demand for ai, forever
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Team Research Published in Nature Methods by Yaron Meirovitch
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The team's work is now in Nature Methods, by @YaronMeirovitch et al:
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Opus 4.7 Failure Modes Reveal AI’s Jagged Frontier
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Even Opus 4.7 is failing this one. Failure modes like this are interesting because they demonstrate the jagged frontier of AI. This same model can write a compiler from scratch, and yet it gets tripped up on small things like this.
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Jensen Huang on AI Accessibility and Cross-Industry Impact
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"AI is an incredible technology that everybody should know how to use." — Jensen Huang
— NVIDIA (@nvidia) 17 avril 2026
Across industries, AI is elevating what all of us are capable of. pic.twitter.com/l4oaQDi0J1"AI is an incredible technology that everybody should know how to use." — Jensen Huang Across industries, AI is elevating what all of us are capable of.