Temporal awareness is another game-changer. Agentic memory doesn't just look for "keywords"; it understands time. It prioritizes recent, relevant strategies over stale, failed ones. It stops repeating the same mistakes because it "remembers" the outcome of the last attempt.
MACHINE LEARNING
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Agents Learn from Experience to Improve Memory and Performance
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Imagine Agents learn from their experiences to improve memory, retention, and task performance, just like the human brain. It distinguishes between "World Facts" and "Experiences". It's the difference between reading a map and actually driving the route.
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Training GPT-2 Grade LLMs for Under $100
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nanochat can now train GPT-2 grade LLM for <<$100 (~$73, 3 hours on a single 8XH100 node). GPT-2 is just my favorite LLM because it's the first time the LLM stack comes together in a recognizably modern form. So it has become a bit of a weird & lasting obsession of mine to train
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Token-Level Data Filtering for AI Model Capability Enhancement
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Shaping capabilities with token-level data filtering Neil Rathi, Alec Radford: https://
arxiv.org/abs/2601.21571 #ArtificialIntelligence #DeepLearning #MachineLearning -
Steering AI Thoughts: New Interpretability Pipeline Framework
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We could not just understand an AI's "thoughts," but actually steer and improve them! A massive collaborative team from HKU, Fudan, LMU Munich, Microsoft, Tencent & more presents a new playbook. They reframe AI interpretability as an actionable pipeline: Locate the key
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Artificial Intelligence Improving Industrial Mixing Processes
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Artificial intelligence improving mixing processes
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @timnitgebru @oriolvinyalsml @ceobillionaire @soumithchintala @waitin4agi_ @sallyeaves @bernardmarr -
ICRA 2026 Paper Decision Notifications and Reviewer Appreciation
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Decisions on @ieee_ras_icra #ICRA2026 papers are trickling out…Thanks to program chairs, committees, and reviewers for completing a huge amount of reviewing right on schedule.
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Recursive Self-Improvement: Path to Technological Singularity
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From Seed AI to Technological Singularity via Recursively Self-Improving Software Roman V. Yampolskiy: https://
arxiv.org/abs/1502.06512 #ArtificialIntelligence #RSI #Singularity -
RTL’s modular AI breakthroughs in 2026
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This isn't just academic. RTL works on: → Image classification (CIFAR-10/100)
→ Speech enhancement (3 acoustic environments)
→ Implicit neural representations (within-image specialization) The era of "one model fits all" is over. Welcome to modular, data-aware AI. Paper: -
RTL reveals semantic data structure in deep layers
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The semantic alignment is beautiful: Related classes (cat, dog, deer) share more pruning structure in deep layers. Unrelated classes (airplane, truck) stay independent. RTL doesn't just find sparse networks – it discovers the SEMANTIC STRUCTURE of your data.