3. Multi-Agent Evolve Multi-Agent Evolve (MAE) enables LLMs to self-improve their reasoning capabilities without human-annotated data through a co-evolving multi-agent framework.
MACHINE LEARNING
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Attending EMNLP2025 in Suzhou presenting multimodal LLM grounding work
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I will be heading to Suzhou soon attending #EMNLP2025 next week, presenting my work on grounding multimodal LLMs with world/cultural knowledge, https://
arxiv.org/abs/2508.07414. Email/DM open if you want to chat about the paper and other topics more broadly(multimodal LLMs x languages x -
Yann LeCun’s 1998 Gradient-Based Deep Learning Paper Milestone
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#otd in 1998 Yann LeCun submitted a paper on “gradient-based” deep learning for document recognition. It took more than a decade before the world finally warmed to neural networks: https://
bit.ly/3EzX9FD First image v/Erik Tanner & WIRED -
Efficiency and Intelligence in AI Agent Development
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By the end of testing, it was beating every open-source agent in the field and holding its own against proprietary systems built with 10x the resources. Turns out intelligence isn’t about size. It’s about how well you manage what you already know.
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AI models demonstrating reflection and iterative problem-solving
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It even knows when it’s wasting time. After 11 failed attempts in one example, it folded the entire dead end into one sentence, learned the lesson, and moved on. That’s not just optimization that’s reflection.
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Breakthrough in Scalable Reasoning Across Model Depth
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Here’s where it gets wild other models plateau after 64 steps. This one keeps getting better all the way up to 256 turns. It learns across depth, not just width the first real sign of scalable reasoning.
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New 30B Model Outperforms Larger LLMs via Innovative Memory Folding
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This small 30B model just outperformed systems over 20x larger including DeepSeek-V3.1-671B and OpenAI’s o4-mini. The secret? It doesn’t just store memory it folds it. A self-managing memory system that keeps its thoughts organized while solving 500-step problems.
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Alibaba’s AgentFold introduces a human-style memory system for web agents
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Alibaba just dropped a monster paper in agent research. It’s called AgentFold, and it basically gives web agents a human-style memory system that manages itself. Here’s why it’s wild Current agents either: ∙ keep everything (context bloat, chaos)
∙ or summarize too -
PyTorch Version of Hands-On Machine Learning Book Released
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PyTorch version of Hands-On Machine Learning Book by Aurélien Géron is just out! This was one of my favorite books when I started learning machine learning and it's nice to see it using PyTorch. Data science courses/MOOCs back then used to teach you numpy, pandas, matplotlib,
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Neural Networks Tolerate Mantissa Bit Reduction for Bandwidth Savings
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Rough thinking: neural nets are very tolerant of noise, so chopping off mantissa bits is akin to small amounts of noise. So I'd rather lose nearly all mantissa bits before losing exponent bits. So tried dropping 16 mantissa bits & model trained just fine w/ half the bandwidth.