Jules now supports AGENTS md file! So it can use information from this file in your repository as an additional context for coding tasks.
CODE
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Embodied Web Agents: Bridging Physical-Digital Realms for Real-World Tasks
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https://t.co/63LYHHBiEV pic.twitter.com/fNffHwnsN0
— AI Breakfast (@AiBreakfast) 20 juin 2025Meet Embodied Web Agents that bridge physical-digital realms. Imagine embodied agents that can search for online recipes, shop for ingredients and cook for you. Embodied web agents search internet information for implementing real-world embodied tasks. All data, codes and web
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Property Inference Advances in Machine Learning Research
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yeah, agree that that's a nice relaxation of this problem. this work focuses on property inference:
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PyTorch Training Resilience During Infrastructure Failures
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the model keeps on training even when the underlying infra keeps failing….out-of-the-box PyTorch
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Supervisor Worker Pattern: Coordinating Multiple Specialized AI Agents
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The Supervisor Worker pattern is a powerful workflow design where a supervisor agent coordinates multiple specialized worker agents to complete complex tasks. Full walkthrough https://
youtu.be/TbZaj5SZcbM?si
=Zig4v9mmvji2wr3v
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Discrete Text Optimization Challenges in Language Models
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you're right that it's the discreteness of text that makes this problem extremely hard but also the problem you're imagining requires optimizing over optimization processes, which is also very hard what you're describing sort of works for images, e.g. this
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Obfuscating AI Models While Maintaining Performance
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yeah. people will start finding ways to obfuscate them without harming performance
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AdamW Weight Decay Obfuscation Effects on Neural Networks
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a random detail that I found cool is that AdamW seems to "obfuscate" weights a bit better than Adam or vanilla SGD guessing this is bc weight decay does something nonlinear during optimization, which decreases the amount of information available in weights