ABOUT THIS FEED
AIModels.fyi is a curated resource for tracking the release of new AI models, tools, and datasets. Its Substack RSS feed provides digest-style newsletters that summarize the latest in machine learning research and open-source projects. The platform focuses on making it easier for practitioners and enthusiasts to discover and follow emerging models across natural language processing, computer vision, generative AI, and reinforcement learning. Each post aggregates relevant updates, links, and context, saving readers time compared to browsing multiple sources. The writing is concise yet informative, appealing to developers, researchers, and students who want a quick overview of cutting-edge developments. With a few posts per week, the feed is highly practical for staying on top of the rapidly expanding AI ecosystem without information overload.
- Model Highlight: Laguna S 2.1
A new heavyweight for agentic coding?
- Why force models to compute knowledge when they could just look it up?
Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models
- Why build a bigger model when you can just loop twice for twice the power?
LoopCoder-v2: Only Loop Once for Efficient Test-Time Computation Scaling
- Can an AI agent run the entire scientific method without human supervision?
Toward Generalist Autonomous Research via Hypothesis-Tree Refinement
- Why do your coding agents keep getting lost in large repositories?
SWE-Explore: Benchmarking How Coding Agents Explore Repositories
- Are you still manually fighting with LaTeX and TikZ to create publication-quality figures?
Crafter: A Multi-Agent Harness for Editable Scientific Figure Generation from Diverse Inputs
- Can your AI agent actually learn from its mistakes or just keep repeating them?
SkillOpt: Executive Strategy for Self-Evolving Agent Skills
- Can your AI agent remember your secrets without the cloud ever seeing them?
MemPrivacy: Privacy-Preserving Personalized Memory Management for Edge-Cloud Agents
- Can we build elite search agents without the massive industrial RL pipelines?
OpenSeeker-v2: Pushing the Limits of Search Agents with Informative and High-Difficulty Trajectories
- Xiaomi just open-sourced a 1T-parameter model and almost nobody noticed
MiMo-V2.5-Pro matches frontier coders on benchmarks, ships under MIT, and burns 40-60% fewer tokens per agent run - but it's 1.02 trillion parameters of MoE and you can't run it on your gaming rig.