April 2026

Xiaomi MiMo team publicly released two new models: MiMo-V2.5-Pro and MiMo-V2.5. The benchmarks, combined with some genuinely striking real-world task demos, make a compelling case that open agentic AI is catching up to the frontier faster than most expected. Both models are available immediately via API, and priced competitively. What is an Agentic Model, and Why Does It Matter? Most LLM benchmarks test a model’s ability to answer a single, self-contained question. Agentic benchmarks test something much harder […]

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Most AI agents today have a fundamental amnesia problem. Deploy one to browse the web, resolve GitHub issues, or navigate a shopping platform, and it approaches every single task as if it has never seen anything like it before. No matter how many times it has stumbled on the same type of problem, it repeats the same mistakes. Valuable lessons evaporate the moment a task ends. A team of researchers from Google Cloud AI, the University of Illinois […]

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There’s a pattern playing out inside almost every engineering organization right now. A developer installs GitHub Copilot to ship code faster. A data analyst starts querying a new LLM tool for reporting. A product team quietly embeds a third-party model into a feature branch. By the time the security team hears about any of it, the AI is already running in production — processing real data, touching real systems, making real decisions. That gap between how fast AI […]

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In this tutorial, we explore the implementation of OpenMythos, a theoretical reconstruction of the Claude Mythos architecture that enables deeper reasoning through iterative computation rather than increased parameter size. We build and analyze models using both GQA and MLA attention mechanisms, examine memory efficiency through KV-cache comparisons, and validate stability via the spectral properties of the recurrent update. We then train the model on a structured parity task and investigate how increasing loop depth at inference improves performance […]

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I’m working on a startup right now and from the outside it probably looks like I’m doing fine, but internally it feels like I’m always late to something late to trends late to execution and I can’t tell if that feeling is actually useful (like pushing me to move faster) or if it’s just messing with my ability to focus for people who’ve been through this, does that ever go away? or do you just learn how to […]

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Streaming Continual Learning (CL) typically converts a continuous stream into a sequence of discrete tasks through temporal partitioning. We argue that this temporal taskification step is not a neutral preprocessing choice, but a structural component of evaluation: different valid splits of the same stream can induce different CL regimes and therefore different benchmark conclusions. To study this effect, we introduce a taskification-level framework based on plasticity and stability profiles, a profile distance between taskifications, and Boundary-Profile Sensitivity (BPS), […]

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Continual learning (CL) studies how models acquire tasks sequentially while retaining previously learned knowledge. Despite substantial progress in benchmarking CL methods, comparative evaluations typically keep the fine-tuning regime fixed. In this paper, we argue that the fine-tuning regime, defined by the trainable parameter subspace, is itself a key evaluation variable. We formalize adaptation regimes as projected optimization over fixed trainable subspaces, showing that changing the trainable depth alters the effective update signal through which both current task fitting […]

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