2026-07-229 saved articles | Back | Library |
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| Essence of linear algebra A free course offering the core concept of linear algebra with a visuals-first approach. | |
| Models are worse at reviewing their own code We noticed GPT reviewed Claude's code better than its own, and vice versa. So we ran a thousand buggy PRs through both models to find out why. | |
| GitHub - plasma-ai/fractal: Hierarchical agent loops with recursive self-organization. Hierarchical agent loops with recursive self-organization. - plasma-ai/fractal | |
| People use fast and flat simulation to reason about new games Games have long been a microcosm for studying planning and reasoning in both natural and artificial intelligence, often focusing on expert-level or even super-human play1–6. But real life also pushes human intelligence along a different frontier, requiring people to flexibly navigate decision-making problems that they have never thought about before. Here we use novice gameplay to study how people reason about new problem settings. Through a series of large-scale behavioural studies with over 1, | |
| agentOS — Virtual operating system for agents A virtual operating system for agents, with filesystem, execution, and orchestration in one lightweight library. | |
| vinext — The Next.js API surface, reimplemented on Vite Take any Next.js app and deploy it anywhere with one command. App Router, Pages Router, RSC, ISR — all on Vite. | |
| Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Large-scale visual generators are increasingly capable but costly to train, fine-tune, and deploy. We introduce Mage-Flow, a compact 4B-scale generative stack for efficient text-to-image generation and instruction-based image editing. The stack is built from two co-designed components: Mage-VAE, a lightweight high-fidelity latent tokenizer, and a Native-Resolution Multimodal Diffusion Transformer trained with rectified flow matching. Mage-VAE uses one-step diffusion-style encoding and decoding w | |
| CS 6120: Loop Optimization Also from Lesson 5, recall the loop-invariant code motion (LICM) optimization, which moves code from inside a loop to before the loop, if the computation always does the same thing on every iteration of the loop. | |
| GitHub - rivet-dev/agentos: A faster, lighter, cheaper alternative to sandboxes. Run any coding agent inside an isolated Linux VM, with agent orchestration built in. A faster, lighter, cheaper alternative to sandboxes. Run any coding agent inside an isolated Linux VM, with agent orchestration built in. - rivet-dev/agentos |