This repository contains solutions to competitive programming problems from multiple platforms, organized by difficulty and topic. It serves as a personal learning journey and reference for ...

Anthropic has revealed a striking experiment where AI systems worked together to build a complete C compiler almost entirely on their own. Led by researcher Nicholas Carlini, the project shows how far ...

Overview Rust projects can have notoriously long compile times. One way to speed up compilation is to split a project into multiple crates in a single "workspace", where each crate can be recompiled ...

Anthropic researcher Nicholas Carlini published a blog post describing how he set 16 instances of the company’s Claude Opus 4.6 AI model loose on a shared codebase with minimal supervision, tasking ...

Claude Opus 4.6 AI agents built a Rust-based C compiler in two weeks The compiler passed 99 percent of GCC torture tests and compiled the game Doom Anthropic's AI can handle complex software ...

An Anthropic researcher's efforts to get its newly released Opus 4.6 model to build a C compiler left him "excited," "concerned," and "uneasy." It also left many observers on GitHub skeptical, to say ...

FOSDEM 2026 The creators of security software have encountered an unlikely foe in their attempts to protect us: modern compilers. Today's compilers boil down code into its most efficient form, but in ...

Days after putting SaaS companies on alert with Claude Cowork, Anthropic has now revealed that its Claude Opus 4.6 model can build a C compiler from scratch. Here is why it is a big deal. Anthropic, ...

Cursor had said last month that it had managed to build a web browser autonomously with AI agents alone. Anthropic seems to have done one better. Anthropic has announced that it tasked 16 parallel ...

This guide assumes that the project is being built on Linux* but equivalent steps can be performed on any other operating system. cmake path/to/repo/root && cmake --build . To run the tests, proceed ...

Abstract: Sparsity is becoming arguably the most critical dimension to explore for efficiency and scalability as deep learning models grow significantly larger. Particularly, pruning is a common ...