Poolside Releases Laguna S 2.1, an Open-Weight Agentic Coding Model Punching Above Its Weight Class on SWE-Bench Multilingual
Poolside has released Laguna S 2.1, a 118B-parameter open-weight model built for agentic coding. It is a Mixture-of-Experts (MoE) model with 8B activated parameters per token. It supports a context window of up to 1M tokens in both thinking and no-thinking modes. The weights are on Hugging Face under an OpenMDW-1.1 license, and the model is small enough to run on a single NVIDIA DGX Spark. On long-horizon coding benchmarks, Laguna S 2.1 holds its own against models several times its size, in
Poolside has released an open-weight model designed for coding tasks that uses a sparse architecture, meaning only a fraction of its total parameters activate per step, allowing it to perform comparably to much larger models while remaining cheaper to run. The model scores competitively on coding benchmarks against larger closed and open models, ranking first among open models with disclosed sizes on some benchmarks. It can run on a single GPU at lower precision levels and was trained in under nine weeks. The model includes a "thinking mode" that enables it to spend more computational effort on complex problems, though this increases token usage substantially.
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Google DeepMind just mathematically verified key parts of Signal
Google DeepMind researchers used agentic AI to mathematically prove, or “formally verify,” a number of the Signal protocol’s key cryptographic guarantees—a landmark development for the widely used cryptography and AI itself. Conducted as a sort of proof-of-concept project in just four weeks, the work is significant in two ways. It serves as further independent validation of the cryptography that protects massive quantities of the world's communications on platforms like the Signal app, Google Me
Baidu’s ERNIE Evolve Automated Research System Beats NanoChat and NanoGPT Records
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AI coding agents still need human cleanup on nearly three out of four tasks in a real-world test
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The gap between open and closed AI models in cyber capabilities keeps shrinking
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