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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…
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Accelerating Text-to-Video Generation with Calibrated Sparse Attention
Recent diffusion models enable high-quality video generation, but suffer from slow runtimes.…
3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber
Developers and customers building production AI agents need higher token efficiency, lower…
Validating Distributed LLM Serving Benchmarks with NVIDIA srt-slurm, SLURM Recipes, Parameter Sweeps, and Pareto Analysis
In this tutorial, we explore NVIDIA’s srt-slurm framework and learn how we…
I Tried Fine-Tuning a Robot AI Model on Colab. Here Is What Worked
model sounds expensive, fragile, and hard to verify. I wanted a smaller…
Environment-free Synthetic Data Generation for API-Calling Agents
Training API-calling large language model (LLM) agents demands massive amounts of high-quality…
How Much of a Data Science Workflow Can Run on a GPU Today? Part 1: Accelerating Data Preparation
spend much of their time working with tabular data. Traditionally, these workloads…
Are Your ML Experiments a Mess? Here’s the Fix
a new model. You get decent baseline results with a simple model,…
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