188 stories
I built MaRN (Mapping Networks), a PyTorch library that lets you optimize a compact latent representation instead of directly training every model parameter.
TL;DR Agentic workloads change the traffic an inference server sees. Unlike single-turn chat, an agent session can involve a large initial prefill, repeated model calls, and subagents running in parallel,... The post Session-Aware Agentic Inference with NVIDIA Dynamo appeared first on PyTorch.
AI agents can now write CUDA kernels that outperform PyTorch—but proving those speedups are real is the harder problem. I put them to the test on an NVIDIA DGX Spark and found that benchmark design matters just as much as the code.
TL;DR Spyre becomes a native PyTorch device by connecting PyTorch’s existing device, allocator, stream, and compiler abstractions through torch-spyre to the Spyre runtime and firmware. PrivateUse1 gives Spyre a real... The post Building Spyre as a Native PyTorch Device appeared first on PyTorch.
You don't need a massive GPU cluster to learn how modern frontier AI works. In our new video on the freeCodeCamp.org YouTube channel, you will build, pre-train, and fine-tune a working 25-million para
Liquid AI d1 API review covering $0.04/M hosted pricing, d1-3B vs d1-omni-600M, licensing, hardware, and local deployment trade-offs.
Today, we release two open decision models in our d1 decision model family: d1-3B and d1-omni-600M (experimental).
If you’re more interested in asking why a model works than just using it off the shelf, a career as an AI research scientist might be the right fit for you.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them.
I put a physics-informed neural network up against a plain finite-difference solver twice: once in 1D and once in 5D. The winner changed. The post When Do PINNs Beat Classical Numerical Methods? A 1D vs 5D Experiment appeared first on Towards Data Science.
This is the final post in a four-part series about post-training. If you missed them, check out part 1, part 2, and part 3. Time to get your hands dirty! I’ll take you through implementing the key pieces of the classic ChatGPT pipeline: SFT, then reward model training, then PPO.
Kandinsky 6.0 is an open-source text-to-video model that runs on consumer GPUs. Here's how to install it locally or use it via Fal.ai.
Learn how to administer Amazon SageMaker HyperPod through Amazon SageMaker Unified Studio while preserving cluster governance. This post shows platform teams how to design infrastructure boundaries, govern access, allocate shared capacity, and operate HyperPod consistently across the organization,…
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass Touch Grass Bingo: Nature Exploration Powered by OpenCLIP & Render 🌿 What I Built Modern developers and students often spend 12+ hours a day behind glowing monitors, debugging code and attending virtual…
<ul> <li>13.0 - Raise minimal supported SonarQube Server version to 2025.1. 23 new rules for Java. 5 new rules for JS/TS. 1 new rule for C#. Fewer FPs for PHP and JS/TS.
Two copies of one small AI model keep a remote machine in sync with the cloud, with no constant streaming. A beginner-friendly world model tutorial in PyTorch. The post How to Make a Cloud Read a Drone's Mind (and Cut Data Usage by 94%) appeared first on Towards Data Science.
This article covers building robust Python AI libraries specifically, Python AI SDK best practices, and what separates a production-ready AI package from one that only survives in its own demo.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch. - Release Diffusers 0.41.0: QwenImage 2.1 pipeline and more · huggingface/diffusers
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