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Search and recommendation systems increasingly need to return a set of results, not one best match. A query like ‘camping gear’ should return a tent, a sleeping bag, a stove, and a headlamp. It should not return 10 near-identical tents. Google Research has introduced Retrieve-for-Train (R4T) for this problem. The framework uses reinforcement learning (RL) […]
Nunchux AI has released VC-Attention, a training-free low-bit attention kernel built for video Diffusion Transformers (DiTs). It targets 2 problems at once: value quantization error and a slow softmax stage. Why Attention is the Video Bottleneck Video DiTs flatten a clip into 1 sequence of spatiotemporal tokens and run full self-attention at every layer. A
Computational papers ship code that readers must clone, install, configure and debug. That cost keeps useful methods locked inside PDFs. A Stanford team led by Jiacheng Miao and James Zou proposes a fix. Paper2Agent was published in Nature on 16 September 2026. It converts a paper and its codebase into a Model Context Protocol (MCP)
Prior Labs has released TabPFN-3.5, the newest version of its tabular foundation model. It predicts on a table in a forward pass, with no per-dataset training or tuning. Prior Labs reports first place across 7 tabular benchmarks. A separate demonstration shows it beating the winning solution of a famous 2015 Kaggle competition. Deployable? Yes, with
In this tutorial, we work through the cuDNN Frontend‘s graph API from below the framework: we describe a computation as a graph of operations, let cuDNN pick an engine to run it, and then take control of that choice ourselves. Every kernel we build here is expressed the same way: we declare tensors by their
Inside NVIDIA’s cuDNN Graph API: Fusion, Autotuning, and Plan Reuse with cuDNN Frontend Read More »
Google has introduced Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, its most advanced live dialogue models to date. Both are native speech to speech models built for real time voice agents. They extend the Gemini Audio family that Google expanded last month with Gemini 3.5 Transcribe. The release targets a specific gap: voice
Backpropagation is a global algorithm: a forward pass, then a backward pass, then a weight update, each locked behind the previous one. Brains have no known mechanism for that kind of network-wide phase locking, which is why local-learning alternatives such as predictive coding (PC) keep drawing research interest. Sakana AI researchers propose Augmented Lagrangian Predictive
Robot developers do not have one compute problem. They have 3. A policy is trained on GB200 or H100 clusters, tested in Isaac Sim on RTX GPUs, then validated on a Jetson mounted inside a real robot. Each tier has its own cluster, its own scheduler, and its own glue scripts. NVIDIA OSMO is NVIDIA’s
On September 12, 2026, Anthropic CEO Dario Amodei published a writeup ‘We Must Pace the Frontier’. Its core message is blunt: ‘We must slow the pace at which we improve the capabilities of AI models.’ Within hours, OpenAI’s Sam Altman and xAI’s Elon Musk endorsed it. The next day, Microsoft CEO Satya Nadella welcomed ‘deliberate
In this tutorial, we build an end-to-end hierarchical Neural Radiance Field (NeRF) using JAX, Flax, Optax, and the volume-rendering primitives provided by jax3d. We first construct a synthetic multi-view dataset from an analytic scene containing volumetric geometry and view-dependent radiance, using sample_along_rays and volume_rendering to establish the forward rendering process. We then implement a NeRF
