Why Researchers Are Excited About Mamba-3

by Shreyas Naphad — AI architecture built for long memory and efficiency

Towards AI·2h ago

Scaling Biomolecular Modeling Using Context Parallelism in NVIDIA BioNeMo

For decades, computational biology has operated under a reductionist compromise. To fit complex biological systems into the limited memory of a single GPU,... For decades, computational biology has...

NVIDIA Developer·Apr 28

Codex for (almost) everything

The updated Codex app for macOS and Windows adds computer use, in-app browsing, image generation, memory, and plugins to accelerate developer workflows.

OpenAI·Apr 16

Introducing NVIDIA BlueField-4-Powered CMX Context Memory Storage Platform for the Next Frontier of AI

AI‑native organizations increasingly face scaling challenges as agentic AI workflows drive context windows to millions of tokens and models scale toward... AI‑native organizations increasingly face...

NVIDIA Developer·Mar 16

Adobe Research Unlocking Long-Term Memory in Video World Models with State-Space Models

By combining State-Space Models (SSMs) for efficient long-range dependency modeling with dense local attention for coherence, and using training strategies like diffusion forcing and frame local...

Synced Review·May 28

Osaurus brings both local and cloud AI models to your Mac

Osaurus combines local and cloud AI models in a Mac app that keeps users’ memory, files, and tools on their own hardware.

TechCrunch AI·14h ago

Simplify Sparse Deep Learning with Universal Sparse Tensor in nvmath-python

In a previous post, we introduced the Universal Sparse Tensor (UST), enabling developers to decouple a tensor’s sparsity from its memory layout for greater... In a previous post, we introduced the...

NVIDIA Developer·Apr 22

NVIDIA NVbandwidth: Your Essential Tool for Measuring GPU Interconnect and Memory Performance

When you’re writing CUDA applications, one of the most important things you need to focus on to write great code is data transfer performance. This applies to... When you’re writing CUDA...

NVIDIA Developer·Apr 14

Accelerating Data Processing with NVIDIA Multi-Instance GPU and Locality Domains

NVIDIA flagship data center GPUs in the NVIDIA Ampere, NVIDIA Hopper, and NVIDIA Blackwell families all feature non-uniform memory access (NUMA) behaviors, but... NVIDIA flagship data center GPUs in...

NVIDIA Developer·Feb 19

Visualize and understand GPU memory in PyTorch

Hugging Face·Dec 24

mimalloc: A new, high-performance, scalable memory allocator for the modern era

mimalloc is an open-source, modern, scalable memory allocator that is a drop-in replacement for malloc and free. It is relatively small (~12K lines), with clear internal data structures, and is easy...

Microsoft Research·2d ago

Maximizing Memory Efficiency to Run Bigger Models on NVIDIA Jetson

The boom in open source generative AI models is pushing beyond data centers into machines operating in the physical world. Developers are eager to deploy these... The boom in open source generative...

NVIDIA Developer·Apr 20

Personalizing ChatGPT

Learn how to personalize ChatGPT using custom instructions and memory to get more relevant, consistent, and tailored responses.

OpenAI·Apr 10

Stable Diffusion 3.5 Models Optimized with TensorRT Deliver 2X Faster Performance and 40% Less Memory on NVIDIA RTX GPUs

In collaboration with NVIDIA, we've optimized the SD3.5 family of models using TensorRT and FP8, improving generation speed and reducing VRAM requirements on supported RTX GPUs.

Stability·Jun 12

Nyströmformer: Approximating self-attention in linear time and memory via the Nyström method

Hugging Face·Aug 2