Knowledge catalogue
Storage architecture is being rewritten for artificial intelligence factories. Traditional enterprise storage was designed around workloads that scaled in relatively predictable ways. AI changes that
Artificial intelligence factory economics increasingly depend on more than access to high-performance graphics processing units. As agentic systems draw on multiple models, databases and tools, the en
arXiv:2608.24199v1 Announce Type: new Abstract: Generative simulation for surgical robotics still lacks real-time interaction. Physical-robot experiments, often involving animal or cadaver labs, are t
https://developer.nvidia.com/blog/serve-qwen3-8-2-4t-a95b-a-2-4t-parameter-model-with-configurable-reasoning-on-nvidia-gb300-nvl72/ 4k tokens per second per GPU of which there are 72. 350 tokens per s
arXiv:2608.08522v1 Announce Type: new Abstract: Event-based vision is becoming an increasingly important sensing paradigm for robotics, yet its adoption remains limited by sensor availability and the
https://github.com/NVIDIA-NeMo/Switchyard Finally an open source LLM router. An alternative to openrouter fusion and Sakana Fugu. Doesn't look like it does exactly what Sakana Fugu does according to i
River AI Inc., a startup that helps enterprises customize open-source artificial intelligence models, has raised 1.1 billion in early-stage funding. The company stated in today’s announcement that it
🐦⬛ Magpie-TTS Multilingual 🦜 Nemotron Speech Streaming EN 0.6B 🦜 Nemotron-3.5 ASR Streaming 🦜 Parakeet CTC 1.1B 🦜 Parakeet TDT 0.6B v3 🥦 NanoCodec Merged PR https://huggingface.co/nvidia/magpie_tts_m
Hello together I decided to go with 2× Radeon AI PRO R9700 GPUs (64 GB total VRAM) for my local AI server. However, I keep reading that AMD/ROCm is still not as mature as NVIDIA/CUDA when it comes to
Agentic AI is driving key technology providers to rethink the computing architecture required to run rapidly expanding autonomous systems. In response to this challenge, two leading tech companies hav
Realizing value from AI investment has become the ultimate prize for most enterprises today. This requires the ability of data and compute to work together, a key mission for the partnership between N
Artificial intelligence played a prominent role at this week’s Bio International Convention in San Diego, the largest biotech event with vendors spanning the full ecosystem of companies in this indust
Cloud-based artificial intelligence infrastructure startup TensorWave Inc. said today it has closed on a bumper 350 million Series B funding round as it strives to meet demand for an alternative to Nv
Automation startup Neura Robotics GmbH is raising a funding round worth up to 1.4 billion from a group of prominent investors. The company detailed today that the consortium includes Amazon.com Inc.,
arXiv:2509.22685v2 Announce Type: replace-cross Abstract: Fringe projection profilometry (FPP) is a high-precision structured-light sensing technique for 3D surface reconstruction, yet its practical d
arXiv:2601.20115v3 Announce Type: replace-cross Abstract: As the role of modern Graphics Processing Units (GPUs) becomes increasingly essential for several computing tasks, analyzing their past and cu
arXiv:2605.27599v1 Announce Type: cross Abstract: Agentic AI workloads - where a single user goal triggers multi-step orchestration, tool calls, retries, and failure recovery - are being targeted for
Tensormesh Inc. has hit upon a way to make artificial intelligence inference more efficient by eliminating the need for redundant computations, and its technology is so convincing that several of AI i
As organizations push to convert AI ambition into defensible business results, many are discovering that infrastructure alone is not enough. Instead, the real challenge lies in reconciling decades of
Aidoc Medical Ltd., a startup with an artificial intelligence platform that helps doctors diagnose patients faster, has secured 150 million in funding. Goldman Sachs led the Series C round. Aidoc stat
The tweet from @NousResearch links to a Windows Central article written by Zac Bowden that provides an in‑depth review and benchmark analysis of Nvidia’s RTX Spark. Posted on Oct 16, 2026, the review
Size is pretty small at 102GB. For comparison nvidia/Qwen3.8-Flash-Next-NVFP4 is 133GB. Would be cool to see some of the Qwen3.8-FN specific engines support this. submitted by /u/rerri [link] [comment
Two months ago we released a fully quantized NVFP4 Qwen3.8-27B trained with QUASAR. We've since trained QUASAR checkpoints for a bunch of other recent models: Qwen3.5-4B, Gemma 4 E4B and 12B, and Muse
https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-GGUF https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-LiLiCorr-GGUF NVIDIA Nemotron 3.5 Bolt 74B-A9B 24GB is a vi
arXiv:2610.04949v1 Announce Type: new Abstract: Reinforcement learning controllers for underwater vehicles are usually trained against one physics representation and deployed against another, so repor
The man who may stand to make the most money from the AI boom seems to think he knows better than anyone else, including researchers who have studied and worked on AI for decades. In an interview with
Cosmos3 INT4 T2I + I2V on Apple Silicon — code, weights and a Grok comparison GitHub - https://github.com/gtrg55/cosmos3-quant-mlx-cuda HF weights - https://huggingface.co/JuliaML/Cosmos3-Super-Text2I
OpenAI’s Jalapeño is a self‑designed ASIC for large‑language‑model inference that was taped‑out in about 16 months, developed with Broadcom and featuring HBM4 memory. Benchmarks on the InferenceX suit
arXiv:2608.10103v1 Announce Type: cross Abstract: High-performance Tensor Core kernels rely on a low-level PTX pipeline built from asynchronous data movement with cp.async, warp-level matrix loads wit
arXiv:2608.07226v1 Announce Type: cross Abstract: Compact AI systems make local language-model experimentation increasingly accessible, yet practical evidence for multi-node training on desktop-class
The artificial intelligence competition is no longer between large language models, but rather between AI systems. Advanced Micro Devices Inc. has shifted from being primarily a chip business to a sec
A group of tech firms has released an open letter that calls on policymakers not to ban open-source artificial intelligence models. The development follows a report that some Trump administration offi
Quantized Krea 2 Turbo checkpoints for ComfyUI, up to 2x faster and about a third smaller than the usual FP8 version — no calibration dataset, no quality cliff. How to use it (short version): clone th
arXiv:2607.19353v1 Announce Type: new Abstract: Confidential computing is becoming a practical deployment requirement for AI inference workloads that process sensitive inputs or protect proprietary mo
arXiv:2607.08098v1 Announce Type: new Abstract: Event cameras offer microsecond temporal resolution, low latency, and high dynamic range, making them attractive for robotics. However, labeled event-ca
In this post, we explore what makes the Nemotron 3 architecture unique, walk through the fine-tuning techniques available, and show you step-by-step how to get started with serverless customization us
Many organizations today are floating in a ton of data. This is good for powering AI agents, but less favorable when it comes to identifying which signals from all of that data actually matter. The so
Nivida Corp. today announced Halos for Robotics, the industry’s first full framework for robotic safety systems that encompasses building, testing and managing complete artificial intelligence robotic
arXiv:2506.01969v3 Announce Type: replace-cross Abstract: Efficient inference of Multi-Head Latent Attention (MLA) is challenged by deploying the DeepSeek-R1 671B model on a single Multi-GPU server. T
arXiv:2606.03159v1 Announce Type: cross Abstract: As autonomous vehicle capabilities advance, the safe evaluation of driving policies in long-tail scenarios remains a critical bottleneck. In closed-lo
In this post you'll learn how to build a multi-agent campaign review system that demonstrates parallel reasoning, context persistence, and traceable execution paths using an integrated architecture th
Now we know for sure: This will be the year of monster initial public offerings. Elon Musk’s SpaceX filed for an IPO this week, aiming to raise a record $80 billion or more, and OpenAI was expected to
I've used this to watch shows and movies that have never been translated to English. There's so much great content out there, that is now accessible thanks to AI. Basically you clone the repo and tell
TornadoVM: The Java to CUDA engine: https://github.com/beehive-lab/TornadoVM jitLLM: The inference engine: https://github.com/beehive-lab/jitllm Deep dive talk: https://www.youtube.com/watch?v=HO5CpET
Planning, coding, testing = 8h total. Stack: VSCode Copilot in autopilot mode + SGLang Stats: ∼10k lines generated, ∼800k tokens consumed Sure, it's not GPT-6 Astra level, but for a 100% local ∼180B M
arXiv:2609.12923v1 Announce Type: cross Abstract: A single SM utilization percentage can make an LLM inference workload look compute-saturated while hiding how much useful work is being done. The prob
Github Repo. Blog post. 💡 TL;DR (from the Github Readme) Spend less without making the agent do less useful work. SoL-Pi is a standalone extension for Pi that packages four reusable efficiency mechani
75B MoE is an interesting size to check, you can run it today (no MTP support yet) The model employs a hybrid MoE architecture with interleaved Mamba, MoE, and Attention layers. Like Nemotron-3-Super,
I recently bought a 32GB V100 off eBay and thought I was all set with rudimentary tests showing zero issues. But then I started seeing weird VRAM-related errors in llama.cpp. I sic'ed Claude on it, to
Given Gavin Bakers recent interview where he says: > Multiple private companies are planning on spending at least 2x more per GPU for compute as contracts roll-off and some have spoken about this publ
Disclaimer - no LLM was used to write this post/note As larger post about my setup will come later, want to give heads-up to folks who use VLLM and >= 2 GPUs. So I have pretty meaty server (8 channel
We run a local model instance in our company that the dev we hired built for us. We're a trade business and we want to further use our on hand hardware for it. The specs given we have is a 5090 gpu wi
The Open Letter was initiated by Microsoft and published today: “Open Weights and American AI Leadership”. It argues against broad or premature restrictions on open-weight models and explicitly says p
I managed to get this model working on 2x 3090s with full 262k ctx and N=4, if anyone is interested to try it, thanks to this quant: https://huggingface.co/danielrmay/NVIDIA-Nemotron-Labs-3-Puzzle-75B
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Four nuclear reactors hit a big milestone in the US —Casey Cro
This post shows you how to configure training jobs on Amazon SageMaker AI to get the most out of Blackwell’s architecture on AWS. You learn how to select batch sizes and sequence lengths that take adv
The Mac mini M4 uses unified memory architecture where CPU and GPU share a single 24GB memory pool, while the RTX 5060 has dedicated VRAM. Mac mini M4 is preferred for large model inference (70B param
NVIDIA has released a corrected version of DeepSeek-V4-Pro-NVFP4, a quantized model variant optimized for NVIDIA hardware using NV-FP4 (NVIDIA's 4-bit floating-point format). The model is available on
This guide demonstrates that modern AI image generation models beyond Stable Diffusion 1.5 can run on a GTX 1060 6GB GPU using optimization techniques and ComfyUI, countering the common misconception
On March 5, 2026, the much-anticipated paper for FlashAttention-4 (FA4) was published. The code was dropped on GitHub months ago; early benchmarks circulated, and preliminary results were presented at