NVIDIA’s on the bottom at Open Supply AI Week. Keep tuned for a celebration highlighting the spirit of innovation, collaboration and neighborhood that drives open-source AI ahead. Observe NVIDIA AI Developer on social channels for extra information and insights.
NVIDIA Inception Startups Spotlight AI Innovation 🔗
On the PyTorch Convention’s Startup Showcase, 11 startups — together with members from the NVIDIA Inception program — are sharing their work creating sensible AI purposes and connecting with traders, potential clients and friends.
Runhouse, an AI infrastructure startup optimizing mannequin deployment and orchestration, was topped the 2025 PyTorch Startup Showcase Award Winner. The Group Selection Award was offered to CuraVoice, with CEO Sakhi Patel, CTO Shrey Modi, and advisor Rahul Vishwakarma accepting the award on behalf of the workforce.
CuraVoice gives an AI-powered voice simulation platform — powered by NVIDIA Riva for speech recognition and text-to-speech, and NVIDIA NeMo for conversational AI fashions — for healthcare college students and professionals, providing interactive workouts and adaptive suggestions to enhance affected person communication expertise.
Along with CuraVoice, different Inception members, together with Backfield AI, Graphsignal, Okahu AI, Snapshot AI and XOR, had been featured individuals within the Startup Showcase.
Snapshot AI delivers actionable, real-time insights to engineering groups utilizing recursive retrieval-augmented technology (RAG), transformers and multimodal AI. The corporate’s platform faucets into the NVIDIA CUDA Toolkit to ship high-performance evaluation and fast insights at scale.
XOR is a cybersecurity startup providing AI brokers that mechanically repair vulnerabilities within the provide chain of different AIs. The corporate helps enterprises eradicate vulnerabilities whereas complying with regulatory necessities. XOR’s agentic know-how makes use of NVIDIA cuVS vector seek for indexing, real-time retrieval and code evaluation. The corporate additionally makes use of GPU-based machine studying to coach fashions to detect hidden backdoor patterns and prioritize of high-value safety outcomes.
Highlights From Open Supply AI Week 🔗
Attendees of Open Supply AI Week are getting a peek on the newest developments and inventive tasks which might be shaping the way forward for open know-how.
Right here’s a take a look at what’s occurring onsite:
The world’s smallest AI supercomputer: NVIDIA DGX Spark represents the chopping fringe of AI computing {hardware} for enterprise and analysis purposes.
Humanoids and robotic canines, up shut: Unitree robots are on show, charming attendees with superior mobility powered by the most recent robotics know-how.
Why open supply is vital: Study the way it can empower builders to construct stronger communities, iterate on options, and seamlessly combine one of the best of open supply AI.
Accelerating AI Analysis By way of Open Fashions 🔗
A research from the Heart for Safety and Rising Know-how (CSET) printed as we speak reveals how entry to open mannequin weights unlocks extra alternatives for experimentation, customization and collaboration throughout the worldwide analysis neighborhood.
The report outlines seven high-impact analysis use instances the place open fashions are making a distinction — together with fine-tuning, continued pretraining, mannequin compression and interpretability.
With entry to weights, builders can adapt fashions for brand spanking new domains, discover new architectures and lengthen performance to fulfill their particular wants. This additionally helps belief and reproducibility. When groups can run experiments on their very own {hardware}, share updates and revisit earlier variations, they acquire management and confidence of their outcomes.
Moreover, the research discovered that almost all open mannequin customers share their knowledge, weights and code, constructing a fast-growing tradition of collaboration. This open trade of instruments and data strengthens partnerships between academia, startups and enterprises, facilitating innovation.
NVIDIA is dedicated to empowering the analysis neighborhood by means of the NVIDIA Nemotron household of open fashions — that includes not simply open weights, but in addition pretraining and post-training datasets, detailed coaching recipes, and analysis papers that share the most recent breakthroughs.
Learn the full CSET research to learn the way open fashions are serving to the AI neighborhood transfer ahead.
Advancing Embodied Intelligence By way of Open-Supply Innovation 🔗
On the PyTorch Convention, Jim Fan, director of robotics and distinguished analysis scientist at NVIDIA, mentioned the Bodily Turing Take a look at — a method of measuring the efficiency of clever machines within the bodily world.
With conversational AI now able to fluent, lifelike communication, Fan famous that the subsequent problem is enabling machines to behave with comparable naturalism. The Bodily Turing Take a look at asks: can an clever machine carry out a real-world activity so fluidly {that a} human can not inform whether or not an individual or a robotic accomplished it?
Fan highlighted that progress in embodied AI and bodily AI is determined by producing giant quantities of various knowledge, entry to open robotic basis fashions and simulation frameworks — and walked by means of a unified workflow for creating embodied AI.
With artificial knowledge workflows like NVIDIA Isaac GR00T-Desires — constructed on NVIDIA Cosmos world basis fashions— builders can generate digital worlds from photographs and prompts, rushing the creation of huge units of various and bodily correct knowledge.
That knowledge can then be used to post-train NVIDIA Isaac GR00T N open basis fashions for generalized humanoid robotic reasoning and expertise. However earlier than the fashions are deployed in the true world, these new robotic expertise have to be examined in simulation.
Open simulation and studying frameworks similar to NVIDIA Isaac Sim and Isaac Lab enable robots to “observe” numerous instances throughout thousands and thousands of digital environments earlier than working in the true world, dramatically accelerating studying and deployment cycles.
Plus, with Newton, an open-source, differentiable physics engine constructed on NVIDIA Warp and OpenUSD, builders can convey high-fidelity simulation to advanced robotic dynamics similar to movement, steadiness and phone — lowering the simulation-to-real hole.
This accelerates the creation of bodily succesful AI programs that be taught quicker, carry out extra safely and function successfully in real-world environments.
Nonetheless, scaling embodied intelligence isn’t nearly compute — it’s about entry. Fan reaffirmed NVIDIA’s dedication to open supply, emphasizing how the corporate’s frameworks and basis fashions are shared to empower builders and researchers globally.
Builders can get began with NVIDIA’s open embodied and bodily AI fashions on Hugging Face.
Llama‑Embed‑Nemotron‑8B Ranks Amongst High Open Fashions for Multilingual Retrieval 🔗
NVIDIA’s Llama‑Embed‑Nemotron‑8B mannequin has been acknowledged as the highest open and transportable mannequin on the Multilingual Textual content Embedding Benchmark leaderboard.
Constructed on the meta‑llama/Llama‑3.1‑8B structure, Llama‑Embed‑Nemotron‑8B is a analysis textual content embedding mannequin that converts textual content into 4,096‑dimensional vector representations. Designed for flexibility, it helps a variety of use instances, together with retrieval, reranking, semantic similarity and classification throughout greater than 1,000 languages.
Educated on a various assortment of 16 million question–doc pairs — half from public sources and half synthetically generated — the mannequin advantages from refined knowledge technology methods, exhausting‑detrimental mining and mannequin‑merging approaches that contribute to its broad generalization capabilities.
This outcome builds on NVIDIA’s ongoing analysis in open, excessive‑performing AI fashions. Following earlier leaderboard recognition for the Llama NeMo Retriever ColEmbed mannequin, the success of Llama‑Embed‑Nemotron‑8B highlights the worth of openness, transparency and collaboration in advancing AI for the developer neighborhood.
Try Llama-Embed-Nemotron-8B on Hugging Face, and be taught extra in regards to the mannequin, together with architectural highlights, coaching methodology and efficiency analysis.
What Open Supply Teaches Us About Making AI Higher
Open fashions are shaping the way forward for AI, enabling builders, enterprises and governments to innovate with transparency, customization and belief. Within the newest episode of the NVIDIA AI Podcast, NVIDIA’s Bryan Catanzaro and Jonathan Cohen talk about how open fashions, datasets and analysis are laying the muse for shared progress throughout the AI ecosystem.
The NVIDIA Nemotron household of open fashions represents a full-stack strategy to AI improvement, connecting mannequin design to the underlying {hardware} and software program that energy it. By releasing Nemotron fashions, knowledge and coaching methodologies brazenly, NVIDIA goals to assist others refine, adapt and construct upon its work, leading to a quicker trade of concepts and extra environment friendly programs.
“Once we as a neighborhood come collectively — contributing concepts, knowledge and fashions — all of us transfer quicker,” stated Catanzaro within the episode. “Open applied sciences make that attainable.”
There’s extra occurring this week at Open Supply AI Week, together with the beginning of the PyTorch Convention — bringing collectively builders, researchers and innovators pushing the boundaries of open AI.
Attendees can tune in to the particular keynote handle by Jim Fan, director of robotics and distinguished analysis scientist at NVIDIA, to listen to the most recent developments in robotics — from simulation and artificial knowledge to accelerated computing. The keynote, titled “The Bodily Turing Take a look at: Fixing Normal Objective Robotics,” will happen on Wednesday, Oct. 22, from 9:50-10:05 a.m. PT.
Andrej Karpathy’s Nanochat Teaches Builders How you can Prepare LLMs in 4 Hours 🔗
Pc scientist Andrej Karpathy not too long ago launched Nanochat, calling it “one of the best ChatGPT that $100 can purchase.” Nanochat is an open-source, full-stack giant language mannequin (LLM) implementation constructed for transparency and experimentation. In about 8,000 strains of minimal, dependency-light code, Nanochat runs all the LLM pipeline — from tokenization and pretraining to fine-tuning, inference and chat — all by means of a easy net consumer interface.
NVIDIA is supporting Karpathy’s open-source Nanochat undertaking by releasing two NVIDIA Launchables, making it simple to deploy and experiment with Nanochat throughout varied NVIDIA GPUs.
With NVIDIA Launchables, builders can prepare and work together with their very own conversational mannequin in hours with a single click on. The Launchables dynamically assist different-sized GPUs — together with NVIDIA H100 and L40S GPUs — on varied clouds with out want for modification. Additionally they mechanically work on any eight-GPU occasion on NVIDIA Brev, so builders can get compute entry instantly.
The first 10 customers to deploy these Launchables can even obtain free compute entry to NVIDIA H100 or L40S GPUs.
Begin coaching with Nanochat by deploying a Launchable:
Andrej Karpathy’s Subsequent Experiments Start With NVIDIA DGX Spark
At this time, Karpathy obtained an NVIDIA DGX Spark — the world’s smallest AI supercomputer, designed to convey the ability of Blackwell proper to a developer’s desktop. With as much as a petaflop of AI processing energy and 128GB of unified reminiscence in a compact kind issue, DGX Spark empowers innovators like Karpathy to experiment, fine-tune and run large fashions domestically.
Constructing the Way forward for AI With PyTorch and NVIDIA 🔗
PyTorch, the fastest-growing AI framework, derives its efficiency from the NVIDIA CUDA platform and makes use of the Python programming language to unlock developer productiveness. This 12 months, NVIDIA added Python as a first-class language to the CUDA platform, giving the PyTorch developer neighborhood better entry to CUDA.
CUDA Python contains key parts that make GPU acceleration in Python simpler than ever, with built-in assist for kernel fusion, extension module integration and simplified packaging for quick deployment.
Following PyTorch’s open collaboration mannequin, CUDA Python is offered on GitHub and PyPI.
Each month, builders worldwide obtain a whole bunch of thousands and thousands of NVIDIA libraries — together with CUDA, cuDNN, cuBLAS and CUTLASS — principally inside Python and PyTorch environments. CUDA Python gives nvmath-python, a brand new library that acts because the bridge between Python code and these extremely optimized GPU libraries.
Plus, kernel enhancements and assist for next-generation frameworks make NVIDIA accelerated computing extra environment friendly, adaptable and broadly accessible.
NVIDIA maintains a long-standing collaboration with the PyTorch neighborhood by means of open-source contributions and technical management, in addition to by sponsoring and collaborating in neighborhood occasions and activations.
At PyTorch Convention 2025 in San Francisco, NVIDIA will host a keynote handle, 5 technical classes and 9 poster shows.
NVIDIA’s on the bottom at Open Supply AI Week. Keep tuned for a celebration highlighting the spirit of innovation, collaboration and neighborhood that drives open-source AI ahead. Observe NVIDIA AI Developer on social channels for extra information and insights.
NVIDIA Spotlights Open Supply Innovation 🔗
Open Supply AI Week kicks off on Monday with a sequence of hackathons, workshops and meetups spotlighting the most recent advances in AI, machine studying and open-source innovation.
The occasion brings collectively main organizations, researchers and open-source communities to share data, collaborate on instruments and discover how openness accelerates AI improvement.
NVIDIA continues to increase entry to superior AI innovation by offering open-source instruments, fashions and datasets designed to empower builders. With greater than 1,000 open-source instruments on NVIDIA GitHub repositories and over 500 fashions and 100 datasets on the NVIDIA Hugging Face collections, NVIDIA is accelerating the tempo of open, collaborative AI improvement.
Over the previous 12 months, NVIDIA has change into the highest contributor in Hugging Face repositories, reflecting a deep dedication to sharing fashions, frameworks and analysis that empower the neighborhood.
Brazenly out there fashions, instruments and datasets are important to driving innovation and progress. By empowering anybody to make use of, modify and share know-how, it fosters transparency and accelerates discovery, fueling breakthroughs that profit each business and communities alike. That’s why NVIDIA is dedicated to supporting the open supply ecosystem.
We’re on the bottom all week — keep tuned for a celebration highlighting the spirit of innovation, collaboration and neighborhood that drives open-source AI ahead, with the PyTorch Convention serving because the flagship occasion.
