Introducing NVIDIA Ising, the world’s first open AI models to accelerate the path to useful quantum computers. Researchers and enterprises can now use AI-powered workflows for scalable, high-performance quantum systems with quantum processor calibration capabilities and quantum error-correction decoding. Learn more:

For Non Technical People - Right now, quantum computers have a major problem: they make mistakes constantly. To be useful, they need to be almost perfectly accurate. but today they’re nowhere close. What NVIDIA did is clever. Instead of solving this purely with physics, they’re using AI to manage and fix the errors. One part of the AI helps tune and calibrate quantum machines automatically, better than previous tools. Another part detects and fixes errors in real time, making the system faster and more reliable. Now, Why this matter: > Quantum computers are currently too unreliable to be practical. NVIDIA is turning that reliability problem into something AI can handle and they’ve made it open for everyone to use. > If quantum computing becomes important in the future, NVIDIA has positioned itself as the key technology provider behind the scenes the one everyone depends on.

@dallairedemers first eh? might want to double check.

Nemotron for language, Cosmos for physical AI, Isaac for robotics, Alpamayo for autonomous vehicles, BioNeMo for biomedical. Now Ising for quantum. Who says NVIDIA is a GPU company?

Open-sourcing both weights and datasets on Hugging Face turns quantum error management from a physics-only problem into an accessible AI-engineering workflow. This hybrid classical–quantum stack is precisely what scales NISQ devices toward useful, fault-tolerant machines. #LLMs

Nvidia is really cooking these days!!

Annother accelerator multiplier towards Cryptographically Relevant Quantum Computers. Have to wonder if we will have a black swan Quantum event, similar to AI taking the world by storm.

Could we see useful quantum computers before 2030?

NVQLink era

NVIDIA continues to bridge the gap between classical and quantum computing.

Links to ISING: model weights & dataset

You are not the first! 😂 This was already achieved last year, and your post here is nearly word for word of what the Real first scientist and developer said and accomplished already...a YEAR AGO

@chainyoda Nvidia is ahead of the industry this time!

nvidia sells GPUs to every AI lab on earth then buildong AI models that outperform all of them jensen huang is not your friend he is your landlord

@BarathAnandan7 Any beginner friendly to understand this? Anyone? Yeah i can just ask llm about this but any other way

Open AI models for quantum is exactly the kind of move that matters rn. this is why @SentientAGI been pushing community owned AGI so hard, keeping powerful models open instead of locked behind corporate walls. more of this please

I wonder how quantum will impact AI, maybe infinite context? Instant token speed? I feel like we have already hit an intelligence plateau where a 1% more intelligent model costs 10x more power to run. I don’t think Quantum solves that. Anyone know better?

if compute stays expensive most of this never reaches real users

Love it - thanks @nvidia

@nvidia This is awesome. NVIDIA Ising with AI that can tune quantum processors and decode errors way better? Feels like we're finally getting closer to useful quantum computing. Super cool to see it open source too.

Interesting move, turning quantum reliability into an AI problem could be a big unlock if it scales.

@nvidia AI is shit for people

@nvidia Oh, good..

Kalibrierung in Stunden statt Tagen. Das ist wie beim Grillen, wenn das Thermometer endlich mitspielt. Endlich handhabbare Quantentechnik!

I found the benchmarking comparison with other general models to be the most interesting. They are still pretty good, so curious which one the QC industry will adopt. I highlighted Ising in this week's Post-Quantum Roundup!

i can feel the acceleration

Hah any llm can do that

Advancing quantum calibration is a meaningful step in AI's integration with hardware development

This release shows that the path to useful quantum computing is becoming an engineering problem rather than just a physics one. Providing researchers with scalable calibration tools will significantly speed up the development of reliable processors.

optimize

and when you have a 1B qudit/qubit quantum computer you can do beyond what quantum companies are trying to do .. good luck catching up!

Huge step for NVIDIA and quantum computing progress