AI Models One Million Times More Powerful than ChatGPT Within 10 Years

A million here, times a million there. Pretty soon you’re talking about big numbers. So the chip maker Nvidia claims for its AI accelerating hardware in terms of the performance boost it has delivered over the last decade and will deliver again over the next 10 years. The result, if Nvidia is correct, will be a new industry of AI factories across the world and gigantic breakthroughs in AI processing power. It also means, ostensibly, AI models one million times more powerful than existing examples, including ChatGPT, in AI processing terms at least. CEO Jensen Huang claimed that Nvidia‘s GPUs had boosted AI processing performance by a factor of no less than one million in the last 10 years.

“Moore’s Law, in its best days, would have delivered 100x in a decade,” Huang explained. “By coming up with new processors, new systems, new interconnects, new frameworks and algorithms and working with data scientists, AI researchers on new models, across that entire span, we’ve made large language model processing a million times faster.

Put another way: no Nvidia, no ChatGPT. The AI language model that is said to run on around 10,000 Nvidia GPUs and has captured the world’s consciousness by demonstrating something akin to its own actual consciousness in recent months wouldn’t be here without Jensen. And, of course, the team at OpenAI who actual put it into operation.

If one million times the performance in the last decade isn’t impressive enough, Huang has news for you: Nvidia‘s going to do it again.


AI-generated Replica of a Fusion Reactor Accelerates the Advent of Nuclear Fusion Power

The most powerful supercomputers on the planet are used to perform all manner of complex operations. Increasingly, they are used to enable artificial intelligence for research that could one day impact billions of people. The world’s fastest and most powerful high-performance computing (HPC) supercomputers are front and center at the International Supercomputing Conference (ISC).

HPC plus AI is really the transformational tool of scientific computing,” Dion Harris, Nvidia marketing manager for accelerated computing, said in a media briefing ahead of ISC. “We talk about exascale AI because we do believe that this is going to be one of the key pivotal tools to drive scientific innovation and any data center that’s building a supercomputer needs to understand how their system will perform from an AI standpoint.

Los Alamos National Laboratory and Hewlett Packard Enterprise (HPE) are building Venado, which is the first U.S. based supercomputer to use the Grace chip architecture. The Venado supercomputer uses a combination of Grace and Grace Hopper superchips, in a system that is expected to deliver 10 exaflops of AI performance. The Venado system will be used for material science, renewable energy, as well as energy distribution research.

As people around the world try to find solutions to the challenges of global warming, one of the primary strategies is to identify renewable energy sources. One such source could be nuclear reactors. Today’s nuclear reactors are fission-based and generate radioactive waste. The promise of fusion is that it can deliver large amounts of energy, without the same waste as fission. The U.K. Atomic Energy Authority (AEA) is using the Nvidia Omniverse simulation platform to accelerate the design and development of a full-scale fusion reactor. “With the Nvidia Omniverse, researchers could potentially build a fully functioning digital twin of a reactor, helping ensure the most efficient designs are selected for construction,” Harris said.

The goal for Omniverse and the digital twin is to have an AI-generated replica of the fusion reactor system. The U.K. AEA is also planning to simulate the physics of the Fusion plasma containment itself.The holy grail of fusion energy is being able to not just create a fusion reaction, but have it be sustainable,” Harris added. “We really think this will be a path towards sustainable energy.”


This Person Does Not exist

With the help of artificial intelligence, you can manipulate video of public figures to say whatever you like — or now, create images of people’s faces that don’t even exist. You can see this in action on a website called It uses an algorithm to spit out a single image of a person’s face, and for the most part, they look frighteningly realHit refresh in your browser, and the algorithm will generate a new face. Again, these people do not exist.

The website is the creation of software engineer Phillip Wang, and uses a new AI algorithm called StyleGAN, which was developed by researchers at NvidiaGAN, or Generative Adversarial Networks, is a concept within machine learning which aims to generate images that are indistinguishable from real ones. You can train GANs to remember human faces, as well bedrooms, cars, and cats, and of course, generate images of them.

Wang explained that he created the site to create awareness for the algorithm, and chose facesbecause our brains are sensitive to that kind of image.”  He added that it costs $150 a month to hire out the server, as he needs a good amount of graphical power to run the website.


It also started off as a personal agenda mainly because none of my friends seem to believe this AI phenomenon, and I wanted to convince them,” Wang said. “This was the most shocking presentation I could send them. I then posted it on Facebook and it went viral from there.

I think eventually, given enough data, a big enough neural [network] can be teased into dreaming up many different kinds of scenarios,” Wang added.