Scientists in China say they have been able to run an artificial intelligence model as sophisticated as a human brain on their most powerful supercomputer, a report from the South China Morning Pos t reveals.
According to the report, this puts China’s Newest Generation Sunway supercomputer on the same level as the U.S. Department of Energy’s Frontier, which was named the world’s most powerful supercomputer earlier this month.
As a point of reference, Frontier is the first machine to have demonstrated it can perform more than one quintillion calculations per second.
Unfortunately my internet link went down in the second Q&A session at the end and the recording cut off. Shame, loads of great information came out about FPGA/ASIC implementations, AI for the VR/AR, C/C++ and a whole load of other riveting and most interesting techie stuff. But thankfully the main part of the talk was recorded.
TALK OVERVIEW This talk is about the realization of the ideas behind the Fractal Brain theory and the unifying theory of life and intelligence discussed in the last Zoom talk, in the form of useful technology. The Startup at the End of Time will be the vehicle for the development and commercialization of a new generation of artificial intelligence (AI) and machine learning (ML) algorithms.
We will show in detail how the theoretical fractal brain/genome ideas lead to a whole new way of doing AI and ML that overcomes most of the central limitations of and problems associated with existing approaches. A compelling feature of this approach is that it is based on how neurons and brains actually work, unlike existing artificial neural networks, which though making sensational headlines are impeded by severe limitations and which are based on an out of date understanding of neurons form about 70 years ago. We hope to convince you that this new approach, really is the path to true AI.
In the last Zoom talk, we discussed a great unifying of scientific ideas relating to life & brain/mind science through the application of the mathematical idea of symmetry. In turn the same symmetry approach leads to a unifying of a mass of ideas relating to computer and information science. There’s been talk in recent years of a ‘master algorithm’ of machine learning and AI. We’ll explain that it goes far deeper than that and show how there exists a way of unifying into a single algorithm, the most important fundamental algorithms in use in the world today, which relate to data compression, databases, search engines and also existing AI/ML. Furthermore and importantly this algorithm is completely fractal or scale invariant. The same algorithm which is able to perform all these functionalities is able to run on a micro-controller unit (MCU), mobile phone, laptop and workstation, going right up to a supercomputer.
The application and utility of this new technology is endless. We will discuss the road map by which the sort of theoretical ideas I’ve been discussing in the Zoom, academic and public talks over the past few years, and which I’ve written about in the Fractal Brain Theory book, will become practical technology. And how the Java/C/C++ code running my workstation and mobile phones will become products and services.
Qubits are a basic building block for quantum computers, but they’re also notoriously fragile—tricky to observe without erasing their information in the process. Now, new research from the University of Colorado Boulder and the National Institute of Standards and Technology (NIST) could be a leap forward for handling qubits with a light touch.
In the study, a team of physicists demonstrated that it could read out the signals from a type of qubit called a superconducting qubit using laser light, and without destroying the qubit at the same time.
The group’s results could be a major step toward building a quantum internet, the researchers say. Such a network would link up dozens or even hundreds of quantum chips, allowing engineers to solve problems that are beyond the reach of even the fastest supercomputers around today. They could also, theoretically, use a similar set of tools to send unbreakable codes over long distances.
Canadian quantum computer company, Xanadu, has used its photonic quantum computer chip, Borealis, to solve a problem in 36 microseconds versus classical supercomputers taking 9,000 years. This is 7,884 trillion times faster. This runtime advantage is more than 50 million times larger than that of earlier photonic demonstrations.
An earlier quantum photonic computer used a static chip. The Borealis optical elements can all be readily programmed.
Borealis is accessible to anyone with an internet connection over Xanadu Cloud, and will also be available via Amazon Braket, the fully managed quantum computing service from AWS.
The first exascale computer has officially arrived.
The world’s fastest supercomputer performed more than a quintillion calculations per second, entering the realm of exascale computing. That’s according to a ranking of the world’s speediest supercomputers called the TOP500, announced on May 30. The computer, known as Frontier, is the first exascale computer to be included on the biannual list.
Ars Technica’s Chris Lee has spent a good portion of his adult life playing with lasers, so he’s a big fan of photon-based quantum computing. Even as various forms of physical hardware like superconducting wires and trapped ions made progress, it was possible to find him gushing about an optical quantum computer put together by a Canadian startup called Xanadu. But, in the year since Xanadu described its hardware, companies using that other technology continued to make progress by cutting down error rates, exploring new technologies, and upping the qubit count.
But the advantage of optical quantum computing didn’t go away, and now Xanadu is back with a reminder that it still hasn’t gone away. Thanks to some tweaks to the design it described a year ago, Xanadu is now able to sometimes perform operations with more than 200 qubits. And it has shown that simulating the behavior of just one of those operations on a supercomputer would take 9,000 years, while its optical quantum computer can do them in just a few-dozen milliseconds.
This is an entirely contrived benchmark: Just as Google’s quantum computer did, the quantum computer is just being itself while the supercomputer is trying to simulate it. The news here is more about the potential of Xanadu’s hardware to scale.
