Nvidia CEO Jensen Huang has unveiled plans to build a next-generation AI platform called Rubin — named after astronomer Vera Rubin.
Huang made the announcement at an address ahead of the COMPUTEX technology convention in Taipei, which starts on June 4.
According to the company’s blog, Huang spoke to nearly 6,500 industry executives, reporters, entrepreneurs, gamers, inventors, and AI fans who had congregated at the glass-domed National Taiwan University Sports Center in Taipei.
NVIDIA takes to the stage at COMPUTEX, with a slew of AI-powered tools to enable game assistants, digital humans, and improve generative AI.
Scientists are calculating earthquake risk using an ISI-created system that automates and manages data-and compute-intensive research.
Quantum simulators are now addressing complex physics problems, such as the dynamics of 1D quantum magnets and their potential similarities to classical phenomena like snow accumulation. Recent research confirms some aspects of this theory, but also highlights challenges in fully validating the KPZ universality class in quantum systems. Credit: Google LLC
Quantum simulators are advancing quickly and can now tackle issues previously confined to theoretical physics and numerical simulation. Researchers at Google Quantum AI and their collaborators demonstrated this new potential by exploring dynamics in one-dimensional quantum magnets, specifically focusing on chains of spin-1/2 particles.
They investigated a statistical mechanics problem that has been the focus of attention in recent years: Could such a 1D quantum magnet be described by the same equations as snow falling and clumping together? It seems strange that the two systems would be connected, but in 2019, researchers at the University of Ljubljana found striking numerical evidence that led them to conjecture that the spin dynamics in the spin-1⁄2 Heisenberg model are in the Kardar-Parisi-Zhang (KPZ) universality class, based on the scaling of the infinite-temperature spin-spin correlation function.
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AI technology is spreading quickly throughout many different industries, and its integration depends on users’ trust and safety concerns. This matter becomes complicated when the algorithms powering AI-based tools are vulnerable to cyberattacks that could have detrimental results.
Dr. David P. Woodruff from Carnegie Mellon University and Dr. Samson Zhou from Texas A&M University are working to strengthen the algorithms used by big data AI models against attacks.
Much like the invigorating passage of a strong cold front, major changes are afoot in the weather forecasting community. And the end game is nothing short of revolutionary: an entirely new way to forecast weather based on artificial intelligence that can run on a desktop computer.
Today’s artificial intelligence systems require one resource more than any other to operate—data. For example, large language models such as ChatGPT voraciously consume data to improve answers to queries. The more and higher quality data, the better their training, and the sharper the results.
The Dark Energy Spectroscopic Instrument (DESI) is a robotic instrument and spectrograph mounted on the Mayall Telescope in Kitt Peak, Arizona. The DESI collaboration aims primarily to understand the elusive Dark Energy. This is an energy of unknown source causing the Universe to accelerate in its expansion; this accelerating expansion is not predicted to occur for a universe that is filled with just ordinary matter and radiation (some more detail can be seen in this Astrobite). Since we still know so little about Dark Energy, a large galaxy survey can allow us to explore the history of the expansion of the Universe in more detail. The DESI instrument has 5,000 individual optical fibres controlled by robots that allow it to measure individual spectra of up to 5,000 galaxies in just a mere 20 minutes! Due to this design, and an observing program that optimises targets in the sky based on observing conditions, the survey will measure spectra of up to 35 million galaxies over 5 years. This will allow DESI to perform precise cosmological measurements, as a great volume of space and number of galaxies can be probed, and noise in the data products is reduced. This bite looks at the cosmology results from the collaboration’s analysis of the recently released Year 1 Data (YR1), in particular, via a signal that can be seen in the data known as Baryon Acoustic Oscillations.
DESI tracers
For the cosmological results in this work DESI uses information from various different ‘tracers’ – galaxies that trace the Large Scale Structure of the Universe. These consist of low redshift bright galaxies (BGS) that are measured when the moon lights the sky (and thus dimmer galaxies are less visible), and higher redshift galaxies measured during the dark time. The dimmer objects include luminous red galaxies (LRGs) which are elliptical galaxies that are extremely bright, emission line galaxies (ELGs) which are younger galaxies with emission line features in their spectra, and quasars (QSOs) which are very distant and bright galaxies that contain active galactic nuclei. The sample used also includes QSOs detected using Lyman-alpha forest measurements, or a method of tracing matter that utilises a series of absorption lines detected due to light from distant QSOs passing through neutral hydrogen in the space between us and the distant galaxies.
I disagree with you Dan Breeden. In my openion AI WILL A BETTER FUTURE FOR HUMAN CIVILIZATION.
Doctors and engineers from Massachusetts General Hospital and MIT are trying to revolutionize cancer detection through an artificial intelligence program called Sybil. Their study found that Sybil could accurately predict whether a person will develop lung cancer in the next year up to 94 percent of the time. NBC News’ Dr. John Torres reports.
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Coral reefs, nurturing hubs of marine biodiversity, are grappling with mounting threats from environmental shifts. Traditional monitoring techniques, often laborious and invasive, are proving inadequate in the face of rapid ecological changes.
“Testing people early, so early interventions are possible, is key to longevity,” she says. “Technology, data and AI, and what we’re starting to be able to do with it, are propelling us to a time of greater understanding which will foster earlier, more effective treatment. Or perhaps even therapies that can delay neurodegenerative diseases, pushing back dementia to beyond our lifespan.”
Mind Over Matter goes out on 29th and 30th June on BBC News and 30th June on BBC One.
Lara Lewington will be hosting a Fireside Chat on AI drug discovery with Alex Zhavoronkov at next week’s Founders Longevity Forum. Register your interest to discover how AI is accelerating drug discovery, commercialization and licensing models HERE.
