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Tesla’s Full Self-Driving (FSD) technology is rapidly advancing, impressing users and analysts alike, while navigating challenges in the auto industry and broader economic factors.

Questions to inspire discussion.

Tesla’s FSD Progress.

🚗 Q: How many unsupervised miles has Tesla’s FSD driven? A: Tesla’s FSD has driven over 50,000 unsupervised miles, demonstrating significant progress in autonomous driving capabilities.

🌐 Q: What indicates Tesla’s transition to software-defined earnings? A: FSD unsupervised miles and operating domain growth are key leading indicators of Tesla’s shift towards software-defined earnings.

🤖 Q: How does Tesla’s FSD showcase AI potential in driving? A: Tesla’s FSD unsupervised capabilities, demonstrated in complex driving scenarios, serve as a proof case for artificial intelligence’s potential in autonomous driving.

Researchers from the Department of Energy’s Oak Ridge National Laboratory have developed a new application to increase efficiency in memory systems for high-performance computing.

Rather than allow data to bog down traditional memory systems in supercomputers and impact performance, the team from ORNL, along with researchers from the University of Tennessee, Knoxville, created a framework to manage data more efficiently with memory systems that employ more complex structures. Research papers detailing their work were recently accepted in ACM Transactions on Architecture and Code Optimization and the International Journal of High-Performance Computing Applications.

Working under the Exascale Computing Project, or ECP, a multi-year software research, development and deployment project managed by DOE, ORNL senior computer science researcher Terry Jones and his team titled their work the “ECP Simplified Interface to Complex Memories,” or SICM, Project.

Imagine if phones never got hot no matter how many apps were running. Picture a future where supercomputers use less energy, electric cars charge faster, and life-saving medical devices stay cooler and last longer.

In a study published in Nature Materials, a team of engineers at the University of Virginia and their collaborators revealed a radical new way to move heat, faster than ever before. Using a special kind of crystal called hexagonal boron nitride (hBN), they found a way to move heat like a beam of light, sidestepping the usual bottlenecks that make electronics overheat.

“We’re rethinking how we handle heat,” said Patrick Hopkins, professor of mechanical and aerospace engineering and Whitney Stone Professor of Engineering at UVA. “Instead of letting it slowly trickle away, we’re directing it.”

Both systems are powered by AMD GPUs—Frontier is equipped with 9,408 AMD EPYC processors and 37,632 AMD Instinct MI250X accelerators, while El Capitan features 44,544 of the newer AMD Instinct MI300A accelerators.

Given the success with this simulation, Ansys has hailed AMD’s Instinct GPUs for cutting the simulation time. According to the company, this milestone could dramatically speed up the design iterations and deliver more accurate performance forecasts for industrial systems.

The Gefion AI Supercomputer (GAIS) project, which delivers Denmark’s first artificial intelligence (AI) turbo-charged supercomputer, has positioned Denmark as the most advanced of the Nordic region’s quantum computing investing nations.

It also serves to accelerate the use of AI to drive innovation across Denmark’s business and industrial sectors.

Built on the Nvidia DGX SuperPOD AI supercomputer, GAIS is powered by 1,528 Nvidia H100 Tensor Core graphics processing units (GPUs) and interconnected using Nvidia Quantum-2 InfiniBand networking.

A major breakthrough in quantum computing has just been achieved by American researchers at MIT. This innovation, dubbed the “quantum superhighway”, revolutionizes communication between quantum processors and opens up promising new prospects for the development of more powerful and efficient supercomputers.

Quantum computers today represent the cutting edge of computing , capable of solving problems far beyond the capabilities of conventional supercomputers. However, their efficiency depends on fast, precise communication between their various processors. This is precisely the challenge that American engineers have just met.

The innovation developed by the MIT team consists of an interconnection device enabling instant communication between quantum processors. Unlike traditional “point-to-point” link systems, which are prone to increasing errors during data transfer, this “quantum superhighway” promotes far more efficient “all-to-all” communication.