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Texas-based Tesla gets China's initial approval of self-driving software

Chinese officials told Tesla that Beijing has tentatively approved the automaker's plan to launch its “Full Self-Driving,” or FSD, software feature in the country. Photo via tesla.com

Shares of Tesla stock rallied Monday after the electric vehicle maker's CEO, Elon Musk, paid a surprise visit to Beijing over the weekend and reportedly won tentative approval for its driving software.

Musk met with a senior government official in the Chinese capital Sunday, just as the nation’s carmakers are showing off their latest electric vehicle models at the Beijing auto show.

According to The Wall Street Journal, which cited anonymous sources familiar with the matter, Chinese officials told Tesla that Beijing has tentatively approved the automaker's plan to launch its “Full Self-Driving,” or FSD, software feature in the country.

Although it's called FSD, the software still requires human supervision. On Friday the U.S. government’s auto safety agency said it is investigating whether last year’s recall of Tesla’s Autopilot driving system did enough to make sure drivers pay attention to the road. Tesla has reported 20 more crashes involving Autopilot since the recall, according to the National Highway Traffic Safety Administration.

In afternoon trading, shares in Tesla Inc., which is based in Austin, Texas, surged to end Monday up more than 15% — its biggest one-day jump since February 2020. For the year to date, shares are still down 22%.

Tesla has been contending with its stock slide and slowing production. Last week, the company said its first-quarter net income plunged by more than half, but it touted a newer, cheaper car and a fully autonomous robotaxi as catalysts for future growth.

Wedbush analyst Dan Ives called the news about the Chinese approval a “home run” for Tesla and maintained his “Outperform” rating on the stock.

“We note Tesla has stored all data collected by its Chinese fleet in Shanghai since 2021 as required by regulators in Beijing,” Ives wrote in a note to investors. “If Musk is able to obtain approval from Beijing to transfer data collected in China abroad this would be pivotal around the acceleration of training its algorithms for its autonomous technology globally.”

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A View From HETI

Hadi Ghasemi, a University of Houston professor, has uncovered a method to release heat from data centers and electronics at record performance. Photo courtesy UH.

A University of Houston professor has developed a new cooling method that can remove heat at least three times more effectively from AI data centers than current technologies.

Hadi Ghasemi, a distinguished professor of Mechanical & Aerospace Engineering at UH, published his findings in two articles in the International Journal of Heat and Mass Transfer. The findings solve a critical issue in the growing AI sector, according to UH.

High-powered AI data centers generate huge amounts of heat due to the GPU and operating systems they use with extreme power densities, which introduce complex thermal challenges. Traditionally, cooling methods, like microchannels, which use flow and spray cooling, have had limitations when exposed to extreme heat flux, according to UH.

Ghasemi’s research, however, found a more effective way to design thin-film evaporation structures to release heat from data centers and electronics at record performance.

Ghasem’s solution coupled topology optimization and AI modeling to determine the best shapes for thin film efficiency, ultimately landing on a branch-like structure—resembling a tree.

The model found that the “branches” needed to be about 50 percent solid and 50 percent empty space for optimum efficiency, and that they could sustain high heat fluxes with minimal thermal resistance.

“These structures could achieve high critical heat flux at much lower superheat compared to traditionally studied structures,” Ghasemi said in a news release. “The new structures can remove heat without having to get as hot as previous removal systems.

Ghasemi’s doctoral candidates, Amirmohammad Jahanbakhsh and Saber Badkoobeh Hezave, also worked on the project. The team believes their results show the impact of a physics-aware, AI design and can help ensure reliability, longevity and stability of AI data centers.

“Beyond achieving record performance, these new findings provide fundamental insight into the governing heat-transfer physics and establishes a rational pathway toward even higher thermal dissipation capacities,” Ghasemi added in the release

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