Clearview AI plans technology to identify faces as they age

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In short Controversial facial recognition startup Clearview AI plans to employ more staff in order to land big, lucrative contracts with the US government worth millions of dollars.

CEO Hoan Thon That Recount Reuters Clearview’s current annual contracts with its 3,100 customers are relatively small.

“We know some of these agencies are very successful, but they’re just a little five-figure buy or six-figure buy. And so it’s ‘Can we get some seven digits, maybe eight – numeric purchases?’.”

To pursue larger projects, Clearview AI will increase in size by a third and build new capabilities such as matching photographs of young and old people to improve identification.

Clearview is best known for grabbing people’s personal images from social media platforms like Facebook or Instagram, as well as image sharing sites like Flickr or Getty Images. This practice got the company in legal trouble in the United States and Canada.

Will RISC-V chips continue to dominate AI?

The number of chips based on the RISC-V architecture is expected to increase by 73.6% per year until 2027, the majority of which will power AI and machine learning software, according to to the research and consultancy group Semico.

Hardware startups building custom AI accelerators are turning to RISC-V’s open-source plans to avoid paying the licensing fees required when using x86 and Arm architectures. RISC-V’s low-cost instruction set also allows chip designers to build processors that are smaller and require fewer transistors. The resulting products are more energy efficient than their competitors.

Arm-based chips remain the market leader in AI hardware, with RISC-V designs accounting for just 15% of total CPU core architecture revenue.

Rich Wawrzyniak, Senior Research Analyst at Semico Recount IEEE Spectrum that RISC-V is growing rapidly. “It’s not 50%, but it’s not 5% either. And if you think about how long RISC-V has been around, it’s growing pretty fast.” Around 25 billion machine learning chips are expected to be built by 2027, an industry totaling some $291 billion.

AI algorithms are better at teaching students how to perform brain surgery than remote human instructors

Study finds medical student learning curves improved when using neurosurgical simulator and machine learning coach to study virtual brain tumor removal published in JAMA Network Last week.

A group of 70 students from McGill University, Canada, were divided into three different groups. One received instruction and feedback from remote human tutors who guided them through model procedures. Others were taught by an AI system known as a virtual operating assistant (VOA), while a third group received no help.

Researchers found that students learned surgical skills 2.6 times faster and performed 36% better when learning from VOA, compared to those taught remotely by real experts.

“Artificially intelligent tutors like the VOA can become a valuable tool in training the next generation of neurosurgeons,” noted Rolando Del Maestro, lead author of the study and a researcher at the Neurosurgical Simulation and Artificial Intelligence Learning Center. ®

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