Shortly Controversial facial recognition startup Clearview AI plans to hire more staff to pursue lucrative multimillion-dollar US government contracts.
CEO Hoan Thon That told Reuters Clearview’s current annual contracts with its 3,100 customers are relatively small.
“We know some of these agencies are having great success, but they’re only at a small five-figure or six-figure purchase. And so it’s, ‘Can we get some of these into seven figures, maybe eight figures? -Figure purchases?’.”
To pursue larger projects, Clearview AI will increase its size by a third and develop new capabilities such as B. Matching photos of people younger and older to improve identification.
Clearview is best known for scraping people’s personal pictures from social media platforms like Facebook or Instagram, as well as image-sharing sites like Flickr or Getty Images. This practice got the company into 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 grow at 73.6 percent per year through 2027, most of which will support AI and machine learning software. according to to the research and consulting group Semico.
Hardware startups building custom AI accelerators are turning to RISC-V’s open-source blueprints to avoid paying the licensing fees required when using x86 and ARM architectures. RISC-V’s economical instruction set also enables chip designers to build processors that are smaller and use fewer transistors. The resulting products are more energy efficient than those of the competition.
ARM-based chips remain the market leader for AI hardware, with RISC-V designs accounting for just 15 percent of total CPU core architecture sales.
Semico Research Principal Analyst Rich Wawrzyniak told IEEE spectrum that RISC-V is expanding rapidly. “It’s not 50 percent, but it’s not five percent either. And considering how long RISC-V has been around, that’s pretty rapid growth.” Around 25 billion machine learning chips are expected to be built by 2027, an industry worth around $291 billion.
AI algorithms are better at teaching students how to perform brain surgeries than remote human instructors
Medical students’ learning curves improved when they used a neurosurgical simulator and machine learning trainer to study virtual brain tumor removal, according to a study released in JAMA network last week.
A group of 70 students from McGill University, Canada, were divided into three different groups. Instructions and feedback were received from remote human tutors, guiding them through the model procedures. Others were tutored by an AI system called Virtual Operative Assistant (VOA), while a third group received no help at all.
The researchers found that students learned surgical skills 2.6 times faster and performed 36 percent better when learning from the VOA compared to those taught remotely by real experts.
“Artificially intelligent tutors like the VOA can become a valuable tool in the training of the next generation of neurosurgeons,” called Rolando Del Maestro, senior author of the study and researcher at the Neurosurgical Simulation and Artificial Intelligence Learning Centre. ®