Jacopo Pantaleoni joined Nvidia in 2001 when the company had less than 500 employees. He worked on what was then a small research project to improve Nvidia’s graphics processing units so they could better render images on computers and gaming consoles.

More than two decades later, Nvidia has more than 26,000 employees and its GPUs are at the center of the generative AI explosion. Pantaleoni had climbed the ranks to become a principal engineer and research scientist, one of the highest ranking positions for an individual contributor, he says. Then, in July, as Nvidia boomed like no other company, Pantaleoni says he resigned, giving up a substantial amount of unvested stock units, after coming to a realization.

“This market of machine learning, artificial intelligence” is “almost entirely driven by the big players— Googles, Amazons, Metas”—that have the “enormous amounts of data and enormous amounts of capital” to develop AI at scale. Those companies are also Nvidia’s biggest customers. “This was not the world I wanted to help build,” he said.

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Waymo is offering some Los Angeles residents the chance to ride in the self-driving car across the city.

The company is kicking off its Waymo One tour, which they say is ‘the world’s first fully autonomous ride-hailing service,’ in October.

“Chauffeured by the Waymo Driver — Waymo’s autonomous driving technology that never gets distracted, drowsy or drunk — Angelenos will discover new and stress-free ways to explore their city, whether it’s finding hidden gem thrift spots in Mid City, trying a new cafe in Koreatown or catching a concert in DTLA,” the company said.

A team of Japanese researchers claims that they were able to use AI to translate the clucks and noises of chickens.

AI Chicken Language Translator?

This novel feat was documented in a preprint that is yet to undergo peer review. The research team was reportedly able to develop a system that can interpret chicken’s different emotional states. These covered the fowls’ feelings of anger, fear, hunger, excitement, contentment, and distress.

The technology relied on an AI technique that the researchers refer to as Deep Emotional Analysis Learning, according to professor Adrian David Cheok from the University of Tokyo.