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"Hassabis was a child chess prodigy, who learned the game aged four and was able to beat his dad three weeks later - indeed, when he started playing competitively he was so small he had to bring a pillow with him to reach the board - and became a strong player. Yet in AlphaZero's case there was no human input, other than telling it the rules of each game. "In a matter of a few hours it was superhuman," Hassabis says proudly."

"A New York Times deep-dive into a facial recognition AI tool sold to law enforcement agencies uncovered that the company has amassed more than three billion images. Those images are scraped from all corners of the internet from social media sites to companies' "About Us" pages.  That's way more than the typical police or even FBI database. "

"What Hamilton and his colleagues found surprising was that this approach could also be applied to helping find problems with existing deep networks, related to the surge of "deepfakes" that have recently cropped up. They applied this data structure to find areas where probabilistic models, such as the generative adversarial networks (GANs) that are often used to create deepfakes, break down. They coined these problematic areas "blind spots," and note that they give us insight into how GANs can be biased. Such blind spots further show that GANs struggle to represent particular areas of a dataset, even if most of their fakes can fool a human. "

""This study shows that if this algorithm were in place earlier, some materials could have conceivably been discovered years in advance," Jain said."

"A natural alternative to symbolic AI came to prominence: Instead of modeling high-level reasoning processes, why not instead model the brain? After all, brains are the only things that we know for certain can produce intelligent behavior. Why not start with them?"

"The gulf between how well facial recognition performs in academic settings vs. real world applications is vast."

"The difference between skimming and reading with all our intelligence is the difference between fully activated reading brains and their short-circuited, screen-dulled versions."

"The CEO of OpenAI, the company responsible for creating artificial intelligence chatbot ChatGPT and image generator Dall-E 2, said "regulation of AI is essential" as he testified in his first appearance in front of the US Congress. The apocalypse isn't coming. We must resist cynicism and fear about AI Stephen Marche Stephen Marche Read more Speaking to the Senate judiciary committee on Tuesday, Sam Altman said he supported regulatory guardrails for the technology that would enable the benefits of artificial intelligence while minimizing the harms. "We think that regulatory intervention by governments will be critical to mitigate the risks of increasingly powerful models," Altman said in his prepared remarks."

"Now that might be about to change. The arrival of OpenAI's ChatGPT, a program that generates sophisticated text in response to any prompt you can imagine, may signal the end of writing assignments altogether-and maybe even the end of writing as a gatekeeper, a metric for intelligence, a teachable skill. If you're looking for historical analogues, this would be like the printing press, the steam drill, and the light bulb having a baby, and that baby having access to the entire corpus of human knowledge and understanding. My life-and the lives of thousands of other teachers and professors, tutors and administrators-is about to drastically change."

"The performance of LipNet compares incredibly favorably to human lipreading experts on GRID corpus, the largest publicly-available sentence-level lipreading dataset. In fact, where human experts got just 52 percent, LipNet scored 93 percent. Its sentence-based approach to lip-reading also smashed the best previous attempt by a machine, which managed 79.6 percent accuracy on the same dataset."