In 2017, soon after Google researchers invented a new kind of neural network called a transformer, a young OpenAI engineer named Alec Radford began experimenting with it. What made the transformer architecture different from that of existing A.I. systems was that it could ingest and make connections among larger volumes of text, and Radford decided to train his model on a database of seven thousand unpublished English-language books--romance, adventure, speculative tales, the full range of human fantasy and invention. Then, instead of asking the network to translate text, as Google's researchers had done, he prompted it to predict the most probable next word in a sentence. The machine responded: one word, then another, and another--each new term inferred from the patterns buried in those seven thousand books. Radford hadn't given it rules of grammar or a copy of Strunk and White.

Green was going through a breakup. The reasons for the split itself had been largely unremarkable by breakup standards: Two people, unable to meet each others' needs and struggling to communicate, had decided it was best to part ways. So when Green's ex reached out, unprompted, Green was shocked. The email itself was not notable. Green, a 29-year-old New Yorker, describes it as a typical letter to get after a breakup, an airing of grievances pointing out the ways in which expectations weren't met.

Breakthroughs, discoveries, and DIY tips sent every weekday. MotoGP is high-speed, high-tech motorcycle racing. The fastest riders in the world compete on specialized, purpose-built motorcycles from companies like Ducati, Honda, Yamaha on the world stage in this series, which is considered the most prestigious in the game. Riders reach incredible speeds on their machines up to 220 miles per hour, and races can go 350 turns with gravity-defying leaning that scrapes elbows and knees. This Grand Prix is for the toughest of the tough on the moto circuit.

The apple blossoms are sprouting, the sun is finally rising before your alarm goes off, and Google CEO Sundar Pichai is wiping down the lenses of his Gemini-powered smart glasses. You know what that means: It's once again time for Google I/O. Google is going all out for its annual I/O developer conference, which begins on Tuesday, May 20. The event is taking place at Shoreline Amphitheater in Mountain View, California, just down the road from Google's headquarters. The keynote starts at 10 am PDT on Tuesday, and as usual, it will be livestreamed.

Artificial intelligence can do just as well as humans, if not better, when it comes to persuading others in a debate, and not just because it cannot shout, a study has found. Experts say the results are concerning, not least as it has potential implications for election integrity. "If persuasive AI can be deployed at scale, you can imagine armies of bots microtargeting undecided voters, subtly nudging them with tailored political narratives that feel authentic," said Francesco Salvi, the first author of the research from the Swiss Federal Institute of Technology in Lausanne. He added that such influence was hard to trace, even harder to regulate and nearly impossible to debunk in real time. "I would be surprised if malicious actors hadn't already started to use these tools to their advantage to spread misinformation and unfair propaganda," Salvi said.

Their findings are the latest in a growing body of research demonstrating LLMs' powers of persuasion. The authors warn they show how AI tools can craft sophisticated, persuasive arguments if they have even minimal information about the humans they're interacting with. The research has been published in the journal Nature Human Behavior. "Policymakers and online platforms should seriously consider the threat of coordinated AI-based disinformation campaigns, as we have clearly reached the technological level where it is possible to create a network of LLM-based automated accounts able to strategically nudge public opinion in one direction," says Riccardo Gallotti, an interdisciplinary physicist at Fondazione Bruno Kessler in Italy, who worked on the project. "These bots could be used to disseminate disinformation, and this kind of diffused influence would be very hard to debunk in real time," he says.

Breakthroughs, discoveries, and DIY tips sent every weekday. Observing animals, especially other social primates, can be awe-inspiring. Seeing non-human species groom, feed, or socialize with their friends and kin echoes the best of our own impulses. It can feel affirming to know that, in many ways, they're like us. But, like humans, other primates are complicated.

Scanners were great … in 2005. These days, who has time--or desk space--for a chunky machine that you no longer need? There's a document-scanner app that does the same thing your old hunk of beef does, but it does the job even better. You can dodge the app's subscription fees with our lifetime offering: Use code SCAN at checkout to get it for 24.99 through June 1 (reg. If you can take a photo, you can scan documents with iScanner.

You've seen headlines about the market crash and maybe even wondered if now's your shot at finally investing. A stock-picking tool powered by OpenAI is helping regular folks identify strong opportunities with minimal risk. Meet Sterling Stock Picker, the thing that could turn your savings account into an early retirement, extra travel funds, or whatever you wish. Rather than gambling with your hard-earned dollars, this tool helps you research options that match your preferences and risk tolerance, and a lifetime subscription is just 55.19 (reg. Want to dive into the stock market but feel like you're reading a foreign language?

In this series of articles, we're publishing summaries with some of the key takeaways from a few of the workshops held at the 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025). Recent progress in Sphere Neural Networks demonstrates various possibilities for neural networks to achieve symbolic-level reasoning. This workshop aimed to reconsider various problems and discuss walk-round solutions in the two-way street commingling of neural networks and mathematics. This workshop brought together researchers from artificial intelligence and diverse scientific domains to address new challenges towards accelerating scientific discovery and engineering design. This was the fourth iteration of the workshop, with the theme of AI for biological sciences following previous three years' themes of AI for chemistry, earth sciences, and materials/manufacturing respectively.