In the 1960s, an odd experiment showed planarian worms could transfer memories by consuming each other. It was a sensational finding--that is, until the worms stopped learning. It was the dead of winter in Boston. The surface of the Charles River was frozen solid. But Zachary Kelso braved the biting cold to finally put to rest a mystery that has haunted neuroscience labs for over half a century. To do that, Kelso, a research assistant in the Harvard lab of the neuroscientist Sam Gershman, needed some worms . Specifically, planarians: arrow-headed flatworms, which are among the simplest creatures to possess a brain and a nervous system with bilateral symmetry like ours. Normally, labs order these widely used model organisms from biological supply companies.

Things to Do in L.A. Tap to enable a layout that focuses on the article. JPL in limbo, Trump hovering: Caltech's alien-life-seeking chief takes over at a volatile time Ray Jayawardhana is the new president of Caltech. This is read by an automated voice. Please report any issues or inconsistencies here . See more from the L.A. Times in Google Search.

Look Up Gift Ideas For Everyone On Your List Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Mashable @Home In My Bag Safety Net Versus Trending Now Say More Creator Playbook Mashable Selects Getting Technical with Mashable All Series Apple'Pro and Tell' event: Everything announced so far, from iPad Mini to musical AI assistant Apple's M6 MacBook Pro and iMac are here, but John Ternus is still teasing more announcements. Chance Townsend is the General Assignments Editor at Mashable, covering tech, video games, dating apps, digital culture, and whatever else comes his way. He has a Master's in Journalism from the University of North Texas and is a proud orange cat father. His writing has also appeared in PC Mag and . Timothy Beck Werth is the Tech Editor at Mashable, where he leads coverage and assignments for the Tech and Shopping verticals. Tim has over 15 years of experience as a journalist and editor, and he has particular experience covering and testing consumer technology, smart home gadgets, and men's grooming and style products.

Systems that perform well in controlled lab settings often fall short when deployed in homes, in hospitals or on city streets. Vision-based systems, for example, hold promise for improving safety, monitoring health and aiding rehabilitation. For example, a camera-based system could help a clinician assess a patient's gait or rehabilitation progress. In the future, an assistive robot in an older adult's home might need to recognize when the person is struggling to stand or reaching for an object. But a major challenge is ensuring these robots perform reliably beyond the lab, particularly in messy, unpredictable or low-visibility conditions. As a computer scientist who studies AI systems designed to understand human behavior - especially through visual cues like body movements and interactions with objects - I see three main challenges to taking AI from the lab to the real world: generalization, human behavior and resources.

Just two boxes may hold 10 times more information than all the text on the internet, says Dr Oliver Vince, the facility's co-founder. His firm, Basecamp Research, plans to collect as much DNA as possible to create an artificial intelligence that can speak the language of biology, in the same way that US and Chinese tech firms have hoovered up written material online to create Large Language Models (LLMs), the basis of current AI systems. Vince, like many in business and academic research, believes AI will supercharge scientific research. But increasingly, it also comes with controversy. Last month, OpenAI, the creator of ChatGPT, said it had solved one of maths' great unsolved problems, relating to the famous Navier-Stokes equations.

Researchers get AI'drunk' to expose new cyber security risks in chatbots Fine-tuning large language models using drunken text makes them more likely to leak secrets and answer harmful questions, new UNSW-led research shows. UNSW researchers have shown that large language models (LLMs) can be pushed to imitate drunken behaviour - and that once they do, they are significantly more likely to leak confidential information and answer questions they are designed to refuse. In the study, conceptualised and led by Dr Aditya Joshi, Senior Lecturer, School of Computer Science and Engineering, with Anudeex Shetty (Research Assistant) and Professor Salil Kanhere, researchers from UNSW's School of Computer Science and Engineering (CSE) found that AI trained or prompted to mimic drunken speech patterns became more vulnerable to jailbreaking and privacy breaches than their'sober' counterparts. The UNSW team tested three methods of inducing'drunk' behaviour in LLMs. The vulnerability wasn't tested across every LLM on the market.

You're viewing the US edition You can switch to the UK, AU or IE homepage at any time using this menu. Jaw-dropping new photos reveal most detailed look yet at Taylor Swift's wedding: Inside the reception... her scrapped carousel plans... and how they hid elaborate planning for months Trump labels Norway'a sh*thouse country' after he was overlooked for Nobel Peace Prize again America's military bases prepare for 90-day doomsday scenario Leaked Pentagon group chat reveals vulgar nickname for Trump-pick Army chief: Read texts laying bare ugly new war at very top of Pete Hegseth's department Tiny New York village home to just 2,600 people declared the'nicest place in America' RICHARD KAY: What insiders told me about whether Royals will reach out to Meghan and Harry. It's an opportunity to reconcile but there are risks - and the Palace is scrambling Bryan Kohberger's'passionate' prison calls amid shocking new bid for freedom... inside killer's state of mind and his chilling optimism to ...

You're viewing the US edition You can switch to the UK, AU or IE homepage at any time using this menu. Jaw-dropping new photos reveal most detailed look yet at Taylor Swift's wedding: Inside the reception... her scrapped carousel plans... and how they hid elaborate planning for months Trump labels Norway'a sh*thouse country' after he was overlooked for Nobel Peace Prize again Miracle new'Ozempic of autism' drug cured my son's worst symptoms... just days after taking his first pill: Breakthrough treatment poised to explode across globe as clinical trial leader says he'almost fainted' at the results Tiny New York village home to just 2,600 people declared the'nicest place in America' RICHARD KAY: What insiders told me about whether Royals will reach out to Meghan and Harry. It's an opportunity to reconcile but there are risks - and the Palace is scrambling America's military bases prepare for 90-day doomsday scenario Bryan Kohberger's'passionate' prison calls amid shocking new bid ...

Claire chatted to Rika Antonova from the University of Cambridge about using artificial intelligence to develop complimentary robot hardware and algorithms. Rika Antonova is an Associate Professor at the University of Cambridge. Her research interests include co-design, automated algorithm discovery, data-efficient reinforcement learning, exploration, active learning, and robotics. After completing a research Master's degree at the Robotics Institute at Carnegie Mellon University and a PhD at KTH Royal Institute of Technology, Rika undertook a Computing Innovation Fellowship at Stanford University. Before that, she was a senior software engineer at Google.

AI is creating jobs as well as erasing them - but how rewarding are they? Don't believe the hype about AI taking over all forms of work . Most of the evidence to date suggests large-scale job losses are limited . But what is changing is the way work is organised. One area of increased employment is in people "cleaning up" after large language models (LLMs), or quality controlling them.