\u2014James O’Donnell<\/p>\n
Digital clones\u2014AI models that replicate a specific person\u2014package together a few technologies that have been around for a while now: hyperrealistic video models to match your appearance, lifelike voices based on just a couple of minutes of speech recordings, and conversational chatbots increasingly capable of holding our attention.\u00a0<\/p>\n
But they\u2019re also offering something the ChatGPTs of the world cannot: an AI that\u2019s not smart in the general sense, but that \u2018thinks\u2019 like you do.<\/p>\n
Could well-crafted clones serve as our stand-ins? I certainly feel stretched thin at work sometimes, wishing I could be in two places at once, and I bet you do too. To find out, I tried making a clone of myself. Read the full story to find out how it got on<\/a>.<\/p>\n This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here<\/a>.<\/p>\n How lidar measures the cost of climate disasters<\/p>\n The wildfires that swept through Los Angeles County this January left an indelible mark on the Southern California landscape. The Eaton and Palisades fires raged for 24 days, killing 29 people and destroying 16,000 structures, with losses estimated at $60 billion. More than 55,000 acres were consumed, and the landscape itself was physically transformed.<\/p>\n Now, researchers are using lidar (light detection and ranging) technology to precisely measure these changes in the landscape\u2019s geometry\u2014helping them understand and track the cascading effects of climate disasters. Read the full story<\/a>.
\u2014Jon Keegan<\/p>\n