Sooner or later, an AI agent couldn’t solely recommend issues to do and locations to remain on my honeymoon; it could additionally go a step additional than ChatGPT and ebook flights for me. It could bear in mind my preferences and finances for lodges and solely suggest lodging that matched my standards. It may also bear in mind what I favored to do on previous journeys, and recommend very particular issues to do tailor-made to these tastes. It would even request bookings for eating places on my behalf.
Sadly for my honeymoon, at the moment’s AI programs lack the form of reasoning, planning, and reminiscence wanted. It’s nonetheless early days for these programs, and there are quite a lot of unsolved analysis questions. However who is aware of—perhaps for our tenth anniversary journey?
Deeper Studying
A strategy to let robots study by listening will make them extra helpful
Most AI-powered robots at the moment use cameras to grasp their environment and study new duties, however it’s changing into simpler to coach robots with sound too, serving to them adapt to duties and environments the place visibility is restricted.
Sound on: Researchers at Stanford College examined how rather more profitable a robotic could be if it’s able to “listening.” They selected 4 duties: flipping a bagel in a pan, erasing a whiteboard, placing two Velcro strips collectively, and pouring cube out of a cup. In every activity, sounds supplied clues that cameras or tactile sensors wrestle with, like understanding if the eraser is correctly contacting the whiteboard or whether or not the cup comprises cube. When utilizing imaginative and prescient alone within the final check, the robotic might inform 27% of the time whether or not there have been cube within the cup, however that rose to 94% when sound was included. Read more from James O’Donnell.
Bits and Bytes
AI lie detectors are higher than people at recognizing lies
Researchers on the College of Würzburg in Germany discovered that an AI system was considerably higher at recognizing fabricated statements than people. People normally solely get it proper round half the time, however the AI might spot if an announcement was true or false in 67% of instances. Nonetheless, lie detection is a controversial and unreliable expertise, and it’s debatable whether or not we must always even be utilizing it within the first place. (MIT Technology Review)
A hacker stole secrets and techniques from OpenAI
A hacker managed to entry OpenAI’s inside messaging programs and steal details about its AI expertise. The corporate believes the hacker was a personal particular person, however the incident raised fears amongst OpenAI workers that China might steal the corporate’s expertise too. (The New York Times)
AI has vastly elevated Google’s emissions over the previous 5 years
Google stated its greenhouse-gas emissions totaled 14.3 million metric tons of carbon dioxide equal all through 2023. That is 48% greater than in 2019, the corporate stated. That is principally resulting from Google’s huge push towards AI, which can possible make it more durable to hit its objective of eliminating carbon emissions by 2030. That is an completely miserable instance of how our societies prioritize revenue over the local weather emergency we’re in. (Bloomberg)
Why a $14 billion startup is hiring PhDs to coach AI programs from their dwelling rooms
An attention-grabbing learn in regards to the shift occurring in AI and knowledge work. Scale AI has beforehand employed low-paid knowledge staff in nations reminiscent of India and the Philippines to annotate knowledge that’s used to coach AI. However the huge growth in language fashions has prompted Scale to rent extremely expert contractors within the US with the required experience to assist prepare these fashions. This highlights simply how essential knowledge work actually is to AI. (The Information)
A brand new “moral” AI music generator can’t write a midway respectable track
Copyright is among the thorniest problems dealing with AI at the moment. Simply final week I wrote about how AI companies are being forced to cough up for high-quality coaching knowledge to construct highly effective AI. This story illustrates why this issues. This story is about an “moral” AI music generator, which solely used a restricted knowledge set of licensed music. However with out high-quality knowledge, it isn’t capable of generate something even near respectable. (Wired)
