Sooner or later, an AI agent couldn’t solely recommend issues to do and locations to remain on my honeymoon; it will additionally go a step additional than ChatGPT and e book flights for me. It will bear in mind my preferences and funds for inns and solely suggest lodging that matched my standards. It may additionally bear in mind what I appreciated to do on previous journeys, and recommend very particular issues to do tailor-made to these tastes. It’d even request bookings for eating places on my behalf.
Sadly for my honeymoon, in the present day’s AI methods lack the form of reasoning, planning, and reminiscence wanted. It’s nonetheless early days for these methods, and there are loads of unsolved analysis questions. However who is aware of—possibly for our tenth anniversary journey?
Deeper Studying
A solution to let robots study by listening will make them extra helpful
Most AI-powered robots in the present day use cameras to grasp their environment and study new duties, but it surely’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 way more profitable a robotic will 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 job, sounds supplied clues that cameras or tactile sensors wrestle with, like realizing if the eraser is correctly contacting the whiteboard or whether or not the cup incorporates cube. When utilizing imaginative and prescient alone within the final check, the robotic may inform 27% of the time whether or not there have been cube within the cup, however that rose to 94% when sound was included. Learn extra 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 may spot if an announcement was true or false in 67% of instances. Nonetheless, lie detection is a controversial and unreliable know-how, and it’s debatable whether or not we must always even be utilizing it within the first place. (MIT Expertise Evaluate)
A hacker stole secrets and techniques from OpenAI
A hacker managed to entry OpenAI’s inside messaging methods and steal details about its AI know-how. The corporate believes the hacker was a personal particular person, however the incident raised fears amongst OpenAI staff that China may steal the corporate’s know-how too. (The New York Occasions)
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 because of Google’s monumental push towards AI, which is able to probably make it more durable to hit its aim of eliminating carbon emissions by 2030. That is an totally 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 methods from their residing rooms
An attention-grabbing learn in regards to the shift taking place in AI and information work. Scale AI has beforehand employed low-paid information staff in international locations similar to India and the Philippines to annotate information that’s used to coach AI. However the large increase in language fashions has prompted Scale to rent extremely expert contractors within the US with the required experience to assist practice these fashions. This highlights simply how essential information work actually is to AI. (The Info)
A brand new “moral” AI music generator can’t write a midway respectable music
Copyright is likely one of the thorniest issues going through AI in the present day. Simply final week I wrote about how AI firms are being pressured to cough up for high-quality coaching information 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 information set of licensed music. However with out high-quality information, it’s not in a position to generate something even near respectable. (Wired)