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 could 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 preferred 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, at present’s AI methods lack the type of reasoning, planning, and reminiscence wanted. It’s nonetheless early days for these methods, and there are numerous unsolved analysis questions. However who is aware of—perhaps for our tenth anniversary journey?
Deeper Studying
A approach to let robots study by listening will make them extra helpful
Most AI-powered robots at present 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 proscribed.
Sound on: Researchers at Stanford College examined how far more profitable a robotic might 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 battle 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 take a look at, 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. Learn extra from James O’Donnell.
Bits and Bytes
AI lie detectors are higher than people at recognizing liesResearchers on the College of Würzburg in Germany discovered that an AI system was considerably higher at recognizing fabricated statements than people. People often solely get it proper round half the time, however the AI might spot if a press release 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 should 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 inner 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 might steal the corporate’s know-how too. (The New York Instances)
AI has vastly elevated Google’s emissions over the previous 5 yearsGoogle mentioned 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 mentioned. That is largely as a consequence of Google’s monumental push towards AI, which can doubtless make it tougher to hit its objective 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 dwelling roomsAn attention-grabbing learn in regards to the shift taking place in AI and knowledge work. Scale AI has beforehand employed low-paid knowledge staff in international locations resembling India and the Philippines to annotate knowledge that’s used to coach AI. However the large 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 necessary knowledge work actually is to AI. (The Data)
A brand new “moral” AI music generator can’t write a midway respectable songCopyright is among the thorniest issues going through AI at present. Simply final week I wrote about how AI corporations are being compelled 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’s not in a position to generate something even near respectable. (Wired)