Metaculus is a community dedicated to generating accurate predictions about future real-world events by aggregating the collective wisdom, insight, and intelligence of its participants.
Researchers at DeepMind in London have shown that artificial intelligence (AI) can find shortcuts in a fundamental type of mathematical calculation, by turning the problem into a game and then leveraging the machine-learning techniques that another of the company’s AIs used to beat human players in games such as Go and chess.
The AI discovered algorithms that break decades-old records for computational efficiency, and the team’s findings, published on 5 October in Nature1, could open up new paths to faster computing in some fields.
“It is very impressive,” says Martina Seidl, a computer scientist at Johannes Kepler University in Linz, Austria. “This work demonstrates the potential of using machine learning for solving hard mathematical problems.”
Accessing Wolfram|Alpha’s computational knowledge with ChatGPT—an ideal alliance of precise combination with human-like expression of ideas. Stephen Wolfram explains how.
𝐁𝐫𝐚𝐢𝐧 𝐀𝐫𝐞𝐚 𝐍𝐞𝐜𝐞𝐬𝐬𝐚𝐫𝐲 𝐟𝐨𝐫 𝐅𝐥𝐮𝐢𝐝 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐈𝐝𝐞𝐧𝐭𝐢𝐟𝐢𝐞𝐝 — 𝐃𝐞𝐟𝐢𝐧𝐢𝐧𝐠 𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐨𝐟 𝐇𝐮𝐦𝐚𝐧 𝐂𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧
𝘼 𝙩𝙚𝙖𝙢 𝙡𝙚𝙙 𝙗𝙮 𝙐𝙣𝙞𝙫𝙚𝙧𝙨𝙞𝙩𝙮 𝘾𝙤𝙡𝙡𝙚𝙜𝙚 𝙇𝙤𝙣𝙙𝙤𝙣 (𝙐𝘾𝙇) 𝙖𝙣𝙙 𝙐𝙣𝙞𝙫𝙚𝙧𝙨𝙞𝙩𝙮 𝘾𝙤𝙡𝙡𝙚𝙜𝙚 𝙇𝙤𝙣𝙙𝙤𝙣 𝙃𝙤𝙨𝙥𝙞𝙩𝙖𝙡𝙨 (𝙐𝘾𝙇𝙃) 𝙧𝙚𝙨𝙚𝙖𝙧𝙘𝙝𝙚𝙧𝙨 𝙝𝙖𝙨 𝙢𝙖𝙥𝙥𝙚𝙙 𝙩𝙝𝙚 𝙥𝙖𝙧𝙩𝙨 𝙤𝙛 𝙩𝙝𝙚 𝙗𝙧𝙖𝙞𝙣 𝙩𝙝𝙖𝙩 𝙨𝙪𝙥𝙥𝙤𝙧𝙩 𝙤𝙪𝙧 𝙖𝙗𝙞𝙡𝙞𝙩𝙮 𝙩𝙤 𝙨𝙤𝙡𝙫𝙚 𝙥𝙧𝙤𝙗𝙡𝙚𝙢𝙨 𝙬𝙞𝙩𝙝𝙤𝙪𝙩 𝙥𝙧𝙞𝙤𝙧 𝙚𝙭𝙥𝙚𝙧𝙞𝙚𝙣𝙘𝙚 — 𝙤𝙩𝙝𝙚𝙧𝙬𝙞𝙨𝙚 𝙠𝙣𝙤𝙬𝙣 𝙖𝙨 𝙛𝙡𝙪𝙞𝙙 𝙞𝙣𝙩𝙚𝙡𝙡𝙞𝙜𝙚𝙣𝙘𝙚. 𝙁𝙡𝙪𝙞𝙙 𝙞𝙣𝙩𝙚𝙡𝙡𝙞𝙜𝙚𝙣𝙘𝙚 𝙞𝙨 𝙖𝙧𝙜𝙪𝙖𝙗𝙡𝙮 𝙩𝙝𝙚 𝙙𝙚𝙛𝙞𝙣𝙞𝙣𝙜 𝙛𝙚𝙖𝙩𝙪𝙧𝙚 𝙤𝙛 𝙝𝙪𝙢𝙖𝙣 𝙘𝙤𝙜𝙣𝙞𝙩𝙞𝙤𝙣. 𝙄𝙩 𝙥𝙧𝙚𝙙𝙞𝙘𝙩𝙨 𝙚𝙙𝙪𝙘𝙖𝙩𝙞𝙤𝙣𝙖𝙡 𝙖𝙣𝙙 𝙥𝙧𝙤𝙛𝙚𝙨𝙨𝙞𝙤𝙣𝙖𝙡 𝙨𝙪𝙘𝙘𝙚𝙨𝙨, 𝙨𝙤𝙘𝙞𝙖𝙡 𝙢𝙤𝙗𝙞𝙡𝙞𝙩𝙮, 𝙝𝙚𝙖𝙡𝙩𝙝, 𝙖𝙣𝙙 𝙡𝙤𝙣𝙜𝙚𝙫𝙞𝙩𝙮. 𝙄𝙩 𝙖𝙡𝙨𝙤 𝙘𝙤𝙧𝙧𝙚𝙡𝙖𝙩𝙚𝙨 𝙬𝙞𝙩𝙝 𝙢𝙖𝙣𝙮 𝙘𝙤𝙜𝙣𝙞𝙩𝙞𝙫𝙚 𝙖𝙗𝙞𝙡𝙞𝙩𝙞𝙚𝙨 𝙨𝙪𝙘𝙝 𝙖𝙨 𝙢𝙚𝙢𝙤𝙧𝙮.
A team led by University College London (UCL) and University College London Hospitals (UCLH) researchers has mapped the parts of the brain that support our ability to solve problems without prior experience – otherwise known as fluid intelligence.
This Video Explains piRNA (piwi Interacting RNA)
Reference: https://www.researchgate.net/figure/Mechanisms-of-regulation…_326569449
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I n 2017, Andhra Pradesh witnessed two deadly bus accidents after the driver fell asleep at the wheel. One was a tourist bus and the other a school bus carrying children and teachers.
This news concerned Pradeep Varma (22), a student of Gayatri Vidya Parishad College of Engineering, Visakhapatnam. It left him wondering why there was no technology in place to prevent such accidents.
“After doing some research, I realised that while there is technology to detect external crashes and predict them, there aren’t many prevalent ones to detect a driver falling asleep,” says Pradeep, in an interview with The Better India.
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New research may have vital applications in areas such as human-intelligence analytics. Traditionally, emotion detection has relied on the assessment of visible signals such as facial expressions, speech, body gestures or eye movements. However, these methods can be unreliable as they do not effectively capture an individual’s internal emotions. A novel artificial intelligence approach based on wireless signals could help to reveal our inner emotions.
The research from Queen Mary University of London demonstrates the use of radio waves to measure heart rate and breathing signals and predict how someone is feeling even in the absence of any other visual cues, such as facial expressions. It demonstrates how to apply a neural network to decipher emotions gathered with transmitting radio antenna.
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Microsoft has revealed VALL-E, an artificial intelligence that can replicate any voice using a three-second sample. It has huge potential — and huge risks too.
Some predict that in the future we’ll work in virtual worlds, but others are not convinced.
