Five million people are employed in the fast food industry in the U.S. alone, but their tasks are monotonous and easily automated.
Bei einem Experiment in der Antarktis haben Forscher Teilchen beobachtet, die ein Beweis für eine alternative Realität sein könnten.
Google’s Deepmind is working on a rather crazy and unique plan to surpass OpenAI’s biggest and best Artificial Intelligence Model within the next few months. In a new paper, AI researchers at DeepMind present a new technique to improve the capacity of reinforcement learning agents to cooperate with humans at different skill levels. Accepted at the annual NeurIPS conference, the technique is called Fictitious Co-Play (FCP) and it does not require human-generated data to train the RL agents.
–
TIMESTAMPS:
00:00 How Deepmind is ahead of OpenAI
01:45 Why this AI is similar to our Brain.
04:17 New AI Features and Abilities.
06:36 How successful was this AI?
08:58 The Future of AI
10:13 Last Words.
–
#ai #agi #deepmind
Computer simulations and visualizations of knots and other objects have long helped mathematicians to look for patterns and develop their intuition, says Jeffrey Weeks, a mathematician based in Canton, New York, who has pioneered some of those techniques since the 1980s. But, he adds, “Getting the computer to seek out patterns takes the research process to a qualitatively different level.”
The authors say the approach, described in a paper in the 2 December issue of Nature1, could benefit other areas of maths that involve large data sets.
Amazon Scholars Michael I. Jordan and Michael Kearns, and Amazon vice president and distinguished scientist Bernhard Schölkopf discuss the future of AI ahead of NeurIPS 2021. Watch the recorded event where these industry luminaries cover a range of topics including the history of ML in the past decade, its social impacts, the role of causal reasoning in ML, and whether or not autonomous, general-purpose intelligence should really be the aim of AI.
Follow us:
Website: https://www.amazon.science.
Twitter: https://twitter.com/AmazonScience.
Facebook: https://www.facebook.com/AmazonScience.
Instagram: https://www.instagram.com/AmazonScience.
LinkedIn: https://www.linkedin.com/showcase/AmazonScience.
Newsletter: https://www.amazon.science/newsletter.
#AmazonScience #NeurIPS #NeurIPS2021 #ArtificialIntelligence #MachineLearning #AI #ML
Amazon has launched a new secrets detection feature that automatically finds private system credentials “hidden” in public source code.
Forget about Mark Zuckerberg, Facebook and all the talk about a metaverse. The real future will be a world that is convenient and scary and fantastical — at least according to futurologists. As this year ends, here’s a glimpse at what life might be like … one day.
Facial recognition is already common for phones, but “In 30 years it’s quite possible that you will not use a key or even a credit card. You’ll use your face or iris to make purchases and open locks. Recognition will be that good,” said Martin Ford, author of “Rule of the Robots: How Artificial Intelligence will Transform Everything.”
“The scary thing, though, will be if someone hacks your biometric data. Right now you can call the bank to change your pin or cancel a credit card. But you can’t cancel your biometrics.”
We can add suggesting and proving mathematical theorems to the long list of what artificial intelligence is capable of: Mathematicians and AI experts have teamed up to demonstrate how machine learning can open up new avenues to explore in the field.
While mathematicians have been using computers to discover patterns for decades, the increasing power of machine learning means that these networks can work through huge swathes of data and identify patterns that haven’t been spotted before.
In a newly published study, a research team used artificial intelligence systems developed by DeepMind, the same company that has been deploying AI to solve tricky biology problems and improve the accuracy of weather forecasts, to unknot some long-standing math problems.
Clearview AI is about to get formal acknowledgment for its controversial facial recognition technology. Politico reports Clearview has received a US Patent and Trademark Office “notice of allowance” indicating officials will approve a filing for its system, which scans faces across public internet data to find people from government lists and security camera footage. The company just has to pay administrative fees to secure the patent.
In a Politico interview, Clearview founder Hoan Ton-That claimed this was the first facial recognition patent involving “large-scale internet data.” The firm sells its tool to government clients (including law enforcement) hoping to accelerate searches.
As you might imagine, there’s a concern the USPTO is effectively blessing Clearview’s technology and giving the company a chance to grow despite widespread objections to its technology’s very existence. Critics are concerned Clearview is building image databases without targets’ knowledge or permission, and multiple governments (including Australia and the UK) believe the facial recognition violates data laws. The tech could theoretically be used to stifle political dissent or, in private use, to stalk other people. That’s not including worries about possible gender and race biases for facial recognition as a whole.
Scientific ingenuity means cameras keep on getting smaller and smaller, and the latest to appear is not only incredibly tiny – the same size as a grain of salt – it’s also able to produce images of much better quality than a lot of other ultra-compact cameras.
Using a technology known as a metasurface, which is covered with 1.6 million cylindrical posts, the camera is able to capture full-color photos that are as good as images snapped by conventional lenses some half a million times bigger than this particular camera.
And the super-small contraption has the potential to be helpful in a whole range of scenarios, from helping miniature soft robots explore the world, to giving experts a better idea of what’s going on deep inside the human body.
Prof Stuart Russell, founder of the Center for Human-Compatible Artificial Intelligence, at the University of California, Berkeley, is giving this year’s Reith Lectures.
He said: Because I think it’s really important and really urgent.
And the reason it’s urgent is because the weapons that we have been talking about for the last six years or seven years are now starting to be manufactured and sold.
So in 2017, for example, we produced a movie called Slaughterbots about a small quadcopter about 3in [8cm] in diameter that carries an explosive charge and can kill people by getting close enough to them to blow up.
We showed this first at diplomatic meetings in Geneva and I remember the Russian ambassador basically sneering and sniffing and saying: “Well, you know, this is just science fiction, we don’t have to worry about these things for 25 or 30 years.”
