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Category: robotics/AI – Page 1,588

Researchers use magnetic systems to artificially reproduce the learning and forgetting functions of the brain

With the advent of Big Data, current computational architectures are proving to be insufficient. Difficulties in decreasing transistors’ size, large power consumption and limited operating speeds make neuromorphic computing a promising alternative.

Neuromorphic computing, a new brain-inspired computation paradigm, reproduces the activity of biological synapses by using artificial neural networks. Such devices work as a system of switches, so that the ON position corresponds to the information retention or “learning,” while the OFF position corresponds to the information deletion or “forgetting.”

In a recent publication, scientists from the Universitat Autònoma de Barcelona (UAB), the CNR-SPIN (Italy), the Catalan Institute of Nanoscience and Nanotechnology (ICN2), the Institute of Micro and Nanotechnology (IMN-CNM-CSIC) and the ALBA Synchrotron have explored the emulation of artificial synapses using new advanced material devices. The project was led by Serra Húnter Fellow Enric Menéndez and ICREA researcher Jordi Sort, both at the Department of Physics of the UAB, and is part of Sofia Martins Ph.D. thesis.

What’s next for deep learning?

Deep learning is “a ball of mud accumulating all of AI,” says Amazon VP and distinguished scientist Nikko Ström. Integrating symbolic reasoning and learning eff… See more.

Integrating symbolic reasoning and learning efficiently from interactions with the world are two major remaining challenges, says vice president and distinguished scientist Nikko Ström.

Unbelievable New Chip Acts like a Human Brain

Scientists created a new type of Computer Chip which has the ability to constantly rewire itself just like the human brain and is thus able to more efficiently adapt to new processes. This is a new type of neuromorphic computing and holds great promise for future and better Artificial Intelligence models which more closely resemble how humans behave. You will not believe this unbelievable AI Robot Computer Chip!
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TIMESTAMPS:
00:00 A living Computer Chip.
01:32 How this new AI Chip works.
03:12 Does this Chip outperform Human Brains?
05:38 IBM’s return to Glory?
08:17 Last Words.
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#chip #ai #brain

China Is About to Regulate AI—and the World Is Watching

Bipartisan hostility toward China means US lawmakers are unlikely to cite Chinese regulations as inspiration. But Beijing’s manoeuvres could perhaps have a subtle effect. In the UK, some lawmakers have called for online companies to shield young people from harmful content in an approach that some have likened to China’s proposals. “These ideas could ripple out,” says Matt Sheehan, a fellow at the Carnegie Endowment for International Peace who researches China’s AI ecosystem. “What’s interesting in China is that they’re going to be able to run experiments at a very large scale on what it actually means to implement these ideas.”

Sweeping rules will cover algorithms that set prices, control search results, recommend videos, and filter content.

Scientists Are Data Mining Black Holes to See If They Are Holograms

There are few places in the universe that invite as much curiosity—and terror—as the interior of a black hole. These extreme objects exert such a powerful gravitational pull that not even light can escape them, a feature that has left many properties of black holes unexplained.

Now, a team led by Enrico Rinaldi, a research scientist at the University of Michigan, have used quantum computing and deep learning to probe the bizarre innards of black holes under the framework of a mind-boggling idea called holographic duality. This idea posits that black holes, or even the universe itself, might be holograms.

Physics Breakthrough as AI Successfully Controls Plasma in Nuclear Fusion Experiment

Successfully achieving nuclear fusion holds the promise of delivering a limitless, sustainable source of clean energy, but we can only realize this incredible dream if we can master the complex physics taking place inside the reactor.

For decades, scientists have been taking incremental steps towards this goal, but many challenges remain. One of the core obstacles is successfully controlling the unstable and super-heated plasma in the reactor – but a new approach reveals how we can do this.

In a joint effort by EPFL’s Swiss Plasma Center (SPC) and artificial intelligence (AI) research company DeepMind, scientists used a deep reinforcement learning (RL) system to study the nuances of plasma behavior and control inside a fusion tokamak – a donut-shaped device that uses a series of magnetic coils placed around the reactor to control and manipulate the plasma inside it.

Meta AI Researchers Upgrade Their Machine Learning-Based Image Segmentation Models For Better Virtual Backgrounds in Video Calls And Metaverse

When video chatting with colleagues, coworkers, or family, many of us have grown accustomed to using virtual backgrounds and background filters. It has been shown to offer more control over the surroundings, allowing fewer distractions, preserving the privacy of those around us, and even liven up our virtual presentations and get-togethers. However, Background filters don’t always work as expected or perform well for everyone.

Image segmentation is a computer vision process of separating the different components of a photo or video. It has been widely used to improve backdrop blurring, virtual backgrounds, and other augmented reality (AR) effects. Despite advanced algorithms, achieving highly accurate person segmentation seems challenging.

The model used for image segmentation tasks must be incredibly consistent and lag-free. Inefficient algorithms may result in bad experiences for the users. For instance, during a video conference, artifacts generated by erroneous segmentation output might easily confuse persons utilizing virtual background programs. More importantly, segmentation problems may result in unwanted exposure to people’s physical environments when applying backdrop effects.

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