A year after it took biologists by surprise, AlphaFold has changed how researchers work and set DeepMind on a new course.
Category: robotics/AI – Page 1375
A new artificial intelligence program has beaten the world’s best players in the popular PlayStation racing game Gran Turismo Sport. But the impact could be felt far beyond that.
And it’s the size of a grain of dust. Energy storage might have been revolutionized thanks to a common dessert dish.
Advances in microelectronics have enabled the use of miniaturized computers for autonomous intelligence at the size of a dust particle less than one square millimeter across and a few hundred micrometers thick, creating an environment for ubiquitous computing. However, the size mismatch between microbatteries and microelectronics has emerged as a fundamental barrier against the take-off of tiny intelligent systems requiring power anytime anywhere. Mainstream microbattery structures include stacked thin films on the chip or electrode pillars and on-chip interdigitated microelectrodes. Nevertheless, available technologies cannot shrink the footprint area of batteries while maintaining adequate energy storage. Alternatively, the on-chip self-assembly process known as micro-origami is capable of winding stacked thin films into Swiss-roll structures to reduce the footprint area, which exactly mimics the manufacture of the most successful full-sized batteries—cylinder batteries. In addition to discussing in detail the technical difficulties of reducing the size of on-chip microbatteries with various structures and potential solutions, this Perspective highlights the following two basic requirements for eventual integration in microcomputers: minimum energy density of 100 microwatt-hour per square centimeter and monolithic integration with other functional electric circuits on the chip.
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?
Posted in robotics/AI
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.
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
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.
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.