Neuronal ensembles in the mouse insular cortex activated during distinct inflammatory conditions are capable of retrieving or suppressing the associated peripheral immunological responses.
Rich dynamics in a living neuronal system can be considered as a computational resource for physical reservoir computing (PRC). However, PRC that generates a coherent signal output from a spontaneously active neuronal system is still challenging. To overcome this difficulty, we here constructed a closed-loop experimental setup for PRC of a living neuronal culture, where neural activities were recorded with a microelectrode array and stimulated optically using caged compounds. The system was equipped with first-order reduced and controlled error learning to generate a coherent signal output from a living neuronal culture. Our embodiment experiments with a vehicle robot demonstrated that the coherent output served as a homeostasis-like property of the embodied system from which a maze-solving ability could be generated. Such a homeostatic property generated from the internal feedback loop in a system can play an important role in task solving in biological systems and enable the use of computational resources without any additional learning.
The World Food Programme (WFP), the UN’s food assistance arm, outlined how $6.6 billion in investments might prevent 42 million people in 43 countries from becoming hungry. In a tweet outlining the plan, WFP President David Beasley singled out Musk, the world’s wealthiest individual by far.
Google is secretly working on some of the most advanced and crazy-sounding Artificial Intelligence Systems in the world. Some of them they’ve announced and released to the public, while others are being worked on behind closed curtains.
What these secret AI Projects are, what evil, bad or good things they’ll accomplish and how Googles motto of “Don’t be evil” doesn’t apply anymore, all in this one video. One thing is for sure, this might be the dawn of super intelligent AI robots owned by a single company in the hopes of reaching AI Supremacy.
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TIMESTAMPS:
00:00 Don’t be evil.
01:32 Google and Deepmind.
03:26 Google’s Connections with the Military.
04:39 What is Googles plan?
07:21 Last Words.
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#robots #ai #google
SpaceX plans to launch a staggering number of rockets next year, helping to reach CEO Elon Musk’s goal of completing 48 launches in one year.
A group of scientists at the U.S. Department of Energy’s Ames Laboratory has developed computational quantum algorithms that are capable of efficient and highly accurate simulations of static and dynamic properties of quantum systems. The algorithms are valuable tools to gain greater insight into the physics and chemistry of complex materials, and they are specifically designed to work on existing and near-future quantum computers.
Scientist Yong-Xin Yao and his research partners at Ames Lab use the power of advanced computers to speed discovery in condensed matter physics, modeling incredibly complex quantum mechanics and how they change over ultra-fast timescales. Current high performance computers can model the properties of very simple, small quantum systems, but larger or more complex systems rapidly expand the number of calculations a computer must perform to arrive at an accurate model, slowing the pace not only of computation, but also discovery.
“This is a real challenge given the current early-stage of existing quantum computing capabilities,” said Yao, “but it is also a very promising opportunity, since these calculations overwhelm classical computer systems, or take far too long to provide timely answers.”
There are no greater bragging rights in supercomputing than those that come with top ten listing on the bi-annual list of the world’s most powerful systems—the Top 500. And there are no countries more inclined to throw themselves (and billions) into that competition this decade than the U.S. and China.
Today, the latest results were announced (much more on those here) but notably absent, aside from the expected first exascale machine in the U.S., “Frontier” at Oak Ridge National Laboratory in the U.S., are China’s results, which if published, would have shown two separate exascale-class machines.
This would have been a major mainstream news story had China decided to publicize its results–and on several fronts.
IBM says it has built a quantum processor that it says cannot be simulated by a classical computer.
If true, the processor would represent a major breakthrough in quantum computing, which its proponents say could lead to radical changes in how we are able to deal with information.
The company says that the quantum processor is so capable that to simulate its capabilities with a traditional computer, one would require more bits than there are atoms in every person in existence.
