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Solving ‘barren plateaus’ is the key to quantum machine learning

Many machine learning algorithms on quantum computers suffer from the dreaded “barren plateau” of unsolvability, where they run into dead ends on optimization problems. This challenge had been relatively unstudied—until now. Rigorous theoretical work has established theorems that guarantee whether a given machine learning algorithm will work as it scales up on larger computers.

“The work solves a key problem of useability for . We rigorously proved the conditions under which certain architectures of variational quantum algorithms will or will not have barren plateaus as they are scaled up,” said Marco Cerezo, lead author on the paper published in Nature Communications today by a Los Alamos National Laboratory team. Cerezo is a post doc researching at Los Alamos. “With our theorems, you can guarantee that the architecture will be scalable to quantum computers with a large number of qubits.”

“Usually the approach has been to run an optimization and see if it works, and that was leading to fatigue among researchers in the field,” said Patrick Coles, a coauthor of the study. Establishing mathematical theorems and deriving first principles takes the guesswork out of developing algorithms.

Researchers combines AI and robotic exoskeleton to make a self walking robotics exoskeleton

Robotics researchers are developing exoskeleton legs capable of thinking and making control decisions on their own using artificial intelligence called ExoNet

THE PROBLEM

Current generation of exoskeleton legs need to be manually controlled by users via smartphones or joysticks, It has a problem where motors need to change their operating mode manually when they perform a new activity in different terrains.

Five ways artificial intelligence can help space exploration

Do humans really have to go into space?


Artificial intelligence has been making waves in recent years, enabling us to solve problems faster than traditional computing could ever allow. Recently, for example, Google’s artificial intelligence subsidiary DeepMind developed AlphaFold2, a program which solved the protein-folding problem. This is a problem which has had baffled scientists for 50 years.

Advances in AI have allowed us to make progress in all kinds of disciplines – and these are not limited to applications on this planet. From designing missions to clearing Earth’s orbit of junk, here are a few ways artificial intelligence can help us venture further in space.

Do you remember Tars and Case, the assistant robots from the film Interstellar? While these robots don’t exist yet for real space missions, researchers are working towards something similar, creating intelligent assistants to help astronauts. These AI-based assistants, even though they may not look as fancy as those in the movies, could be incredibly useful to space exploration.

Fujitsu Leverages World’s Fastest Supercomputer and AI to Predict Tsunami Flooding

A new AI model that harnesses the power of the world’s fastest supercomputer, Fugaku, can rapidly predict tsunami flooding in coastal areas before the tsunami reaches land.

The development of the new technology was announced as part of a joint project between the International Research Institute of Disaster Science (IREDeS) at Tohoku University, the Earthquake Research Institute at the University of Tokyo, and Fujitsu Laboratories.

The 2011 Great East Japan Earthquake and subsequent tsunami highlighted the shortcomings in disaster mitigation and the need to utilize information for efficient and safe evacuations.

Nanotech scientists create world’s smallest origami bird

If you want to build a fully functional nanosized robot, you need to incorporate a host of capabilities, from complicated electronic circuits and photovoltaics to sensors and antennas.

But just as importantly, if you want your robot to move, you need it to be able to bend.

Cornell researchers have created micron-sized shape memory actuators that enable atomically thin two-dimensional materials to fold themselves into 3D configurations. All they require is a quick jolt of voltage. And once the material is bent, it holds its shape—even after the voltage is removed.

AI Can Now Debate with Humans and Sometimes Convince Them, Too

Today on the Science Talk podcast, Noam Slonim speaks to Scientific American about an impressive feat of computer engineering: an AI-powered autonomous system that can engage in complex debate with humans over issues ranging from subsidizing preschool and the merit of space exploration to the pros and cons of genetic engineering.

In a new Nature paper, Slonim and colleagues show that across 80 debate topics, Project Debater’s computational argument technology has performed very decently—with a human audience being the judge of that. “However, it is still somewhat inferior on average to the results obtained by expert human debaters,” says Slonim.

In a 2019 San Francisco showcase, its first public debut, the system went head to head with expert debater Harish Natarajan.