Lifeboat Foundation

Guided by artificial intelligence and powered by a robotic platform, a system developed by MIT researchers moves a step closer to automating the production of small molecules. Images: Connor Coley, Felice Frankel.

The system, described in the August 8 issue of Science, could free up bench chemists from a variety of routine and time-consuming tasks, and may suggest possibilities for how to make new molecular compounds, according to the study co-leaders Klavs F. Jensen, the Warren K. Lewis Professor of Chemical Engineering, and Timothy F. Jamison, the Robert R. Taylor Professor of Chemistry and associate provost at MIT.

The technology “has the promise to help people cut out all the tedious parts of molecule building,” including looking up potential reaction pathways and building the components of a molecular assembly line each time a new molecule is produced, says Jensen.

Supersolids, solid materials with superfluid properties (i.e., in which a substance can flow with zero viscosity), have recently become the focus of numerous physics studies. Supersolids are paradoxical phases of matter in which two distinct and somewhat antithetical orders coexist, resulting in a material being both crystal and superfluid.

First predicted at the end of the 1960s, supersolidity has gradually become the focus of a growing number of research studies, sparking debate across different scientific fields. Several years ago, for instance, a team of researchers published controversial results that identified this phase in solid helium, which were later disclaimed by the authors themselves.

A key issue with this study was that it did not account for the complexity of helium and the unreliable observations that it can sometimes produce. In addition, in atoms, interactions are typically very strong and steady, which makes it harder for this phase to occur.

NASA and the Space Center Houston are seeking designs for autonomous robots that can explore the surface of the moon—and the leading one will win up to $1 million to continue research and discovery.

On Monday, the organizations announced Phase 2 of the NASA Space Robotics Challenge, focused on virtually designing autonomous robotic operations that allow the US to expand its ability to explore space and maintain its technological leadership.

SEE: Artificial intelligence: A business leader’s guide (free PDF) (TechRepublic)

Next week on board the International Space Station, Canada’s Dextre – the most sophisticated space robot ever built – will conduct tests to show how robots could refuel satellites and spacecraft in space! 🤖 🍁 Read the full story: http://www.asc-csa.gc.ca/eng/iss/news.asp.

Video: CSA

Before an A.I. system can learn, someone has to label the data supplied to it. Humans, for example, must pinpoint the polyps. The work is vital to the creation of artificial intelligence like self-driving cars, surveillance systems and automated health care.

Artificial intelligence is being taught by thousands of office workers around the world. It is not exactly futuristic work.

At iMerit offices in Kolkata, India, employees label images that are used to teach artificial intelligence systems. Credit Credit Rebecca Conway for The New York Times.

Data science is increasingly being used to compare products, find deals…

CAMBRIDGE, Mass. — Finding exoplanets marks just the beginning of what we can learn from these distant worlds, researchers said.

NEW YORK, Aug. 16, 2019 (GLOBE NEWSWIRE) — After a decade of anonymity, Satoshi Nakamoto will break his silence in Part I of his “My Reveal” Sunday, Aug. 18, at 4 p.m. EDT on the Satoshi Nakamoto Renaissance Holdings website, www.SatoshiNRH.com, and the Ivy McLemore & Associates website, www.ivymclemore.com.

A potentially useful material for building quantum computers has been unearthed at the National Institute of Standards and Technology (NIST), whose scientists have found a superconductor that could sidestep one of the primary obstacles standing in the way of effective quantum logic circuits.

Newly discovered properties in the compound uranium ditelluride, or UTe₂, show that it could prove highly resistant to one of the nemeses of quantum computer development — the difficulty with making such a computer’s memory storage switches, called qubits, function long enough to finish a computation before losing the delicate physical relationship that allows them to operate as a group. This relationship, called quantum coherence, is hard to maintain because of disturbances from the surrounding world.

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