Lifeboat Foundation

ASML’s machine has effectively turned into a choke point in the supply chain for chips, which act as the brains of computers and other digital devices. The tool’s three-continent development and production — using expertise and parts from Japan, the United States and Germany — is also a reminder of just how global that supply chain is, providing a reality check for any country that wants to leap ahead in semiconductors by itself.

A $150 million chip-making tool from a Dutch company has become a lever in the U.S.-Chinese struggle. It also shows how entrenched the global supply chain is.

A new wave of startups are using deep learning to build synthetic voice actors for digital assistants, video-game characters, and corporate videos.

A group of mathematicians has shown that at critical moments, a symmetry called rotational invariance is a universal property across many physical systems.

Great Discoveries Channel

A Dangerous AI and Robot Dance, with Elon Musk, Tom Scott & Pissbot (aka Boston Dynamics’ Spot).

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After focusing for decades on cutting costs, the solar industry is shifting attention to making new advances in technology.

Team develops simulator with 256 qubits, largest of its kind ever created.

A team of physicists from the Harvard-MIT Center for Ultracold Atoms and other universities has developed a special type of quantum computer known as a programmable quantum simulator capable of operating with 256 quantum bits, or “qubits.”

The system marks a major step toward building large-scale quantum machines that could be used to shed light on a host of complex quantum processes and eventually help bring about real-world breakthroughs in material science, communication technologies, finance, and many other fields, overcoming research hurdles that are beyond the capabilities of even the fastest supercomputers today. Qubits are the fundamental building blocks on which quantum computers run and the source of their massive processing power.

Artificial intelligence (AI) is able to recognize the biological activity of natural products in a targeted manner, as researchers at ETH Zurich have demonstrated. Moreover, AI helps to find molecules that have the same effect as a natural substance but are easier to manufacture. This opens up huge possibilities for drug discovery, which also has potential to rewrite the rulebook for pharmaceutical research.

Nature has a vast store of medicinal substances. “Over 50 percent of all drugs today are inspired by nature,” says Gisbert Schneider, Professor of Computer-Assisted Drug Design at ETH Zurich. Nevertheless, he is convinced that we have tapped only a fraction of the potential of natural products. Together with his team, he has successfully demonstrated how artificial intelligence (AI) methods can be used in a targeted manner to find new pharmaceutical applications for natural products. Furthermore, AI methods are capable of helping to find alternatives to these compounds that have the same effect but are much easier and therefore cheaper to manufacture.

And so the ETH researchers are paving the way for an important medical advance: we currently have only about 4000 basically different medicines in total. In contrast, estimates of the number of human proteins reach up to 400000, each of which could be a target for a drug. There are good reasons for Schneider’s focus on nature in the search for new pharmaceutical agents. “Most natural products are by definition potential active ingredients that have been selected via evolutionary mechanisms,” he says.

What will ESA’s EnVision mission to Venus add to the growing number of spacecraft investigating our sister planet?