Lifeboat Foundation

Detecting extrasolar rocky planets capable of hosting life will depend in part on decoding their surface reflectivity and colors.

Zhou Yi was terrible at math. He risked never getting into college. Then a company called Squirrel AI came to his middle school in Hangzhou, China, promising personalized tutoring. He had tried tutoring services before, but this one was different: instead of a human teacher, an AI algorithm would curate his lessons. The 13-year-old decided to give it a try. By the end of the semester, his test scores had risen from 50% to 62.5%. Two years later, he scored an 85% on his final middle school exam.

“I used to think math was terrifying,” he says. “But through tutoring, I realized it really isn’t that hard. It helped me take the first step down a different path.”

Molecular dynamics is at the point of simulating bulk matter – but don’t expect it to predict the future.

The TV series Devs took as its premise the idea that a quantum computer of sufficient power could simulate the world so completely that it could project events accurately back into the distant past (the Crucifixion or prehistory) and predict the future. At face value somewhat absurd, the scenario supplied a framework on which to hang questions about determinism and free will (and less happily, the Many Worlds interpretation of quantum mechanics).

Quite what quantum computers will do for molecular simulations remains to be seen, but the excitement about them shouldn’t eclipse the staggering advances still being made in classical simulation. Full ab initio quantum-chemical calculations are very computationally expensive even with the inevitable approximations they entail, so it has been challenging to bring this degree of precision to traditional molecular dynamics, where molecular interactions are still typically described by classical potentials. Even simulating pure water, where accurate modelling of hydrogen bonding and the ionic disassociation of molecules involves quantum effects, has been tough.

Fault-tolerant logic gates will consume a large proportion of the resources of a two-dimensional quantum computing architecture. Here we show how to perform a fault-tolerant non-Clifford gate with the surface code; a quantum error-correcting code now under intensive development. This alleviates the need for distillation or higher-dimensional components to complete a universal gate set. The operation uses both local transversal gates and code deformations over a time that scales with the size of the qubit array. An important component of the gate is a just-in-time decoder. These decoding algorithms allow us to draw upon the advantages of three-dimensional models using only a two-dimensional array of live qubits. Our gate is completed using parity checks of weight no greater than four. We therefore expect it to be amenable with near-future technology. As the gate circumvents the need for magic-state distillation, it may reduce the resource overhead of surface-code quantum computation considerably.

A scalable quantum computer is expected to solve difficult problems that are intractable with classical technology. Scaling such a machine to a useful size will necessarily require fault-tolerant components that protect quantum information as the data is processed (1–4). If we are to see the realization of a quantum computer, its design must respect the constraints of the quantum architecture that can be prepared in the laboratory. In many cases, for instance, superconducting qubits (5–7), this restricts us to two-dimensional architectures.

Leading candidate models for fault-tolerant quantum computation are based on the surface code (3, 8) due to its high threshold (9) and multitude of ways of performing Clifford gates (10). Universal quantum computation is possible if this gate set is supplemented by a non-Clifford gate. Among the most feasible approaches to realize a non-Clifford gate is by the use of magic-state distillation (11). However, this is somewhat prohibitive as a large fraction of the resources of a quantum computer will be expended by these protocols (12, 13).

High-quality data is the fuel that powers AI algorithms. Without a continual flow of labeled data, bottlenecks can occur and the algorithm will slowly get worse and add risk to the system.

It’s why labeled data is so critical for companies like Zoox, Cruise and Waymo, which use it to train machine learning models to develop and deploy autonomous vehicles. That need is what led to the creation of Scale AI, a startup that uses software and people to process and label image, lidar and map data for companies building machine learning algorithms. Companies working on autonomous vehicle technology make up a large swath of Scale’s customer base, although its platform is also used by Airbnb, Pinterest and OpenAI, among others.

The COVID-19 pandemic has slowed, or even halted, that flow of data as AV companies suspended testing on public roads — the means of collecting billions of images. Scale is hoping to turn the tap back on, and for free.

The United States has secured almost a third of the first one billion doses planned for AstraZeneca’s experimental COVID-19 vaccine by pledging up to $1.2 billion, as world powers scramble for medicines to get their economies back to work.

While not proven to be effective against the coronavirus, vaccines are seen by world leaders as the only real way to restart their stalled economies, and even to get an edge over global competitors.

After President Donald Trump demanded a vaccine, the U.S. Department of Health agreed to provide up to US$1.2 billion to accelerate AstraZeneca’s vaccine development and secure 300 million doses for the United States.

A: No. Vaccines against pneumonia, such as pneumococcal vaccine and Haemophilus influenza type B (Hib) vaccine, do not provide protection against the new coronavirus. The virus is so new and different that it needs its own vaccine.

When pharmaceutical company Moderna issued a press release about the promising results of its Phase I clinical trial for a coronavirus vaccine, the media and the markets went wild. The New York Times ran a story that went viral on Twitter, racking up millions of views as social media influencers and doctors alike shared it far and wide. Moderna’s stock price shot up 20 percent and several peer companies like Novavax rallied even higher at more than 30 percent.

But was it justified?

The news cycle in the era of the coronavirus pandemic feels like tidal waves of hope and fear on steroids. Perhaps that’s because with more than 36 million Americans losing their jobs and more than 90,000 losing their lives, everyone is desperately looking for the light at the end of the tunnel. Covid-19 is taking an unprecedented physical and psychological toll on the American people and so small bits of potentially good news that should be taken with a grain of salt can end up dominating the headlines. People turn molehills into mountains because we really need and want a game-changer right now. But the truth is the truth regardless of what we want or feel, especially in science and medicine.

Two astronauts will lift off from Florida on Wednesday — the first time in nine years that humans have left Earth from US territory.

A review panel finds no technical reason to delay the first US orbital crew launch in nine years.