Lifeboat Foundation

Like every other major tech company, Google has designs on being the first to achieve quantum supremacy — the point where a quantum computer could run particular algorithms faster than a classical computer. Today it’s announced that it believes its latest research, Bristlecone, is going to be the processor to help it achieve that. According to the Google Quantum AI Lab, it could provide “a compelling proof-of-principle for building larger scale quantum computers.”

One of the biggest obstacles to quantum supremacy is error rates and subsequent scalability. Qubits (the quantum version of traditional bits) are very unstable and can be adversely affected by noise, and most of these systems can only hold a state for less than 100 microseconds. Google believes that quantum supremacy can be “comfortably demonstrated” with 49 qubits and a two-qubit error below 0.5 percent. Previous quantum systems by Google have given two-qubit errors of 0.6 percent, which in theory sounds like a miniscule difference, but in the world of quantum computing remains significant.

However, each Bristlecone chip features 72 qubits, which may help mitigate some of this error, but as Google says, quantum computing isn’t just about qubits. “Operating a device such as Bristlecone at low system error requires harmony between a full stack of technology ranging from software and control electronics to the processor itself,” the team writes in a blog post. “Getting this right requires careful systems engineering over several iterations.”

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Researchers in Oregon State University’s College of Engineering have taken a key step toward the rapid manufacture of flexible computer screens and other stretchable electronic devices, including soft robots.

The advance by a team within the college’s Collaborative Robotics and Intelligent Systems Institute paves the way toward the 3D printing of tall, complicated structures with a highly conductive gallium alloy.

Researchers put nickel nanoparticles into the liquid metal, galinstan, to thicken it into a paste with a consistency suitable for additive manufacturing.

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China is intensifying its push into space, and broadening its astronaut recruiting.

The Chinese government, which plans to increase the number of manned missions in its military-backed space program to around two a year, will soon begin recruiting civilian astronauts, Yang Liwei, deputy director of the China Manned Space Engineering Office, told reporters on the sidelines of a ceremonial parliament session this weekend. That’s a departure from China’s practice of drawing its astronauts from among air force pilots.

Yang—who was China’s first man in space in 2003—said the trainees could include private-sector maintenance engineers, payload specialists, pilots, scientists, and people from universities and other research institutions, according to the Associated Press. More women are also being encouraged to apply. The loosening of restrictions comes amid NASA’s announcement that it has recruited America’s most competitive class of astronauts ever, as well as other initiatives like Canada’s Hunger Games -style search for new astronauts on the internet.

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Engineering pioneer will produce 3 vehicles from scratch in bold £2 billion venture, Financial Times reports.

Although mobile devices such as tablets and smartphones let us communicate, work and access information wirelessly, their batteries must still be charged by plugging them in to an outlet. But engineers at the University of Washington have for the first time developed a method to safely charge a smartphone wirelessly using a laser.

As the team reports in a paper published online in December in the Proceedings of the Association for Computing Machinery on Interactive, Mobile, Wearable & Ubiquitous Technologies, a narrow, invisible beam from a laser emitter can deliver charge to a smartphone sitting across a room — and can potentially charge a smartphone as quickly as a standard USB cable. To accomplish this, the team mounted a thin power cell to the back of a smartphone, which charges the smartphone using power from the laser. In addition, the team custom-designed safety features — including a metal, flat-plate heatsink on the smartphone to dissipate excess heat from the laser, as well as a reflector-based mechanism to shut off the laser if a person tries to move in the charging beam’s path.

“Safety was our focus in designing this system,” said co-author Shyam Gollakota, an associate professor in the UW’s Paul G. Allen School of Computer Science & Engineering. “We have designed, constructed and tested this laser-based charging system with a rapid-response safety mechanism, which ensures that the laser emitter will terminate the charging beam before a person comes into the path of the laser.”

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When the Chinese government released its Next Generation Artificial Intelligence Plan in July 2017, it crisply articulated the country’s ambition: to become the “world’s primary AI innovation center” by 2030. That headline goal turned heads within the global tech elite. Longtime Google CEO Eric Schmidt cited the plan as proof that China threatened to overtake the United States in AI. High-ranking American military leaders and AI entrepreneurs held it up as evidence that the United States was falling behind in the “space race” of this century. In December 2017, China’s Ministry of Industry and Information Technology followed up with a “three-year action plan,” a translation of which was recently released by New America’s DigiChina initiative.

But how do these plans actually work? There’s a tendency to place this AI mobilization within China’s longstanding tradition of centrally planned engineering achievements that have wowed the world. The rapid build-out of the country’s bullet train network stands as a monument to the power of combining central planning and deep pockets: in the span of a decade, the Chinese central government spent around $360 billion building 13,670 miles of high-speed rail (HSR) track, more mileage than the rest of the world combined.

But putting the AI plan in this tradition can be misleading. While it follows this model in form (ambitious goal set by the central government), it differs in function (what will actually drive the transformation). The HSR network was dreamed up and drawn up by central government officials, and largely executed by state-owned enterprises. In AI, the real energy is and will be with private technology companies, and to a lesser extent academia.

Scientists have been culturing meat in labs for years, but Just and other startups like Finless Foods, which is growing fish meat, have been feverishly pursuing this so-called “clean meat” of late. Just is chasing a cultured chorizo and a cultured nugget in addition to the foie gras. And Tetrick claims his startup has finally made the process cost-effective enough to take to market: At the end of this year, he says, Just will officially introduce an as yet undisclosed lab-grown meat, the first time the stuff will hit shelves.

The challenges of engineering meat in the lab is one thing, but convincing consumers to turn away from the storied kill-it-and-grill-it method of eating is another. And while it’s easy to imagine how lab-grown meat would be better for the planet, there’s actually little data to back that up.

Whether or not Just makes it to market this year, and whether or not their meat tastes and smells and feels like meat, the era of clean meat is approaching. (Just declined to let us taste their food, saying it wasn’t ready for public consumption.) Soon enough, burgers will grow not just in fields, but in vats. Farther down the line, your T-bones may not come from a cow, at least not in the traditional sense. If the sound of that bothers you, know that you’re not alone.

MIT 6.S099: Artificial General Intelligence class takes an engineering approach to exploring possible research paths toward building human-level intelligence. The lectures introduce our current understanding of computational intelligence and ways in which strong AI could possibly be achieved, with insights from deep learning, reinforcement learning, computational neuroscience, robotics, cognitive modeling, psychology, and more.

Lex Fridman

Continue reading “Future of Intelligence (Ray Kurzweil)” »

Zoom in close on the center of the picture above, and you can spot something you perhaps never thought you’d be able to see: a single atom. Here is a close-up if, you’re having trouble:

This strontium atom is emitting light after being excited by a laser, and it’s the winner of the UK’s Engineering and Physical Sciences Research Council (EPSRC) photography award. The EPSRC announced the winners of its fifth annual contest yesterday. Winning photographer David Nadlinger, graduate student at the University of Oxford, was just excited to be able to show off his research.

“It’s exciting to find a picture that resonates with other people that shows what I spend my days and nights working on,” Nadlinger told me. The best part, to him, was “the opportunity to excite people about my research, more than winning a competition.”

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