Lifeboat Foundation

This innovation drive, including increasing use of automation on farms like Dijkstra’s, has helped propel a country with a land mass smaller than the state of West Virginia to become the world’s second-biggest food exporter after the U.S., with agri-food exports worth more than $100 billion.

And it’s dairy, and fruit and vegetables ― where technologies like milking and harvesting robots are becoming commonplace in the Netherlands ― that account for the biggest share of that export revenue.

“Automation has been part of that success story,” said Erik Nicholson of the United Farm Workers of America. The Netherlands “is seen as a world leader because of the innovation going on there and the output it manages despite its comparatively small size.”

More broadly, biologists are wondering how else deep learning — the AI technique used by both approaches — might be applied to the prediction of protein arrangements, which ultimately dictate a protein’s function. These approaches are cheaper and faster than existing lab techniques such as X-ray crystallography, and the knowledge could help researchers to better understand diseases and design drugs. “There’s a lot of excitement about where things might go now,” says John Moult, a biologist at the University of Maryland in College Park and the founder of the biennial competition, called Critical Assessment of protein Structure Prediction (CASP), where teams are challenged to design computer programs that predict protein structures from sequences.

Deep learning makes its mark on protein-structure prediction.

Whether or not creating an AGI is even possible remains up for debate. Meanwhile, others may cringe at the thought of an AI with the intellect to match and exceed humanity. However, OpenAI has been bullish on the prospect. The company points to the breakthroughs researchers have made in last decade in getting AI algorithms to recognize images, translate languages, and control robots. One of OpenAI’s own AI projects can write fiction like a human can (sort of).

However, creating new AI-based technologies costs a lot of money. Not only does it require programming, but also renting access to thousands of servers. So OpenAI has been seeking funding. “The most obvious way to cover costs is to build a product, but that would mean changing our focus. Instead, we intend to license some of our pre-AGI technologies, with Microsoft becoming our preferred partner for commercializing them,” Altman wrote in a separate blog post.

• The AI Breakthrough Will Require Researchers Burying Their Hatchets.

Tesla is working on several significant manufacturing improvements for the Model Y production program and it includes building a giant new casting machine to produce a big part of the Model Y frame in one single piece.

We have been reporting on how Tesla plans to simplify the design of its future vehicle platforms and achieve greater automation in the manufacturing process.

Continue reading “Tesla has a giant new machine to produce the Model Y frame in almost one piece” »

Microsoft is investing $1 billion in OpenAI to support us building artificial general intelligence (AGI) with widely distributed [https://openai.com/charter/]

Economic benefits. We’re partnering to develop a hardware and software platform within Microsoft Azure which will scale to AGI. We’ll jointly develop new Azure.

AI supercomputing technologies, and Microsoft will become our exclusive cloud provider—so we’ll be working hard together to further extend Microsoft Azure’s capabilities in large-s.

It won’t steal your data, but it might steal your soul.

The immediate future of the moon will see us build on those first steps taken in July 1969. We’ll send more robotic landers and rovers to conduct experiments on our behalf. China already has another Chang’e mission planned for this year and India, too, will look to land on the surface before the end of the year. In our stead, the robots will search for water and explore the lunar highlands for the resources necessary to establish a more permanent presence.

Looking further ahead, we’ll prepare to truly colonize the moon. We’ll mine the sublunar layers and smelt its rock for metals and oxygen. We’ll live at its poles, erecting inflatable shelters, communications centers and laboratories, and performing experiments not possible from the surface of the Earth. Eventually, we’ll depart for further into the cosmos and find our way to Mars.

But it starts with the moon.

“If you rearrange the atoms in coal, you get diamond. If you rearrange the atoms in sand, you get silicon. How atoms are arranged is fundamental to all material aspects of life,” says Ralph Merkle, currently senior research chair at the Institute for Molecular Manufacturing. He’s a large, pear-shaped man who, as he speaks, waves his arms far more energetically than his physique would imply. He modulates his tone dramatically for effect, often humorous.

Those words kick off day 2 at the Singularity University Executive Program. The curriculum divides roughly into three days of intensive classroom introductions to critical tech domains, three days of visits to Silicon Valley companies, and two days of workshops devoted to specific industries, plus a final day to wrap up. On Saturday I settled gingerly into a lightly padded metal chair for highly compressed, sometimes super technical, up-to-the-minute overviews of artificial intelligence, robotics, networking, computing, and quantum computing. (Forecast: sunny! With patchy clouds and fog.) That took until dinner time with only a quick break for lunch, which was filled with presentations by graduates of SU’s nine-week summer program.

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A partnership with Sam Altman and Elon Musk’s OpenAI looks to be a win-win for both companies. But a “holy grail” breakthrough is likely decades away.