Lifeboat Foundation: Safeguarding Humanity
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Japanese UAV startup A.L.I. Technologies test flies a prototype drone motorcycle capable of top speeds of 100 kmh for up to 40 minutes.

Why does this not sound like a necessarily great idea? A startup in Japan has unveiled a one-person drone intended to be flown like a motorcycle, hurtling through the air and around corners at top speeds of 100 kmh.

The footage of the Xturismo’s test flight, however, captured a far more contained and cautious outing, with the deafening craft remaining aloft for all of 90 seconds as it performed a few basic moves.

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In a press statement, EdisonFuture said the EF1-T, as well as a van version of the vehicle called the EF1-V, feature “a uniquely designed solar mosaic technology that provides a stunning visual signature while also harnessing the power of the sun to recharge the batteries, enabling work vehicles to continuously charge while in the field.”

Bizarrely, as far as we can tell, the automaker hasn’t actually released any information regarding the battery size, range, or solar charging specifications of the EF1-T, though a prototype of the vehicle is due to go on display at the LA Auto Show in mid-November, so we may learn more information then. EdisonFuture also said it will begin accepting reservations for the pickup during the show.

While we’re likely pretty far off seeing vehicles that run solely on solar power, we’re increasingly seeing pickups and cars fitted with solar panels as the technology matures, allowing for added range figures that aren’t negligible. Dutch automaker Lightyear 0 for example, states on its website that its Lightyear One car can add 7 miles (12 km) of range per hour via solar charging. Lightyear eventually aims to develop vehicles that can go months without needing to charge via conventional means. Stay posted to learn more about the range figures of the EF1-T when we find out more in the very near future.

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The new world of work is also about a new kind of teamwork: humans and AI working together to achieve more than they can accomplish on their own. Regardless of its recent progress, AI is still not accurate enough to meet the enterprise-level requirements of speech-to-text in many industries. “If technology gives me 90% accuracy, humans can deal with the last mile. Human-in-the-loop is core to our product,” explains Livne. In addition to developing the required technology, Ver… See more.

Verbit is a very successful startup. The 4-year-old developer of an AI-powered transcription and captioning platform has reached unicorn status in June, raising $157 million at a valuation of over $1 billion, for a total of $319 million raised to date. It has 2,600 customers, 450 employees, and will reach $100 million in revenues by the end of the year. According to co-founder and CEO Tom Livne, Veribit enjoys Net Revenue Retention (the rate of revenue generation from existing customers) of 163%. “Our customers are growing with us,” says Livne.

This impressive performance is the result of executing on a well thought-out framework for what it will take to succeed in the future, no matter what business you are in and the market you are serving. Verbit’s technology foundation, its global community of freelancers, and its mass customization strategy are the three features of Verbit’s future of work model, the very model of a 21 st century company.

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“Technological advances in robotics have already produced robots that are indistinguishable from human beings,” they write. “If humanoid robots with the same appearance are mass-produced and become commonplace, we may encounter circumstances in which people or human-like products have faces with the exact same appearance in the future.”

To test peoples’ reactions, the team asked people to look at photos of individuals with the same face (clones), with different faces, and of… See more.

The uncanny valley is the scientific explanation for why we all find clowns or corpses creepy. And just when we thought nothing could be more alarming than clowns, scientists have found an even uncannier way to freak us out.

New research finds that there is something even creepier than the uncanny valley: clones. Scientists now predict that when convincing humanoid robots with identical faces are launched, we are all going to panic.

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Like weather forecasting, disease forecasting needs to be statistical.

While we cannot predict in advance exactly how many hurricanes will occur this year or how bad they will be, we know with great confidence that climate change is a risk factor increasing the frequency and severity of hurricanes. Our knowledge of this and all the other risk factors for hurricanes allows us to make a statistical prediction for the coming season.

Similarly, we have known for decades that ther… See more.

I’ve written before about the need for infectious disease intelligence and whether or not we can insure against damages from future outbreaks. Both ideas assume that epidemics can, to some extent, be predicted. But can they?

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In conversation with my teenage daughter last week, I pointed out a news report which flagged concerns over the use of facial recognition technologies in several school canteens in North Ayrshire, Scotland. Nine schools in the area recently launched this practice as a means to take payment for lunches more quickly and minimize COVID risk, though they’ve since paused rolling out the technology.

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Hundreds of millions of years of evolution have produced a variety of life-forms, each intelligent in its own fashion. Each species has evolved to develop innate skills, learning capacities, and a physical form that ensures survival in its environment.

But despite being inspired by nature and evolution, the field of artificial intelligence has largely focused on creating the elements of intelligence separately and fusing them together after the development process. While this approach has yielded great results, it has also limited the flexibility of AI agents in some of the basic skills found in even the simplest life-forms.

In a new paper published in the scientific journal Nature, AI researchers at Stanford University present a new technique that can help take steps toward overcoming some of these limits. Called “deep evolutionary reinforcement learning,” or DERL, the new technique uses a complex virtual environment and reinforcement learning to create virtual agents that can evolve both in their physical structure and learning capacities. The findings can have important implications for the future of AI and robotics research.

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