Lifeboat Foundation

An automated system called Guardian is being developed by the Toyota Research Institute to amplify human control in a vehicle, as opposed to removing it.

Here’s the scenario: A driver falls asleep at the wheel. But their car is equipped with a dashboard camera that detects the driver’s eye condition, activating a safety system that promptly guides the vehicle to a secure halt.

That’s not just an idea on the drawing board. The system, called Guardian, is being refined at the Toyota Research Institute (TRI), where MIT Professor John Leonard is helping steer the group’s work, while on leave from MIT. At the MIT Mobility Forum, Leonard and Avinash Balachandran, head of TRI’s Human-Centric Driving Research Department, presented an overview of their work.

Continue reading “Here’s how automation could affect the relationship between us and our cars” »

Joe Biden has been accused of having “no idea” after he misunderstood a journalist’s question about the public health authority ‘Title 42’ and instead begun speaking about a Department of Justice appeal of airplane mask mandates.

One of the big problems with solar vehicles is that there’s just not much room on a car to make that much power. With a super efficient car like an Aptera, you can get a meaningful amount of power from solar panels, mostly because the car doesn’t use that much power. But, if you don’t want your car to look like an airplane without wings or a weird science project, you can’t get that much actual range per hour of solar charging. However, an Australian professor came up with a better idea to power his Tesla off of solar panels alone: a printed solar panel that rolls up.

The Charge Around Australia project doesn’t aim to be the first EV excursion around Australia, or even the first trip around Australia on solar power. The point is to be the first vehicle that has gone around the continent in a normal car powered by an innovative new solar technology.

“Britain moves closer to a self-driving revolution,” said a perky message from the Department for Transport that popped into my inbox on Wednesday morning. The purpose of the message was to let us know that the government is changing the Highway Code to “ensure the first self-driving vehicles are introduced safely on UK roads” and to “clarify drivers’ responsibilities in self-driving vehicles, including when a driver must be ready to take back control”.

The changes will specify that while travelling in self-driving mode, motorists must be ready to resume control in a timely way if they are prompted to, such as when they approach motorway exits. They also signal a puzzling change to current regulations, allowing drivers “to view content that is not related to driving on built-in display screens while the self-driving vehicle is in control”. So you could watch Gardeners’ World on iPlayer, but not YouTube videos of F1 races? Reassuringly, though, it will still be illegal to use mobile phones in self-driving mode, “given the greater risk they pose in distracting drivers as shown in research”.

Tesla first announced the robot last summer, and says the first models will arrive next year.

Musk’s latest compensation windfall, which must be certified by Tesla’s board, comes days after he offered to buy Twitter for $43 billion, with analysts suggesting he could sell Tesla shares to help finance the deal.

Musk already is the world’s richest person, according to Forbes.

Tesla reported quarterly revenue of $18.76 billion and so-called adjusted earnings before interest, taxes, depreciation and amortization (EBITDA) of $5.02 billion. Combined with the previous three quarters’ results, that surpasses milestones that trigger the vesting of the ninth through 11th of 12 tranches of options granted to Musk in his 2018 pay package.

Labeling data can be a chore. It’s the main source of sustenance for computer-vision models; without it, they’d have a lot of difficulty identifying objects, people, and other important image characteristics. Yet producing just an hour of tagged and labeled data can take a whopping 800 hours of human time. Our high-fidelity understanding of the world develops as machines can better perceive and interact with our surroundings. But they need more help.

Scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), Microsoft, and Cornell University have attempted to solve this problem plaguing vision models by creating “STEGO,” an algorithm that can jointly discover and segment objects without any human labels at all, down to the pixel.

Continue reading “Scientists create algorithm to assign a label to every pixel in the world, without human supervision” »