Lifeboat Foundation

Dutch company Lightyear has unveiled what it claims is the world’s first production-ready solar car. The Lightyear 0 is a family sedan with 5 sq m (53.8 sq ft) of solar panels built in, capable of generating up to 70 km (44 miles) of charge-free driving a day.

Having scaled its workforce up to 500 people and hooked up deals with more than 100 suppliers, Lightyear is deadly serious about this venture and ready to start manufacturing. Its first car is this four-door fastback electric sedan, with enough onboard battery to deliver a very solid 560 km (348 miles) of freeway driving at 110 km/h (68 mph), even without the sun shining.

Continue reading “Lightyear 0 production solar car could run for months without charging” »

Extremely interested to hear some of your opinions on this. Published in the journal Nature.

Scientists have discovered a new, mysterious particle. Of course, making new discoveries is exciting. But, perhaps the most exciting thing about this particle is that it could be a candidate for dark matter.

Incredibly, the never-before-seen particle was discovered using an experiment small enough to fit on a kitchen counter.

Continue reading “Scientists discovered a never-before-seen particle and it could be dark matter” »

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Not only do quantum computers have the edge over classical computers on some tasks, but they are also exponentially faster, according to a new mathematical proof.

The U.K. has reported more than 300 cases.

The U.S. Centers for Disease Control and Prevention (CDC) ramped up its alert level for the ongoing monkeypox outbreak as the nation’s case count hit 30 and the global case count rose above 1,000.

The CDC now advises that travelers “practice enhanced precautions” to avoid contracting and spreading the rare viral disease, the agency’s website states (opens in new tab). The CDC says that people should avoid close contact with sick people, including those with rashes on their skin or genitals, and with dead or live wild animals, especially rodents, such as rats and squirrels, and non-human primates, meaning monkeys and apes.

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A collection of 16 qubits has been organized in such a way that they may be able to operate any computation without error. It is an important step toward constructing quantum computers that outperform standard ones.

When completing any task, a quantum computer consisting of charged atoms can detect its own faults. Because conventional computers constantly detect and rectify their own flaws, quantum computers will need to do the same in order to fully outperform them. Nevertheless, quantum effects can cause errors to propagate rapidly through the qubits, or quantum bits, that comprise these devices.

Continue reading “How Can a Quantum Computer Catch its Own Errors in Calculations?” »

Convolutional neural networks used to be the typical network architecture in modern computer vision systems. Transformers with attention mechanisms were recently presented for visual tasks, and they performed well. Convolutions and self-attention aren’t required for MLP-based (multi-layer perceptron) vision models to perform properly. As a result of these advancements, vision models are reaching new heights.

The input image is handled differently by different networks. In Euclidean space, image data is commonly represented as a regular grid of pixels. On the image, CNNs apply a sliding window and introduce shift-invariance and locality. The MLP vision transformer, which was released recently, treats the image as a series of patches.

Recognizing the items in an image is one of the most basic tasks of computer vision. The typically utilized grid or sequence structures in prior networks like ResNet and ViT are redundant and inflexible to process because the objects are usually not quadrate whose shape is irregular. An item can be thought of as a collection of parts, such as a human’s head, upper torso, arms, and legs. These sections are organically connected by joints, forming a graph structure. Furthermore, a graph is a generic data structure, with grids and sequences being special cases of graphs. Visual perception is more flexible and effective when an image is viewed as a graph.

They can have abilities their creators did not foresee.

Huge “foundation models” are turbo — charging AI progress.

They can have abilities their creators did not foresee.

Machine learning can get a boost from quantum physics.

On certain types of machine learning tasks, quantum computers have an exponential advantage over standard computation, scientists report in the June 10 Science. The researchers proved that, according to quantum math, the advantage applies when using machine learning to understand quantum systems. And the team showed that the advantage holds up in real-world tests.

“People are very excited about the potential of using quantum technology to improve our learning ability,” says theoretical physicist and computer scientist Hsin-Yuan Huang of Caltech. But it wasn’t entirely clear if machine learning could benefit from quantum physics in practice.