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We’re not actually specifically focused on AGI.

I’m simply saying that AGI seems likely to be an emergent property of what we’re doing, because we’re creating all these autonomous cars and autonomous humanoids that are actually a truly gigantic data stream that’s coming in and being processed.

Using self-healing silicon microparticles, scientists have developed the first battery electrode that heals itself.

Researchers have made the first battery electrode that heals itself, opening a new and potentially commercially viable path for making the next generation of lithium-ion batteries for electric cars, cell phones, and other devices.

The secret is a stretchy polymer that coats the electrode, binds it together, and spontaneously heals tiny cracks that develop during battery operation, said the team from Stanford University and the Department of Energy’s SLAC National Accelerator Laboratory.

When the Robovan approached the stage at Tesla’s “We, Robot” event, it became evident that the electric vehicle maker was definitely not shying away from creating machines that look like they belong in a sci-fi movie. But while the event itself was thin on technical details about the Cybercab and the Robovan, CEO Elon Musk did share some information about the people hauler’s suspension system.

The Robovan looked like it was gliding on the pavement when it pulled up in front of the stage of the “We, Robot” event. The Robovan is very low on the ground, so much so that its wheels are almost not visible. This creates a very futuristic look, but it also brought concerns about the vehicle’s capability to traverse roads that are not perfectly paved. It also incited jokes from critics that the Robovan looks like a kitchen appliance.

In later comments on X, CEO Elon Musk highlighted that the Robovan is actually very airy inside even if it may appear otherwise from the outside. Musk also explained that the Robovan’s extremely low ground clearance is due to the vehicle’s automatic load-leveling suspension system. This allows the all-electric people-hauler to raise or lower its suspension depending on the conditions of the road.

Elon Musk on Thursday unveiled what he said was a robotaxi capable of self-driving, predicting it would be available by 2027—about a decade after he first promised an autonomous vehicle.

The Tesla CEO said the fully electric car—which has no steering wheel or pedals—would be priced under $30,000, would be charged wirelessly with inductive technology and would be “10 to 20 times safer” than human-driven cars.

“You can think of the car in an autonomous world as being like just a little lounge,” he told a crowd at the Warner Brothers Studio lot near Los Angeles.

“Our microwave induction heating technology enables fast and easy preparation of hard carbon, which I believe will contribute to the commercialization of sodium-ion batteries,” said Dr. Daeho Kim.


Can sodium-ion batteries be improved to exceed the efficiency and longevity of traditional lithium-ion batteries? This is what a recent study published in Chemical Engineering Journal hopes to address as a team of researchers from South Korea investigated how microwave induction heating can produce sufficient carbon anodes used in sodium-ion batteries. This study holds the potential to help researchers and engineers better understand how to develop and produce efficient sodium-ion batteries, which have demonstrated greater abundancy and stability.

“Due to recent electric vehicle fires, there has been growing interest in sodium-ion batteries that are safer and function well in colder conditions. However, the carbonization process for anodes has been a significant disadvantage in terms of energy efficiency and cost,” said Dr. Jong Hwan Park, who is from the Korea Electrotechnology Research Institute (KERI) and a co-author on the study.

For the study, the KERI-led researchers improved upon existing sodium-ion batteries by using microwave technology, which involves heating carbon nanotubes using a microwave magnetic field, resulting in temperature exceeding 1,400 degrees Celsius (2,550 degrees Fahrenheit) in only 30 seconds. This breakthrough improves upon traditional methods for procuring carbon anodes, which typically require lengthy amounts of time to reach just 1,000 degrees Celsius (1,800 degrees Fahrenheit).

Neural networks have a remarkable ability to learn specific tasks, such as identifying handwritten digits. However, these models often experience “catastrophic forgetting” when taught additional tasks: They can successfully learn the new assignments, but “forget” how to complete the original. For many artificial neural networks, like those that guide self-driving cars, learning additional tasks thus requires being fully reprogrammed.

Biological brains, on the other hand, are remarkably flexible. Humans and animals can easily learn how to play a new game, for instance, without having to re-learn how to walk and talk.

Inspired by the flexibility of human and animal brains, Caltech researchers have now developed a new type of that enables neural networks to be continuously updated with new data that they are able to learn from without having to start from scratch. The algorithm, called a functionally invariant path (FIP) algorithm, has wide-ranging applications from improving recommendations on online stores to fine-tuning self-driving cars.

Be it water, light or sound: waves usually propagate in the same way forwards as in the backward direction. As a consequence, when we are speaking to someone standing some distance away from us, that person can hear us as well as we can hear them. This is useful when having a conversation, but in some technical applications one would prefer the waves to be able to travel only in one direction – for instance, in order to avoid unwanted reflections of light or microwaves.

For sound waves, ten years ago researchers succeeded in suppressing their propagation in the backward direction; however, this also attenuated the waves travelling forwards. A team of researchers at ETH Zurich led by Nicolas Noiray, professor for Combustion, Acoustics and Flow Physics, in collaboration with Romain Fleury at EPFL, has now developed a method for preventing sound waves from travelling backwards without deteriorating their propagation in the forward direction. In the future, this method, which has recently been published in the scientific journal external page Nature Communications, could also be applied to electromagnetic waves.

The basis of this one-way street for sound waves are self-oscillations, in which a dynamical system periodically repeats its behaviour. “I’ve actually spent a good part of my career preventing such phenomena”, says Noiray. Amongst other things, he studies how self-sustaining thermo-acoustic oscillations can arise from the interplay between sound waves and flames in the combustion chamber of an aircraft engine, which can lead to dangerous vibrations. In the worst case, these vibrations can destroy the engine.