What the researchers have achieved has remarkable results: by replacing the traditional h.264 video codec with a neural network, they have managed to reduce the required bandwidth for a video call by an order of magnitude. In one example, the required data rate fell from 97.28 KB/frame to a measly 0.1165 KB/frame — a reduction to 0.1% of required bandwidth.
NVIDIA Research has invented a way to use AI to dramatically reduce video call bandwidth while simultaneously improving quality.
Could this be the energy source of the future?
The secret to the SPARC reactor is that its magnets will be built from new high-temperature superconductors that require much less cooling and can produce far more powerful magnetic fields. That means the reactor can be ten times more compact than ITER while achieving similar performance.
As with any cutting-edge technology, converting principles into practice is no simple matter. But the analysis detailed in the papers suggests that the reactor will achieve its goal of producing more energy than it sucks up. So far, all fusion experiments have required more energy to heat the plasma and sustain it than has been generated by the reaction itself.
The SPARC reactor is designed to achieve a Q factor of at least two, which means it will produce twice as much energy as it uses, but the analysis suggests that figure might actually rise to ten or more. The papers used the same physics and simulations as the ITER design team and other previous fusion experiments.
The theme of this year’s World Space Week is satellites improve life. We are taking this opportunity to appreciate satellite technology and its incredible benefits.
What is 6G? Why do we need it? And why should we consider it before we even have 5G? We will answer these questions in this article with the insights from leading companies such as Samsung and Ericsson.
Imagine if your manager could know whether you actually paid attention in your last Zoom meeting. Or, imagine if you could prepare your next presentation using only your thoughts. These scenarios might soon become a reality thanks to the development of brain-computer interfaces (BCIs).
To put it in the simplest terms, think of a BCI as a bridge between your brain and an external device. As of today, we mostly rely on electroencephalography (EEG) — a collection of methods for monitoring the electrical activity of the brain — to do this. But, that’s changing. By leveraging multiple sensors and complex algorithms, it’s now becoming possible to analyze brain signals and extract relevant brain patterns. Brain activity can then be recorded by a non-invasive device — no surgical intervention needed. In fact, the majority of existing and mainstream BCIs are non-invasive, such as wearable headbands and earbuds.
The development of BCI technology was initially focused on helping paralyzed people control assistive devices using their thoughts. But new use cases are being identified all the time. For example, BCIs can now be used as a neurofeedback training tool to improve cognitive performance. I expect to see a growing number of professionals leveraging BCI tools to improve their performance at work. For example, your BCI could detect that your attention level is too low compared with the importance of a given meeting or task and trigger an alert. It could also adapt the lighting of your office based on how stressed you are, or prevent you from using your company car if drowsiness is detected.
Airbus’s plan to bring to market a zero-emission passenger aircraft by 2035 means it needs to start plotting a course in terms of technology in 2025. In fact it needs to plot several courses.
It looks like something out of “Star Trek,” and runs on a fuel experts once thought “crazy,” but Airbus hopes that in 15 years we’ll be flying into a greener future aboard this new zero-emission aircraft concept.
‘It seemed like out of nowhere SpaceX just came up and catapulted us into the 21st century,’ says a leader of the Hoh tribe, which is based in a remote area of Washington state.
Grid AI, a startup founded by the inventor of the popular open-source PyTorch Lightning project, William Falcon, that aims to help machine learning engineers work more efficiently, today announced that it has raised an $18.6 million Series A funding round, which closed earlier this summer. The round was led by Index Ventures, with participation from Bain Capital Ventures and firstminute.
Falcon co-founded the company with Luis Capelo, who was previously the head of machine learning at Glossier. Unsurprisingly, the idea here is to take PyTorch Lightning, which launched about a year ago, and turn that into the core of Grid’s service. The main idea behind Lightning is to decouple the data science from the engineering.
The time argues that a few years ago, when data scientists tried to get started with deep learning, they didn’t always have the right expertise and it was hard for them to get everything right.
Chinese has selected a third group of astronauts for the nation’s coming space station, the China Manned Space Agency announced on Oct. 1.
Amazon unveiled the electric delivery van that is being built by Michigan-based EV startup Rivian. The delivery giant aims to have 10,000 vehicles on the road by 2022 and 100,000 by 2030.
