Using a clever laser technique, scientists have squished pairs of atoms closer together than ever before, revealing some truly mind-boggling quantum effects.
“Big machine learning models have to consume lots of power to crunch data and come out with the right parameters, whereas our model and training is so extremely simple that you could have systems learning on the fly,” said Robert Kent.
How can machine learning be improved to provide better efficiency in the future? This is what a recent study published in Nature Communications hopes to address as a team of researchers from The Ohio State University investigated the potential for controlling future machine learning products by creating digital twins (copies) that can be used to improve machine learning-based controllers that are currently being used in self-driving cars. However, these controllers require large amounts of computing power and are often challenging to use. This study holds the potential to help researchers better understand how future machine learning algorithms can exhibit better control and efficiency, thus improving their products.
“The problem with most machine learning-based controllers is that they use a lot of energy or power, and they take a long time to evaluate,” said Robert Kent, who is a graduate student in the Department of Physics at The Ohio State University and lead author of the study. “Developing traditional controllers for them has also been difficult because chaotic systems are extremely sensitive to small changes.”
For the study, the researchers created a fingertip-sized digital twin that can function without the internet with the goal of improving the productivity and capabilities of a machine learning-based controller. In the end, the researchers discovered a decrease in the controller’s power needs due to a machine learning method known as reservoir computing, which involves reading in data and mapping out to the target location. According to the researchers, this new method can be used to simplify complex systems, including self-driving cars while decreasing the amount of power and energy required to run the system.
Could we be getting close to quantum teleportation? Eat your hearts out sci-fi fans because this could actually happen.
WASP-193 b is the second least dense planet discovered to date, after Kepler-51 d, which is much smaller,” said Dr. Khalid Barkaoui. “Its extremely low density makes it a real anomaly among the more than five thousand exoplanets discovered to date.
Can gas giant exoplanets larger than Jupiter have less density than the latter? This is what study published today in Nature Astronomy hopes to address as a team of international researchers discovered WASP-193 b in 2023, which is located just under 1,200 light-years from Earth and orbits its parent star (slightly larger than our Sun) in only 6.25 days. What’s unique about WASP-193 b is that it exhibits a radius almost 1.5 times that of Jupiter, the largest planet in our solar system, but whose mass is only 14 percent of Jupiter and whose density is just under 4 percent of Jupiter, as well. This study holds the potential to help astronomers better understand the formation and evolution of exoplanets, which continue to challenge our understanding of solar system architecture.
WASP-193 b has a density of approximately 0.059 grams per centimeter cubed (g/cm3), which is comparable to cotton candy. For context, Jupiter has a density of 1.33 g/cm3, Saturn has a density of 0.69 g/cm3, Uranus has a density of 1.27 g/cm3, and Neptune has a density of 1.64 g/cm3. Therefore, despite being larger than Jupiter, WASP-193b’s density is far less than the largest gas giant in our solar system.
We think of GoogleDeepMind as the engine room of Google in the #AI era.
We’re sharing updates across our Gemini family of models and a glimpse of Project Astra, our vision for the future of AI assistants.
The company is aiming to be the first memory-maker to hit the 1 petabyte barrier in a single SSD.
Google is trying to turn AI chatbots to intelligent systems that can reason, plan, and remember. Project Astra is a window into this potential future.