Lifeboat Foundation

An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network.

The spinoff, aptly named Liquid AI, emerged from stealth this morning and announced that it has raised $37.5 million — substantial for a two-stage seed round — from VCs and organizations including OSS Capital, PagsGroup, WordPress parent company Automattic, Samsung Next, Bold Capital Partners and ISAI Cap Venture, as well as angel investors like GitHub co-founder Tom Preston Werner, Shopify co-founder Tobias Lütke and Red Hat co-founder Bob Young.

The tranche values Liquid AI at $303 million post-money.

O.o!!

Submerged beneath a manmade lake in China lies a forgotten city, dubbed by experts as “China’s Atlantis”

The underwater city, known as the Lion City or Shi Cheng, is hidden 40 metres beneath the surface of Qiandao Lake in eastern China.

Continue reading “Ancient Chinese city found perfectly preserved at the bottom of a lake” »

One of nature’s most common organic materials—lignin—can be used to create stable and environmentally friendly organic solar cells. Researchers at Linköping University and the Royal Institute of Technology (KTH) have now shown that untreated kraft lignin can be used to make solar cells even more environmentally friendly and reliable. The study has been published in the journal Advanced Materials.

Sunlight currently seems to be one of the main sustainable energy sources. Traditional solar cells made from silicon are efficient but have an energy-demanding and complicated manufacturing process that may lead to hazardous chemical spills. Organic solar cells have therefore become a hot research area thanks to their low production cost, light weight and flexibility, and hence have many applications, such as indoor use or attached to clothing to power personal electronic devices.

But one problem is that organic solar cells are made of plastic, or polymers derived from oil. So, although organic, they are not as environmentally friendly as they could be.

Physicists at the University of Regensburg have found a way to manipulate the quantum state of individual electrons using a microscope with atomic resolution. The results of the study have now been published in the journal Nature.

We, and everything around us, consist of molecules. The molecules are so tiny that even a speck of dust contains countless numbers of them. It is now routinely possible to precisely image such molecules with an atomic force microscope, which works quite differently from an optical microscope: it is based on sensing tiny forces between a tip and the molecule under study.

Using this type of microscope, one can even image the internal structure of a molecule. Although one can watch the molecule this way, this does not imply knowing all its different properties. For instance, it is already very hard to determine which kind of atoms the molecule consists of.

“It is particularly challenging, expensive, and time-consuming to find polar bears in the Arctic, let alone count them and understand how they are coping with climate change,” said Dr. Melanie Lancaster.

Can scientists use DNA from polar bear footprints to help improve conservation efforts during this age of climate change? This is what a recent study published in Frontiers in Conservation Science hopes to address as a team of international researchers have developed a novel tool designed to use DNA from polar bear footprint skin cells with the goal of tracking the large mammals without the need to capture them, which often risks the safety of both the polar bears and their human captors in the process. This study holds the potential to develop new methods in tracking animals whose populations are at risk as climate change continues to warm the planet.

Polar bear near Utqiagvik, Alaska in May 2022. (Credit: Elisabeth Kruger, World Wildlife Fund)

Continue reading “Snowy Footprints as DNA Gold Mines: A New Frontier in Polar Bear Research” »

Aging | doi:10.18632/aging.204896. Jae-Hyun Yang, Christopher A. Petty, Thomas Dixon-McDougall, Maria Vina Lopez, Alexander Tyshkovskiy, Sun Maybury-Lewis, Xiao Tian, Nabilah Ibrahim, Zhili Chen, Patrick T. Griffin, Matthew Arnold, Jien Li, Oswaldo A. Martinez, Alexander Behn, Ryan Rogers-Hammond, Suzanne Angeli, Vadim N. Gladyshev, David A. Sinclair.

In today’s Google Bard news today was the fact that it was trained and is running on a new version of the company’s homegrown TPU chips for AI.

The new TPU v5p is a core element of AI Hypercomputer, which is tuned, managed, and orchestrated specifically for gen AI training and serving.

Is phone and digital media addiction real? If so, what steps can be taken to mitigate it? This is something that a recent study published in the journal Technology, Mind, and Behavior hopes to address as a team of researchers discuss a new instrument called the Digital Media Overuse Scale (dMOS) to determine a person’s level of addiction to digital media such as their phone. This study comes at a time when smartphones and digital media device technologies are only improving and holds the potential to help scientists and clinicians make the connection between technology and psychology.

“We wanted to create a tool that was immediately useful in the clinic and lab, that reflects current understandings about how digital addiction works, that wouldn’t go obsolete once the next big tech change hits,” said Dr. Daniel Hipp, who is a research consultant at the Digital Media Treatment & Education Center in Boulder, Colorado, and lead author of the study.

For the study, the researchers developed dMOS to address the outdated methods pertaining to bridging the gap between technology and psychology, such as how we talk about technology and asking outdated questions. The goal of dMOS is to allow scientists and clinicians to conduct a variety of analyses pertaining to digital media usage, including a broad analysis such as social media as a whole or a more focused analysis such a specific social media platform such as Facebook.

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Working together as a consortium, FAIR or university partners captured these perspectives with the help of more than 800 skilled participants in the United States, Japan, Colombia, Singapore, India, and Canada. In December, the consortium will open source the data (including more than 1,400 hours of video) and annotations for novel benchmark tasks. Additional details about the datasets can be found in our technical paper. Next year, we plan to host a first public benchmark challenge and release baseline models for ego-exo understanding. Each university partner followed their own formal review processes to establish the standards for collection, management, informed consent, and a license agreement prescribing proper use. Each member also followed the Project Aria Community Research Guidelines. With this release, we aim to provide the tools the broader research community needs to explore ego-exo video, multimodal activity recognition, and beyond.

How Ego-Exo4D works.

Ego-Exo4D focuses on skilled human activities, such as playing sports, music, cooking, dancing, and bike repair. Advances in AI understanding of human skill in video could facilitate many applications. For example, in future augmented reality (AR) systems, a person wearing smart glasses could quickly pick up new skills with a virtual AI coach that guides them through a how-to video; in robot learning, a robot watching people in its environment could acquire new dexterous manipulation skills with less physical experience; in social networks, new communities could form based on how people share their expertise and complementary skills in video.