Lifeboat Foundation

A team of chemists at McGill University, working with a colleague from Charité-Universitätsmedizin, in Germany, has uncovered part of the process used by mussels to bind to rocks and to quickly release from them when conditions warrant.

In their project, reported in the journal Science, the group studied the interface between mussel tissue and the bundle of filaments that mussels use to anchor themselves to rocks and other objects. Guoqing Pan and Bin Li, with Jiangsu University and Soochow University, both in China, have published a Perspective article in the same journal issue outlining the work done by the team on this new effort.

Continue reading “Dynamic bio-interface between mussel tissue and byssus plays important role in quick release” »

Astronomers have detected a rare and extremely high-energy particle falling to Earth that is causing bafflement because it is coming from an apparently empty region of space.

The particle, named Amaterasu after the sun goddess in Japanese mythology, is one of the highest-energy cosmic rays ever detected.

Full episode with Joscha Bach (Jun 2020): https://www.youtube.com/watch?v=P-2P3MSZrBM
Clips channel (Lex Clips): https://www.youtube.com/lexclips.
Main channel (Lex Fridman): https://www.youtube.com/lexfridman.
(more links below)

Podcast full episodes playlist:

Continue reading “We exist inside the story that the brain tells itself (Joscha Bach) | AI Podcast Clips” »

Picture this: You’re in a conference room, surrounded by a mix of designers, engineers and strategists, all eager to brainstorm your company’s next big innovation. Could a machine be more effective at guiding this brainstorming session than your human team? It may sound counterintuitive, but AI is not only catching up to human creativity — it’s excelling in ways that could redefine how we approach innovation.

Related: How To Use Entrepreneurial Creativity For Innovation

The groundbreaking gene-editing technology known as Crispr, which acts like a molecular pair of scissors that can be used to cut and modify a DNA sequence, has moved rather quickly from the pages of scientific journals to the medical setting. Earlier this month, about three years after Jennifer Doudna and Emmanuelle Charpentier won the Nobel Prize in Chemistry for describing how bacteria’s immune system could be used as a tool to edit genes, regulators in the U.K. approved the first Crispr-based treatment for sickle cell disease and beta-thalassemia patients. The treatment, from Vertex Pharmaceuticals and Crispr Therapeutics, could be approved by the U.S. Food and Drug Administration early next month for sickle cell patients.

While many obstacles lie ahead for the nascent field, such as how to pay for treatments that typically cost more than $1 million, these regulatory approvals are just the start as newer gene-editing technologies such as base and prime editing make their way through human studies. In an interview, Prof. Doudna says the approval is “a turning point in medicine because it really shows how genome editing can be used as a one-and-done cure for disease.”

Gene editing is part of a broader therapeutic revolution that encompasses genetic and cellular medicine. The pills and injections we are all familiar with generally target proteins or pathways in the body to treat disease. With gene and cell therapy, we can now target the root cause of disease, sometimes curing patients.

For 200 years, scientists have failed to grow a common mineral in the laboratory under the conditions believed to have formed it naturally. Now, a team of researchers from the University of Michigan and Hokkaido University in Sapporo, Japan have finally succeeded, thanks to a new theory developed from atomic simulations.

Their success resolves a long-standing geology mystery called the “Dolomite Problem.” Dolomite—a key mineral in the Dolomite mountains in Italy, Niagara Falls, the White Cliffs of Dover and Utah’s Hoodoos—is very abundant in rocks older than 100 million years, but nearly absent in younger formations.

Continue reading “Scientists finally succeed in growing dolomite in the lab by dissolving structural defects during growth” »

From IAC-The Institute of Astrophysics of the Canary Islands [Instituto de Astrofísica de Canarias] (ES)

11.21.23 Helmut Dannerbauer [email protected].

Artist’s impression of a protocluster of galaxies in the early Universe showing galaxies forming new stars and interacting with each other. Credit: M. Kornmesser/ESO.

Tech execs have voiced concern that the development of artificial intelligence is concentrated in the hands of too few companies, potentially giving them too much power. OpenAI’s ChatGPT marked the start of what many in the industry have called an AI arms race, as tech giants including Microsoft and…

ChatGPT marked the start of what many in the industry have called an AI arms race, as tech giants have sought to launch AI models.

Artificial Intelligence and Deep learning have brought about some great advancements in the field of technology. They are enabling robots to perform activities that were previously thought to be limited to human intelligence. AI is changing the way humans approach problems and bringing revolutionary transformations and solutions to almost every industry. Teaching machines to learn from massive amounts of data and make decisions or predictions based on that learning is the basic idea behind AI. Its application in scientific endeavors has given rise to some amazing tools that are gaining massive popularity in the AI community.

In Artificial Intelligence, Symbolic Regression has been playing an important role in the subtleties of scientific research. It basically focuses on algorithms that allow machines to interpret complicated patterns and correlations found in datasets by automating the search for analytic expressions. Scientists and researchers have been putting in efforts to explore the possible uses of Symbolic Regression.

Diving into the field of Symbolic Regression, a team of researchers has recently introduced Φ-SO, a Physical Symbolic Optimization framework. This method navigates the complexities of physics, where the presence of units is crucial. It automates the process of finding analytic expressions fitting complex datasets.