Lifeboat Foundation: Safeguarding Humanity
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Blog – Page 1398

Inside every plant, animal and human cell are billions of molecular machines. They’re made up of proteins, DNA and other molecules, but no single piece works on its own. Only by seeing how they interact together, across millions of types of combinations, can we start to truly understand life’s processes.

In a paper published in Nature, we introduce AlphaFold 3, a revolutionary model that can predict the structure and interactions of all life’s molecules with unprecedented accuracy. For the interactions of proteins with other molecule types we see at least a 50% improvement compared with existing prediction methods, and for some important categories of interaction we have doubled prediction accuracy.

We hope AlphaFold 3 will help transform our understanding of the biological world and drug discovery. Scientists can access the majority of its capabilities, for free, through our newly launched AlphaFold Server, an easy-to-use research tool. To build on AlphaFold 3’s potential for drug design, Isomorphic Labs is already collaborating with pharmaceutical companies to apply it to real-world drug design challenges and, ultimately, develop new life-changing treatments for patients.

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Astronomy Magazine — Project Lyra is the cover feature!

A big thank you to Maciej Rebisz for the images and the entire Project Lyra team for the research work!

Project Lyra develops concepts for reaching interstellar objects such as 1I / ‘Oumuamua and 2I / Borisov with a spacecraft, based on near-term technologies. But what is an interstellar object?

Continue reading “Project Lyra — Exploring Interstellar Objects” | >

Elon Musk’s unique management style at Tesla, which involves small, highly technical teams, removing underperforming employees, and creating challenging deadlines, has been crucial to the company’s success Questions to inspire discussion Who is Andrej Karpathy? —Andrej Karpathy is a highly respected computer scientist who served as the Director of AI and Autopilot at Tesla and co-founded OpenAI.

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The find, simulated with computer modeling, might explain what happens to liquid water across the universe.

“Water is really important for life,” said Eryn Cangi, co-author and a research scientist at the Laboratory for Atmospheric and Space Physics, in a press release. “We need to understand the conditions that support liquid water in the universe, and that may have produced the very dry state of Venus today.”

At one point, Venus might have hosted seas like Earth. So, what happened? The study’s scientists suspect that Venus underwent a powerful greenhouse event that raised temperatures to 900 degrees Fahrenheit. After this happened, all the planet’s water evaporated, leaving some droplets behind. Even the few drops that were left over might have vanished because of an ion, HCO+, in the planet’s atmosphere.

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Google DeepMind’s newly launched AlphaFold Server is the most accurate tool in the world for predicting how proteins interact with other molecules throughout the cell. It is a free platform that scientists around the world can use for non-commercial research. With just a few clicks, biologists can harness the power of AlphaFold 3 to model structures composed of proteins, DNA, RNA and a selection of ligands, ions and chemical modifications.

AlphaFold Server will help scientists make novel hypotheses to test in the lab, speeding up workflows and enabling further innovation. Our platform gives researchers an accessible way to generate predictions, regardless of their access to computational resources or their expertise in machine learning.

Experimental protein-structure prediction can take about the length of a PhD and cost hundreds of thousands of dollars. Our previous model, AlphaFold 2, has been used to predict hundreds of millions of structures, which would have taken hundreds of millions of researcher-years at the current rate of experimental structural biology.

AlphaFold 3 model is a Google DeepMind and Isomorphic Labs collaboration.

Continue reading “AlphaFold Server Demo — Google DeepMind” | >

We discuss a perturbative and non-instantaneous reheating model, adopting a generic post-inflationary scenario with an equation of state w. In particular, we explore the Higgs boson-induced reheating, assuming that it is achieved through a cubic inflaton-Higgs coupling ϕ|H|2. In the presence of such coupling, the Higgs doublet acquires a ϕ-dependent mass and a non-trivial vacuum–expectation–value that oscillates in time and breaks the Standard Model gauge symmetry. Furthermore, we demonstrate that the non-standard cosmologies and the inflaton-induced mass of the Higgs field modify the radiation production during the reheating period. This, in turn, affects the evolution of a thermal bath temperature, which has remarkable consequences for the ultraviolet freeze-in dark matter production.

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Proteins are the molecular machines that sustain every cell and organism, and knowing what they look like will be critical to untangling how they function normally and malfunction in disease. Now researchers have taken a huge stride toward that goal with the development of new machine learning algorithms that can predict the folded shapes of not only proteins but other biomolecules with unprecedented accuracy.

In a paper published today in Nature, Google DeepMind and its spinoff company Isomorphic Labs announced the latest iteration of their AlphaFold program, AlphaFold3, which can predict the structures of proteins, DNA, RNA, ligands and other biomolecules, either alone or bound together in different embraces. The findings follow the tail of a similar update to another deep learning structure-prediction algorithm, called RoseTTAFold All-Atom, which was published in March in Science.

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