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May 8, 2024

Shopify says AI has helped keep its head count flat

Posted by in category: robotics/AI

Shopify’s head count has remained flat since last year, and executives say they have AI to thank.

May 8, 2024

10 Interesting Scientific Discoveries for May, 2024

Posted by in category: futurism

A selection of 10 Interesting Scientific Discoveries for May, 2024.My Patreon Page: https://www.patreon.com/johnmichaelgodierMy Event Horizon Channel: https://

May 8, 2024

Elon Musk’s Management Style at Tesla: A Key to Success

Posted by in categories: Elon Musk, robotics/AI

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.

May 8, 2024

Venus May Have Once Hosted Seas Like Earth, But Is Bone Dry Today

Posted by in categories: alien life, computing, physics

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.

May 8, 2024

AlphaFold Server Demo — Google DeepMind

Posted by in categories: biotech/medical, chemistry, open access, robotics/AI

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.

Continue reading “AlphaFold Server Demo — Google DeepMind” »

May 8, 2024

Higgs Boson-Induced Reheating and Dark Matter Production

Posted by in categories: cosmology, evolution, information science, particle physics

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.

May 8, 2024

New AI Tools Predict How Life’s Building Blocks Assemble

Posted by in categories: biotech/medical, information science, nanotechnology, robotics/AI

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.

May 8, 2024

This $119 houseplant is bioengineered to remove harmful air pollution in your home

Posted by in categories: bioengineering, sustainability

Neoplants has bioengineered a houseplant that uses bacteria to remove indoor air pollution from your home.

May 8, 2024

Meet AdVon, the AI-Powered Content Monster Infecting the Media Industry

Posted by in category: robotics/AI

Our investigation into AdVon Commerce, the AI contractor at the heart of scandals at USA Today and Sports Illustrated.

May 8, 2024

Researchers Develop Energy-Efficient Probabilistic Computer by Combining CMOS with Stochastic Nanomagnet

Posted by in categories: computing, information science, nanotechnology, particle physics

In this study, graduate student Keito Kobayashi and Professor Shunsuke Fukami from Tohoku University, along with Dr. Kerem Camsari from the University of California, Santa Barbara, and their colleagues, developed a near-future heterogeneous version of a probabilistic computer tailored for executing probabilistic algorithms and facile manufacturing.

“Our constructed prototype demonstrated that excellent computational performance can be achieved by driving pseudo random number generators in a deterministic CMOS circuit with physical random numbers generated by a limited number of stochastic nanomagnets,” says Fukami. “Specifically speaking, a limited number of probabilistic bits (p-bits) with a stochastic magnetic tunnel junction (s-MTJ), should be manufacturable with a near-future integration technology.”

The researchers also clarified that the final form of the spintronics probabilistic computer, primarily composed of s-MTJs, will yield a four-order-of-magnitude reduction in area and a three-order-of-magnitude reduction in energy consumption compared to the current CMOS circuits when running probabilistic algorithms.

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