Elon Musk’s bet on the incoming Trump administration is starting to pay off handsomely, with autonomous vehicle permits heading Tesla’s way.
Category: robotics/AI – Page 86
Google is committing $20 million in cash and $2 million in cloud credits to a new funding initiative designed to help scientists and researchers unearth the next great scientific breakthroughs using artificial intelligence (AI).
The announcement, made by Google DeepMind co-founder and CEO Demis Hassabis during a fireside chat at the closed-door AI for Science Forum in London today, feeds into a broader push by Big Tech to curry favor with young innovators and startups, a strategy that has included acqui-hires, equity investments, and cloud partnerships — some of which has attracted the attentions of regulators.
This latest announcement, via Google’s 19-year-old philanthropic arm Google.org, is different in that it centers on non-equity funding for academic and non-for-profit institutions globally. But similar to other Big Tech funding and partnership initiatives, this will go some way toward helping Google ingratiate itself with some of the leading scientific minds, through direct cash injections and by providing infrastructure to power their projects. In turn, this positions Google well to acquire future customers — particularly those currently on the cusp of doing great things, working on projects that require significant AI tooling and compute, which Google can provide.
We might like to think of ourselves as autonomous entities but, in reality, we’re more like walking ecosystems, teeming with bacteria, viruses, and other microbes. It turns out that differences in these microbes might be as crucial to evolution and natural variation as genetic mutations are.
This novel perspective was discussed in a recent publication by Seth Bordenstein, director of Penn State’s One Health Microbiome Center, who is a professor of biology and entomology and holds the Dorothy Foehr Huck and J. Lloyd Huck Endowed Chair in Microbiome Sciences.
He, along with 21 colleagues from around the globe, collectively known as the Holobiont Biology Network, propose that understanding the relationships between microbes and their hosts will lead to a more profound understanding of biological variation.
Nvidia Corp., the chipmaker at the center of a boom in artificial intelligence use, is teaming up with Alphabet Inc.’s Google to pursue another technology once relegated to science fiction: quantum computing.
We all start our lives as symmetric balls of cells. In humans, during the first few weeks after fertilization, embryonic cells undergo several rounds of division, increasing their mass. Then comes gastrulation, the process that changes everything and establishes our body plan. During gastrulation, the collection of uniform cells that make up the early embryo break symmetry and reorganize into a multi-layered structure with distinct cell types.
At this pivotal moment, our body plan is set. Gastrulation also establishes the three body axes: head–tail, front–back, and left–right. This process requires cells to interact and coordinate with each other with astonishing precision. However, how this is achieved is still largely a mystery.
The Trivedi Group at EMBL Barcelona studies how cells give rise to our body plan and has now published a study in the journal Development that may enhance our understanding of early mammalian development.
The rebirth of commercial supersonic flight has kind of, sort of come to pass as Dawn Aerospace announces that its 16-ft (4.8-m) autonomous Mk-II Aurora rocket-powered aircraft broke the sound barrier with a speed of Mach 1.1 on November 12, 2024.
Ever since the Anglo-French Concorde retired in 2003, civil supersonic flight has been something of a lost art. In recent years, a number of startups have been working on various projects to create a new generation of supersonic transports that are quieter, greener, more efficient, and cost effective to operate.
Now, one supersonic aircraft has actually taken flight, albeit in the form of an uncrewed experimental craft with a wingspan of 13 ft (4 m) and a dry weight of 880 lb (200 kg). In the skies over New Zealand’s Glentanner Aerodrome near the base of Aoraki/Mount Cook, the Mk-II Aurora hit Mach 1.1 while climbing to an altitude of 82,500 ft (25,150 m).
The initial product from this collaboration will be a 20-qubit system integrated with NVIDIA’s Grace Hopper Superchip, facilitating hybrid quantum-classical computing. This integration is expected to drive advancements in various fields, including financial services and artificial intelligence.
Through this joint venture, SDT and Anyon Technologies aim to establish a unique and robust partnership in the Asian quantum computing sector, leveraging their combined expertise to lead the commercialization and supply of superconducting quantum computers in the region.
Despite being a mature technology in existence for over several decades, silicon photonic modulators face scrutiny from industry and academic experts. In a recent editorial interview, experts emphasize the need to explore alternatives beyond the traditional platforms. The discussion centers on innovative modulator materials and configurations that could cater to emerging applications in data centers, artificial intelligence, quantum information processing, and LIDAR. Experts also outline the challenges that lie ahead in this field.
Optical and photonic modulators are technologically advanced devices that enable the manipulation of light properties—such as power and phase—based on input signals. Over the decades, scientists have researched and developed silicon photonic modulators with wide-ranging applications, including optical data communication, sensing, biomedical technologies, automotive systems, astronomy, aerospace, and artificial intelligence (AI).
However, these modulators face bandwidth limitations and operational robustness issues stemming from the fundamental properties of silicon and other practical constraints, as highlighted by a panel of leading industry and academic experts in a recent editorial interview.
Banks of computer screens stacked two and three high line the walls. The screens are covered with numbers and graphs that are unintelligible to an untrained eye. But they tell a story to the operators staffing the particle accelerator control room. The numbers describe how the accelerator is speeding up tiny particles to smash into targets or other particles.
However, even the best operator can’t fully track the miniscule shifts over time that affect the accelerator’s machinery. Scientists are investigating how to use computers to make the tiny adjustments necessary to keep particle accelerators running at their best.
Researchers use accelerators to better understand materials and the particles that make them up. Chemists and biologists use them to study ultra-fast processes like photosynthesis. Nuclear and high energy physicists smash together protons and other particles to learn more about the building blocks of our universe.