Lifeboat Foundation

Quantum computers have the potential of outperforming conventional computers on some practically relevant information processing problems, possibly even in machine learning and optimization. Yet their large-scale deployment is not yet feasible, largely due to their sensitivity to noise, which causes them to make errors.

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Dear Subscribers, please see the latest Security & tech Insights newsletter covering emerging issues, trends and potential solutions in the world of cybersecurity. Thanks for reading and stay safe! Best, Chuck Brooks PS checkout my new book on Amazon: Inside Cyber: How AI, 5G, and Quantum Computing Will Transform Privacy and Our Security Amazon.com : Inside Cyber: How AI, 5G, and Quantum Computing Will Transform Privacy and Our Security: 9781394254941: Brooks, Chuck: Books.

According to the World Health Organization, antibiotic resistance is a top public health risk that was responsible for 1.27 million deaths across the globe in 2019. When repeatedly exposed to antibiotics, bacteria rapidly learn to adapt their genes to counteract the drugs—and share the genetic tweaks with their peers—rendering the drugs ineffective.

Superpowered bacteria also torpedo medical procedures—surgery, chemotherapy, C-sections—adding risk to life-saving therapies. With antibiotic resistance on the rise, there are very few new drugs in development. While studies in petri dishes have zeroed in on potent candidates, some of these also harm the body’s cells, leading to severe side effects.

What if there’s a way to retain their bacteria-fighting ability, but with fewer side effects? This month, researchers used AI to reengineer a toxic antibiotic. They made thousands of variants and screened for the ones that maintained their bug-killing abilities without harming human cells.

Could a fully automated fab produce chips faster, cheaper, and better?

Terry Tao is one of the world’s leading mathematicians and winner of many awards including the Fields Medal. He is Professor of Mathematics at the University of California, Los Angeles (UCLA). Following his talk, Terry is in conversation with fellow mathematician Po-Shen Loh.

The Oxford Mathematics Public Lectures are generously supported by XTX Markets.

Defense technology startup Anduril Industries Inc. has raised $1.5 billion in a new funding round and plans to spend hundreds of millions on a new facility to manufacture its rockets, underwater vehicles and other autonomous weapons systems at greater scale and speed.

The deal, which values Anduril at $14 billion, is one of the largest venture capital financings of the year so far, and reflects the company’s success getting government contracts, as well as rising investor enthusiasm for defense technology companies.

Peter Thiel’s Founders Fund and Sands Capital co-led the Series F funding round, which has been in the works for more than a month. The deal nearly doubles the startup’s valuation from its previous funding round in 2022, which raised $1.48 billion.

Advanced control system positions robot to reshape aerial robotics:

Researchers have developed an overactuated aerial robot capable of full body control enabling it to conduct complex tasks.

Unmanned aerial vehicles (UAVs), commonly known as drones, are now used to capture images and carry out a wide range of missions in outdoor environments. While there are now several UAV designs with different advantages and characteristics, most conventional aerial robots are underactuated, meaning that they have fewer independent actuators than their degrees of freedom (DoF).

Underactuated systems are often more cost-effective and can be controlled using simpler control strategies than overactuated systems (i.e., robots that have more independent actuators than their DoF). Nonetheless, they are often less reliable and not as capable of precisely controlling their position and orientation.

Researchers at Tecnalia’s Basque Research and Technology Alliance (BRTA) in Spain recently developed a new overactuated aerial robot that can independently control the position and orientation of its main body. This robot, introduced in a paper published in Robotics and Autonomous Systems, has four quadrotors that cooperatively carry its central body.

A team of engineers at Google’s DeepMind Project has demonstrated a robot capable of playing amateur-level table tennis (ping-pong). The team has published a paper on the arXiv preprint server describing how they developed the robot, how well it performed at different ability levels and how human players responded to playing with the robot.

Over the past several years, robot scientists have been combining advancements in robot design with artificial intelligence, resulting in the development of robots with ever increasing abilities. In this new effort, the research team has developed an AI-based ping-pong player with the highest performance level ever for a robot.

Continue reading “DeepMind develops a robot that can play amateur level ping-pong” »