Lifeboat Foundation

Science is examining the brain’s neural activity for applications ranging from innovative therapies for brain-related injuries and disease to computational learning architectures for artificial intelligence and deep neural networks.

A research team has developed a tool that lets researchers see more of a live mouse’s brain, to make discoveries that can advance research into the neural circuit mechanisms that form the underlying behavior of the human brain. The tool overcomes the drawback of traditional brain probes—the small amount of tissue they can access, which limits their ability to image neurons of interest.

The innovation is to insert an imaging probe with side-viewing capabilities into a previously inserted optically matched channel—an ultrathin-wall glass capillary—to convert deep brain imaging into endoscopic imaging. The operator can freely rotate the probe to image different brain regions, getting a 360-degree view for imaging along the entire length of the inserted probe. This large-volume imaging enables an increase of about 1,000 times in tissue access volume, compared with what is available for imaging at the tip of typical miniature imaging probes.

The pharmaceuticals firm GSK has struck a five-year partnership with King’s College London to use artificial intelligence to develop personalised treatments for cancer by investigating the role played by genetics in the disease.

The tie-up, which involves 10 of the drug maker’s artificial intelligence experts working with 10 oncology specialists from King’s across their labs, will use computing to “play chess with cancer”, working out why only a fifth of patients respond well to immuno-oncology treatments.

Tencent Research Group Unveils ‘PIRenderer’, An AI Model To Control The Generation Of Faces Via Semantic Neural Rendering.

The new artificial intelligence tool has already led to the discovery of four new materials.

Researchers at the University of Liverpool have created a collaborative artificial intelligence tool that reduces the time and effort required to discover truly new materials.

Reported in the journal Nature Communications, the new tool has already led to the discovery of four new materials including a new family of solid state materials that conduct lithium. Such solid electrolytes will be key to the development of solid state batteries offering longer range and increased safety for electric vehicles. Further promising materials are in development.

EXCLUSIVE Pricier sex robots have already been equipped with a range of artificial intelligence features, with customers shelling out thousands on groundbreaking synthetic companions dailystar.

Welcome to AI book reviews, a series of posts that explore the latest literature on artificial intelligence.

Recent advances in deep learning have rekindled interest in the imminence of machines that can think and act like humans, or artificial general intelligence. By following the path of building bigger and better neural networks, the thinking goes, we will be able to get closer and closer to creating a digital version of the human brain.

Continue reading “Abductive inference: The blind spot of artificial intelligence” »

As artificial intelligence grows in intelligence, militaries are incorporating the tech into their arsenal. From Minority Report style predictive AI to anti-aging research, AI is steadily being introduced to everything. In one bizarre example, the Israeli military has created an AI Sniper Rifle.

Reported by The New York Times, Israeli operatives carried out an assassination mission with an AI Sniper Rifle. Conducted in November 2,020 the Israeli military used a “souped-up, remote-controlled” rifle to kill Iranian nuclear scientist Mohsen Fakhrizadeh. The military had been chasing the target “for at least 14 years”.

The Israeli military has reportedly used an AI Sniper Rifle to assassinate Iranian nuclear scientist Mohsen Fakhrizadeh after 14 years of trying.

Continue reading “AI Sniper Rifle used by Israel to assassinate nuclear scientist” »

New tools that help developers write software also generate similar mistakes.

Learning how to learn is something most humans do well, by leveraging previous experiences to inform the learning processes for new tasks. Endowing AI systems with such abilities however remains challenging, as it requires the machine learners to learn update rules, which typically have been manually tuned for each task.

The field of meta-learning studies how to enable machine learners to learn how to learn, and is a critical research area for improving the efficiency of AI agents. One of the approaches is for learners to learn an update rule by applying it on previous steps and then evaluating the corresponding performance.

To fully unlock the potential of meta-learning, it is necessary to overcome both the meta-optimization problem and myopic meta objectives. To tackle these issues, a research team from DeepMind has proposed an algorithm designed to enable meta-learners to teach themselves.