Machine learning tagged posts

Researchers have applied a deep learning technique to a previously studied dataset of nearby stars and uncovered eight previously unidentified signals of interest.

When pondering the probability of discovering technologically advanced extraterrestrial life, the question that often arises is, “if they’re out there, why haven’t we found them yet?” And often, the response is that we have only searched a tiny portion of the galaxy. Further, algorithms developed decades ago for the earliest digital computers can be outdated and inefficient when applied to modern petabyte-scale datasets...

A multi-institution research team has developed an optical chip that can train machine learning hardware.

Machine learning applications skyrocketed to $165B annually, according to a recent report from McKinsey. But, before a machine can perform intelligence tasks such as recognizing the details of an image, it must be trained. Training of modern-day artificial intelligence (AI) systems like Tesla’s autopilot costs several million dollars in electric power consumption and requires supercomputer-like infrastructure. This surging AI “appetite” leaves an ever-widening gap between computer hardware and demand for AI...

Researchers have discovered new properties of tiny magnetic whirlpools called skyrmions. Their pivotal discovery could lead to a new generation of microelectronics for memory storage with vastly improved energy efficiency in high performance computers.

Magnets generate invisible fields that attract certain materials. A common example is fridge magnets. Far more important to our everyday lives, magnets also can store data in computers. Exploiting the direction of the magnetic field (say, up or down), microscopic bar magnets each can store one bit of memory as a zero or a one — the language of computers.

Scientists at the U.S...

Imperial privacy experts have created an AI algorithm that automatically tests privacy-preserving systems for potential data leaks.

This is the first time AI has been used to automatically discover vulnerabilities in this type of system, examples of which are used by Google Maps and Facebook.

The experts, from Imperial’s Computational Privacy Group, looked at attacks on query-based systems (QBS)—controlled interfaces through which analysts can query data to extract useful aggregate information about the world. They then developed a new AI-enabled method called QuerySnout to detect attacks on QBS.

QBS give analysts access to collections of statistics gathered from individual-level data like location and demographics...