Lifeboat Foundation

Artificial intelligences are promising in future societies, and neural networks are typical technologies with the advantages such as self-organization, self-learning, parallel distributed computing, and fault tolerance, but their size and power consumption are large. Neuromorphic systems are biomimetic systems from the hardware level, with the same advantages as living brains, especially compact size, low power, and robust operation, but some well-known ones are non-optimized systems, so the above benefits are only partially gained, for example, machine learning is processed elsewhere to download fixed parameters. To solve these problems, we are researching neuromorphic systems from various viewpoints. In this study, a neuromorphic chip integrated with a large-scale integration circuit (LSI) and amorphous-metal-oxide semiconductor (AOS) thin-film synapse devices has been developed.

See more.

A newly discovered data wiper malware that wipes routers and modems has been deployed in the cyberattack that targeted the KA-SAT satellite broadband service to wipe SATCOM modems on February 24, affecting thousands in Ukraine and tens of thousands more across Europe.

The malware, dubbed AcidRain by researchers at SentinelOne, is designed to brute-force device file names and wipe every file it can find, making it easy to redeploy in future attacks.

SentinelOne says this might hint at the attackers’ lack of familiarity with the targeted devices’ filesystem and firmware or their intent to develop a reusable tool.

Neural networks keep getting larger and more energy-intensive. As a result, the future of AI depends on making AI run more efficiently and on smaller devices.

That’s why it’s alarming that progress is slowing on making AI more efficient.

The most resource-intensive aspect of AI is data transfer. Transferring data often takes more time and power than actually computing with it. To tackle this, popular approaches today include reducing the distance that data needs to travel and the data size. There is a limit to how small we can make chips, so minimizing distance can only do so much. Similarly, reducing data precision works to a point but then starts to hurt performance.

Closing Gaps in Geometrically Frustrated Symmetric Clusters: Local Equivalence between Discrete Curvature and Twist Transformations.

Researchers uncover an ongoing large-scale supply-chain attack which exploits dependency confusion attacks against the NPM package repository.

A group of academics has designed a new system known as “Privid” that enables video analytics in a privacy-preserving manner.