Lifeboat Foundation

Should you trust it?

Information about Tom Snyder: AI could be smarter than humans when it comes to health care.

STOCKHOLM — John Hopfield and Geoffrey Hinton were awarded the Nobel Prize in physics Tuesday for discoveries and inventions that formed the building blocks of machine learning.

“This year’s two Nobel Laureates in physics have used tools from physics to develop methods that are the foundation of today’s powerful machine learning,” the Nobel committee said in a press release.

Hopfield’s research is carried out at Princeton University and Hinton works at the University of Toronto.

The Oregon company already has robots working in a Spanx warehouse and running trials at Amazon facilities.

Researchers from Tohoku University and the Massachusetts Institute of Technology (MIT) have unveiled a new AI tool for high-quality optical spectra with the same accuracy as quantum simulations, but working a million times faster, potentially accelerating the development of photovoltaic and quantum materials.

Organizations are losing between $94 — $186 billion annually to vulnerable or insecure APIs (Application Programming Interfaces) and automated abuse by bots. That’s according to The Economic Impact of API and Bot Attacks report from Imperva, a Thales company. The report highlights that these security threats account for up to 11.8% of global cyber events and losses, emphasizing the escalating risks they pose to businesses worldwide.

Drawing on a comprehensive study conducted by the Marsh McLennan Cyber Risk Intelligence Center, the report analyzes over 161,000 unique cybersecurity incidents. The findings demonstrate a concerning trend: the threats posed by vulnerable or insecure APIs and automated abuse by bots are increasingly interconnected and prevalent. Imperva warns that failing to address security risks associated with these threats could lead to substantial financial and reputational damage.

Researchers have developed an algorithm that could dramatically reduce the energy consumption of artificial intelligence systems.

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Scientists at BitEnergy AI created a method called “Linear-complexity multiplication” (L-Mul) that replaces complex floating-point multiplications in AI models with simpler integer additions.

The advent of LLMs has reopened a debate about the limits of machine intelligence — and requires new benchmarks of what reasoning consists of.

One milestone along that journey is the demonstration of machine common sense.

AI-powered assistants are set to become a part of daily life, offering guidance and reminders through body-worn devices that blend AI with XR.