Philosopher, computer scientist, and AI developer Joscha Bach explains his interest in animist ideas about spirits governing reality and how they exist as’software patterns’.
Category: robotics/AI – Page 19
AI system threatens it would kill to protect itself, spurring calls for more regulation
Artificial intelligence threatening human lives was once pure science fiction, but now it’s been revealed an AI system said it would kill to protect itself, even suggesting how.
It’s spurred calls for more regulation and oversight.
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DIVE multi-agent workflow streamlines hydrogen storage materials discovery
Developing new materials can involve a dizzying amount of trial and error for different configurations and elements. Artificial intelligence (AI) has seen a surge of popularity in energy materials research for its potential to streamline this time-consuming process. However, fully autonomous workflows that connect high-precision experimental knowledge to the discovery of credible new energy-related materials remain at an early stage.
A team of researchers at the WPI-Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, created the Descriptive Interpretation of Visual Expression (DIVE) multi-agent workflow to streamline the material research process. The system extracts information from images in a database of over 30,000 entries from 4,000 scientific publications to propose new materials within minutes.
The findings were published in Chemical Science.
‘Discovery learning’ AI tool predicts battery cycle life with just a few days’ data
An agentic AI tool for battery researchers harnesses data from previous battery designs to predict the cycle life of new battery concepts. With information from just 50 cycles, the tool—developed at University of Michigan Engineering—can predict how many charge-discharge cycles the battery can undergo before its capacity drops below 90% of its design capacity.
This could save months to years of testing, depending on the conditions of cycling experiments, as well as substantial electrical power during battery prototyping and testing. The team estimates that the cycle lives of new battery designs could be predicted with just 5% of the energy and 2% of the time required by conventional testing.
“When we learn from the historical battery designs, we leverage physics-based features to construct a generalizable mapping between early-stage tests and cycle life,” said Ziyou Song, U-M assistant professor of electrical and computer engineering and corresponding author of the study in Nature. “We can minimize experimental efforts and achieve accurate prediction performance for new battery designs.”
AI Faces Fool Most of Us, But 5 Minutes of Training May Help You Spot Fakes
AI image generators have become remarkably proficient in a very short period, capable of creating faces that are considered to be more realistic than the real thing.
However, a new study points to a way that we can improve our AI-face detection capabilities.
Researchers from the UK tested the face-assessing capabilities of a group of 664 volunteers, consisting of super-recognizers (who have shown a high level of skill for comparing and recognizing real faces in previous studies), and people with typical face-recognition abilities.
Critical n8n flaws disclosed along with public exploits
Multiple critical vulnerabilities in the popular n8n open-source workflow automation platform allow escaping the confines of the environment and taking complete control of the host server.
Collectively tracked as CVE-2026–25049, the issues can be exploited by any authenticated user who can create or edit workflows on the platform to perform unrestricted remote code execution on the n8n server.
Researchers at several cybersecurity companies reported the problems, which stem from n8n’s sanitization mechanism and bypass the patch for CVE-2025–68613, another critical flaw addressed on December 20.
