Artificial intelligence
fromTheregister
21 hours agoWho is liable when AI agents go wrong in business?
AI agents in business decision-making raise questions about accountability and risk distribution among vendors and users.
Qi Sun's DrayEasy platform exemplifies a significant advancement in logistics, merging quoting, booking, and real-time tracking into a seamless automated experience for shippers.
Despite significant investments and technological advancements, the reality is that no vehicle currently operating on public roads can be classified as fully autonomous. The complexities of real-world driving conditions present insurmountable challenges.
Time pressure, limited information, confusion, fatigue, and mortality salience combine to set the stage for decision-making errors, sometimes with grave consequences. An example is the downing of Iran Air Flight 655 by a missile launched by the USS Vincennes in 1988, resulting in the death of 290 passengers and crew. In a time of heightened tension between the U.S. and Iran, the captain of the Vincennes misidentified the airliner as an incoming hostile aircraft and ordered his crew to shoot it down.
AI agents need skills - specific procedural knowledge - to perform tasks well, but they can't teach themselves, a new research suggests. The authors of the research have developed a new benchmark, SkillsBench, which evaluates agentic AI performance on 84 tasks across 11 domains including healthcare, manufacturing, cybersecurity and software engineering. The researchers looked at each task under three conditions: