AI for science
Research
powered by artificial intelligence made leaps this year, and it is here to stay. AI ‘agents’ that integrate several
large language models (LLMs) to carry out
complex, multi-step processes are likely to be used more widely, some with little human oversight. The coming year might even bring the first
consequential scientific advances made by AI. But heavier use could also expose serious failures in some systems. Researchers have already reported errors that AI agents are prone to, such as the deletion of data.
Next year will also bring techniques that move beyond LLMs, which are expensive to train. Newer approaches focus on designing small-scale AI models that learn from a limited pool of data and can specialize in solving
specific reasoning puzzles. These systems do not generate text, but process mathematical representations of information. This year, one such tiny AI model
beat massive LLMs at a logic test.