Designing Materials with AI: A New Era for Polymer Science

Researchers have developed an intelligent agent that leverages the power of artificial intelligence to accelerate the discovery and design of new polymers with targeted properties.

Researchers have developed an intelligent agent that leverages the power of artificial intelligence to accelerate the discovery and design of new polymers with targeted properties.
As generative AI becomes increasingly adept at mimicking human conversation, understanding how people develop trust in these systems for emotional support is becoming critical.
A new workflow combining artificial intelligence with high-throughput experimentation is dramatically accelerating the discovery and synthesis of promising metal phosphosulfides.

A new control framework combines the strengths of artificial intelligence and predictive algorithms to enable safer and more efficient human-robot collaboration in complex environments.

A new approach proposes uniquely identifying algorithms using established digital identifiers to bolster accountability and transparency in increasingly complex AI systems.

New research explores how making a chatbot’s reasoning process visible impacts how users perceive its empathy, warmth, and overall competence.

A new wave of AI-powered search is challenging the dominance of traditional web search, prompting a critical look at how we find and consume information online.
![The system, REprompt, functions as a recursive loop, continually refining prompts based on previous outputs-a process mirroring the unpredictable growth of any complex ecosystem where each iteration introduces the seeds of future, unforeseen adaptations and potential systemic failures, formalized as [latex]P_{t+1} = f(P_t, O_t)[/latex], where [latex]P_t[/latex] represents the prompt at time <i>t</i> and [latex]O_t[/latex] denotes the observed output.](https://arxiv.org/html/2601.16507v1/x1.png)
A new framework leverages the principles of software requirements engineering to craft effective prompts for large language models, boosting the quality of generated code.

A new study examines the quality of code generated by AI to manage software builds, revealing both improvements and potential pitfalls.

Researchers have developed a new framework and dataset to improve how robots interpret ambiguous commands during assistive tasks, paving the way for more natural and effective human-robot collaboration.