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Category: robotics/AI – Page 87

AI tensor network-based computational framework cracks a 100-year-old physics challenge

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics.

The Tensors for High-dimensional Object Representation (THOR) AI framework employs tensor network algorithms to efficiently compress and evaluate the extremely large configurational integrals and central to determining the thermodynamic and mechanical properties of materials.

The framework was integrated with machine learning potentials, which encode interatomic interactions and dynamical behavior, enabling accurate and scalable modeling of materials across diverse physical conditions.

Human intuition fuels AI-driven quantum materials discovery

Many properties of the world’s most advanced materials are beyond the reach of quantitative modeling. Understanding them also requires a human expert’s reasoning and intuition, which can’t be replicated by even the most powerful artificial intelligence, mixed with fortuitous accident, according to Eun-Ah Kim, the Hans A. Bethe Professor of physics in the College of Arts and Sciences.

Kim and collaborators have developed a that encapsulates and quantifies the valuable intuition of human experts in the quest to discover new quantum materials. The model, Materials Expert-Artificial Intelligence (ME-AI), “bottles” this intuition into descriptors that predict the functional properties of a material. The team used the method to solve a quantum materials problem.

“We are charting a new paradigm where we transfer experts’ knowledge, especially their intuition and insight, by letting an expert curate data and decide on the fundamental features of the model,” said Kim, director of the Cornell-led National Science Foundation AI-Materials Institute. “Then the machine learns from the data to think the way the experts think.”

Democratizing AI scientists using ToolUniverse

AI scientists are emerging computational systems that serve as collaborative partners in discovery. These systems remain difficult to build because they are bespoke, tied to rigid workflows, and lack shared environments that unify tools, data, and analyses into a common ecosystem. In omics, unified ecosystems have transformed research by enabling interoperability, reuse, and community-driven development; AI scientists require comparable infrastructure. We present ToolUniverse, an ecosystem for building AI scientists from any language or reasoning model, whether open or closed. TOOLUNIVERSE standardizes how AI scientists identify and call tools, integrating more than 600 machine learning models, datasets, APIs, and scientific packages for data analysis, knowledge retrieval, and experimental design. It automatically refines tool interfaces for correct use by AI scientists, creates new tools from natural language descriptions, iteratively optimizes tool specifications, and composes tools into agentic workflows. In a case study of hypercholesterolemia, ToolUniverse was used to create an AI scientist to identify a potent analog of a drug with favorable predicted properties. The open-source ToolUniverse is available at https://aiscientist.tools.

Creator behind AI actress responds to backlash: ‘She is not a replacement for a human being’

Artificial people may put a lot of actors out of work.

Tilly Norwood looks and sounds real, but she’s not real at all.

Created by Eline Van Der Velden, the CEO of the AI production company Particle6, the “actress” has garnered interest from studios with talent agents eyeing to sign her.

Variety reports, Van Der Velden explained at the Zurich Summit that studio interest has spiked since Tilly’s launch with agency representation expected soon. If signed, she would be one of the first AI-generated actresses to have talent representation.

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