Shifting Priorities: How AI is Reshaping US Research Funding

A new analysis reveals that the surge in artificial intelligence capabilities is demonstrably altering the landscape of federal research investment.

A new analysis reveals that the surge in artificial intelligence capabilities is demonstrably altering the landscape of federal research investment.
A new robotic system combines tactile sensing and reinforcement learning to autonomously locate and characterize embedded objects with greater precision than manual methods.
As artificial intelligence transforms healthcare, ensuring robust security and patient privacy is paramount to realizing its full potential.
![The architecture learns a unified latent representation of motion by decoupling a shared latent space into five body-segment subspaces - left arm, right arm, trunk, left leg, and right leg - and employing robot-specific embedding layers [latex]E_r[/latex] to project varying pose dimensionalities into a common feature space, subsequently reconstructed via inverse mappings [latex]D_r[/latex], thereby enabling cross-embodiment motion modeling across humans and diverse robotic platforms.](https://arxiv.org/html/2601.15419v1/figures/modeloverview.png)
Researchers have developed a new framework that allows robots with different physical forms to share a common understanding of movement, simplifying cross-embodiment control.
A new perspective challenges traditional notions of creativity, arguing that consistent output, not intentional agency, may be the key to unlocking AI’s artistic potential.

New research explores how intelligently suggesting follow-up questions can unlock more expressive and exploratory interactions with generative AI models.
A new system combines the power of large language models with logical reasoning to automate end-to-end business processes.
A new review explores how social robots are being designed to encourage positive health behaviors, and what we know about their effectiveness.
Researchers have developed a novel approach to combine the strengths of symbolic reasoning and neural networks into a single, cohesive system.

A new study examines the potential of social robots to support disabled students in higher education, revealing both promise and practical limitations.