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Reasoning AI: Tailoring Explanations to Expert Minds

24.03.2026 by ebaster

The research introduces an adaptive explainability approach composed of two phases: the initial phase constructs agentic personas via embedding techniques, clustering algorithms, and large language model synthesis, while the subsequent phase leverages these personas to condition reward functions within a reinforcement learning framework.

A new approach leverages AI personas modeled on expert reasoning to deliver explanations that adapt to individual understanding and build trust in complex scientific domains.

Categories Science

Navigating the Code: An Agent for Smarter Scientific Computing

24.03.2026 by ebaster

Researchers have developed a new framework that allows autonomous agents to efficiently explore and solve complex coding problems in scientific domains.

Categories Science

How We Solve Problems With AI: Three Collaboration Styles

24.03.2026 by ebaster

New research reveals distinct patterns in how humans and artificial intelligence work together, impacting both efficiency and critical thinking.

Categories Science

Self-Adapting Radios: The Rise of Agentic AI

24.03.2026 by ebaster

A multi-agent artificial intelligence framework optimizes radio frequency receiver performance through a neurosymbolic architecture, dynamically responding to real-time signal characteristics-such as the short-time Fourier transform and error vector magnitude-and integrated sensor feedback.

A new framework leverages artificial intelligence to create RF systems that learn, adapt, and optimize their performance in real-time.

Categories Science

Soft Robotics Finds Its Reach: Navigating Clutter with Hybrid Manipulators

24.03.2026 by ebaster

A system integrates goal detection, three-dimensional reconstruction-enhanced by occupancy grids to map traversable space-and shape-informed path planning to enable a learned controller for hybrid manipulators, facilitating real-time reaching and control within complex environments and allowing actuation to any arbitrary pose.

A new framework combines vision and control to enable robotic arms – blending rigid and soft components – to reliably grasp objects in complex, real-world environments.

Categories Science

AI Powers the Experiment: Speeding Up Innovation Cycles

24.03.2026 by ebaster

Artificial intelligence is rapidly transforming how businesses iterate and improve, moving beyond theory to fuel practical experimentation.

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Building AI That Acts: A Unified Framework for Embodied Agents

24.03.2026 by ebaster

This review explores how Active Inference, implemented through reactive message passing, offers a principled architecture for creating robust and adaptable physical AI agents.

Categories Science

Coordinated Robotics: Planning for the Unexpected

24.03.2026 by ebaster

As robot teams scale, the planner demonstrably coordinates efforts to optimize task completion costs, effectively dividing work across the team for both complex, order-dependent assignments and simpler, order-independent ones.

New research details a framework for multi-robot teams to dynamically adapt and efficiently complete tasks in uncertain environments.

Categories Science

Scaling Robot Intelligence: A New Approach to Collaborative Search

24.03.2026 by ebaster

A codesign framework integrates small, terminal AI models with larger, edge-based models, establishing a layered architecture for robotic systems operating in secure environments and enabling a nuanced balance between localized intelligence and broader computational resources.

Researchers have developed a framework that combines the reasoning power of large AI models with the efficiency of smaller, edge-based systems to enhance multi-robot coordination and exploration.

Categories Science

The Cognitive Science Lab of the Future?

24.03.2026 by ebaster

A self-optimizing cycle drives scientific advancement in cognitive science, wherein experimental proposals initiate data generation by foundation models, followed by iterative model refinement and critical evaluation of results-a feedback loop that ultimately guides further experimental design.

A new vision proposes fully automating the cycle of experiment design, data generation, and model building to accelerate progress in understanding the mind.

Categories Science
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