Science – Page 75

Robotics’ Reliability Challenge: Testing Before the Robots Take Over

03.02.2026 by ebaster

The prevalence of research addressing specific testing aspects within robotics varies considerably, as evidenced by the differing numbers of publications dedicated to each facet of robotic validation.

As robots become increasingly autonomous, ensuring their software is rigorously tested is paramount, and this review examines the current state of robotics testing practices.

Governing the Rise of AI: Beyond the Rules

03.02.2026 by ebaster

Effective AI oversight demands a fundamental shift from debating what regulations are needed to building the legal systems that will actually deliver them.

Learning to Bend Reality: A New Simulator for Soft Robotics

03.02.2026 by ebaster

SoMA reconstructs deformable objects from real-world manipulation data as hierarchical Gaussian splats, propagating their motion through a neural simulator governed by force-based interactions-a two-stage training strategy first establishes global movement across significant temporal distances before refining nuanced dynamics even under conditions of occlusion and contact.

Researchers have developed a neural simulator that learns to accurately model the complex dynamics of deformable objects manipulated by robots, bridging the gap between simulation and real-world performance.

Uncovering Hidden Order: AI’s New Lens on Physical Data

03.02.2026 by ebaster

Symmetry within machine learning manifests across three distinct approaches: architectural imposition of invariance, implicit introduction through data manipulation, and emergent organization arising within latent spaces-a progression where control gives way to the spontaneous formation of order without explicit design.

Researchers are harnessing the power of artificial intelligence to identify underlying symmetries and reduce complexity in datasets, offering a novel approach to understanding the fundamental structure of physical phenomena.

Learning from Humans: A New Framework for Agile Humanoid Robots

03.02.2026 by ebaster

Researchers have developed a full-stack system that allows humanoid robots to learn complex interaction skills directly from human videos, bypassing the need for laborious task-specific programming.

Modeling Materials with Minds: The Rise of AI-Driven Plasticity

03.02.2026 by ebaster

A new wave of artificial intelligence techniques is transforming how we understand and predict the behavior of materials under stress.

The AI Echo Chamber: How Constant Interaction Shifts Your Thinking

03.02.2026 by ebaster

Human interaction with generative AI isn’t simply a direct exchange, but a complex entanglement fostering cognitive and behavioral drift at individual, group, and population levels, where even those not directly interacting with AI can be subtly influenced, necessitating targeted metacognitive interventions to recalibrate the feedback loop.

Sustained collaboration with artificial intelligence isn’t just changing what we do, but how we think, necessitating new strategies for self-awareness and cognitive resilience.

The Self-Driven Lab: AI Agents Accelerate Materials Discovery

03.02.2026 by ebaster

Initially focused on discrete, task-specific applications, material science research leveraging large language models and agentic systems has evolved towards deeper integration with these systems, enabling a progression from reactive problem-solving to more holistic material design and discovery approaches.

A new vision for materials science leverages intelligent AI agents to orchestrate experiments, curate data, and ultimately design novel materials with minimal human intervention.

Simulating Smarter Exoskeletons

03.02.2026 by ebaster

The Exo-plore framework generates realistic gait trajectories for hip exoskeleton assistance-built upon a 164-muscle musculoskeletal model-and validates these through a sim-to-real approach that replicates observed human adaptation patterns and metabolic responses, ultimately enabling efficient, customizable exoskeleton control via a trained surrogate network.

A new simulation framework uses AI to optimize exoskeleton control, potentially streamlining development and personalization for a wider range of users.

Beyond the Context Window: Scaling AI Research with File Systems

03.02.2026 by ebaster

The FS-Researcher framework establishes a structured approach to facilitate research, prioritizing a holistic understanding of system behavior through interconnected components rather than isolated modifications-a principle reflecting that elegant design stems from simplicity and clarity, and that structure dictates behavior.

A new framework empowers artificial intelligence agents to conduct extended, iterative research by leveraging a file-system workspace to overcome the limitations of short-term memory.