Geeky Gadgets

DeepSeek Insider Reveals Self-Improving AI Agents Are Almost Here

Self-improving AI agents are poised to become a pivotal force in the evolution of artificial intelligence. These systems, capable of refining their own algorithms and learning processes, represent a ...
IEEE

Direct Thruster Force Optimization via Sparse Linearized Gaussian Process Model Predictive Control for ROV Trajectory Tracking

Abstract: Traditional hierarchical remotely operated vehicle (ROV) control suffers from feasibility gaps between motion control and thrust allocation (TA). Modeling uncertainties further complicate ...
Harvard Business Review

Design Processes to Evolve with Emerging Technology

For decades, businesses have been trapped in a cycle of painful, episodic change, launching massive re-engineering projects and investing in new IT systems, only to find their organization’s ...
The New York Times

Silicon Valley Wants to Build A.I. That Can Improve A.I. on Its Own

Ricursive Intelligence, founded by two former Google researchers and valued at $4 billion, is among several efforts to automate the creation of artificial intelligence. Anna Goldie and Azalia ...
VentureBeat

MIT’s new ‘recursive’ framework lets LLMs process 10 million tokens without context rot

Recursive language models (RLMs) are an inference technique developed by researchers at MIT CSAIL that treat long prompts as an external environment to the model. Instead of forcing the entire prompt ...
Interesting Engineering

New adaptive system lets robots replicate human touch with far less training data

Researchers in Japan have developed an adaptive motion reproduction system that allows robots to generate human-like movements using surprisingly small amounts of training data. Despite rapid advances ...
EurekAlert!

A physics-constrained AI framework enables accurate thermal field inversion for chiplet-based packaging with sparse data

Researchers at Shanghai University have developed a physics-constrained, data-efficient artificial intelligence framework that enables accurate thermal field inversion in chiplet-based packaging ...
GitHub

SVGP-KAN: Sparse Variational Gaussian Process Kolmogorov-Arnold Networks

SVGP-KAN is a library for building interpretable, probabilistic, and scalable neural networks. It merges the architecture of Kolmogorov-Arnold Networks (KANs) with the uncertainty quantification of ...
Interesting Engineering

Chinese model with high success rate helps humanoid robots adapt to tasks without training

Researchers from Wuhan University have developed a new framework that could help robots manipulate objects more easily. Introduced in a new paper on arXiv, this approach should enable humanoid robots ...
eLife

Learning sequence-function relationships with scalable, interpretable Gaussian processes

This important work introduces a family of interpretable Gaussian process models that allows us to learn and model sequence-function relationships in biomolecules. These models are applied to three ...