Researchers have developed a new approach to object-goal navigation that empowers AI agents to reason about their surroundings and plan routes using both visual perception and language understanding.
As artificial intelligence increasingly turns its ear to animal communication, a fundamental challenge emerges: can we truly understand another species when our very methods of listening may distort the signal?
Researchers have developed a collaborative framework that prioritizes key visual features for compression, resulting in sharper images at lower bitrates.
New research explores representation learning techniques that move beyond variational autoencoders to reveal underlying data structures and enable more effective scientific discovery.
Researchers have developed a new approach that blends predictive control with reinforcement learning to enable safer, more efficient navigation for teams of robots in challenging environments.
A new analysis reveals the key elements developers emphasize when configuring AI coding agents like Claude Code to achieve desired software development outcomes.
A new framework illuminates how entrepreneurs are leveraging artificial intelligence to turn imaginative concepts into thriving businesses.
Researchers are demonstrating a neurosymbolic system powered by Vector Symbolic Algebras that tackles complex abstract reasoning challenges, moving beyond the limitations of purely statistical models.
A new framework leverages machine learning to predict human intentions, enabling mobile robots to proactively assist and reduce operator cognitive load.
As artificial intelligence rapidly advances, a critical gap remains in its ability to support the nuanced insights of qualitative research.