Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

The parody includes comical AI hallucinations and inconsistencies, including some serious problems coping with the logic of doors and telephones.

Abstract: The successive convex approximation (SCA) methods stand out as the viable option for nonlinear optimization-based control, as it effectively addresses the challenges posed by nonlinear ...

Brilliant figures such as Sergey Nikitovich Mergelyan (1928-2008) defined the 20th century as an era for extraordinary mathematical discovery. Mergelyan was best known for his contributions to ...

ABSTRACT: Based on theorems, the Atomic AString Functions theory, evolving since the 1970s, is introduced into Quantum Mechanics to represent a wave function via the shifts and stretches of smooth ...

Abstract: In this article, the optimal parking trajectory planning problem with chance constraints is considered. A conservative approximation-based method is presented to handle the chance ...

Three-body problems—the analytical expressions of three celestial bodies in a stable orbit—have beguiled mathematicians for centuries. In 2017, Chinese mathematicians discovered more than a thousand ...

Making sense of the country’s economic trouble. By David Leonhardt China’s economic problems can seem sudden and surprising. Just a few years ago, its economy inspired worldwide envy. Today, signs of ...

Mathematician Per Enflo, who solved a huge chunk of the 'invariant subspaces problem' decades ago, may have just finished his work. When you purchase through links on our site, we may earn an ...

Two weeks ago, a modest-looking paper was uploaded to the arXiv preprint server with the unassuming title “On the invariant subspace problem in Hilbert spaces”. The paper is just 13 pages long and its ...