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.

Real-time Interactive Barnes-Hut N-Body Simulator. Create galaxies, apply forces, visualize spatial partitioning, parameterize simulation physics and entities, etc.

Abstract: This paper proposes a new approximation algorithm that digitizes the estimation error of second-order difference of signal samples rather than digitizing ...

The AC performance of an analog-to-digital converter depends on its architecture. In part 3 of this series, we discussed the integral nonlinearity (INL) error of an ...

Abstract: In applied and numerical algebraic geometry, many problems are reduced to computing an approximation to a real algebraic curve. In order to elevate the results of such a computation to the ...

We propose the Trust Region Preference Approximation (TRPA) algorithm ⚙️, which integrates rule-based optimization with preference-based optimization for LLM reasoning tasks 🤖🧠. As a ...

1 School of Automation and Information Engineering, Sichuan University of Science and Engineering, Yibin, China. 2 Sichuan Key Laboratory of Artificial Intelligence, Yibin, China. A 14-bit successive ...