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.

In his decades-long career in tech journalism, Dennis has written about nearly every type of hardware and software. He was a founding editor of Ziff Davis’ Computer Select in the 1990s, senior ...

Abstract: We consider stochastic optimization problems with non-convex functional constraints, such as those arising in trajectory generation, sparse approximation, and robust classification. To this ...

In his decades-long career in tech journalism, Dennis has written about nearly every type of hardware and software. He was a founding editor of Ziff Davis’ Computer Select in the 1990s, senior ...

[Igor] made a VU meter with LEDs using 8 LEDs and 8 comparators. This is a fast way to get one of 8 bits to indicate an input voltage, but that’s only the equivalent of a 3-bit analog to digital ...

We note that it is always possible to apply a variable shift so that the initial value problem can be written as $$ \frac{dy}{dx} = f(x,y), \quad y(0) = 0 $$ Example ...

Abstract: This paper presents a modification of the successive approximation method so the model can be updated with an each new learning example, without need to keep them all from the beginning. The ...