Abstract: In-memory computing is, in current literature, the most common paradigm used to counteract the Von-Neumann bottleneck, proposing the use of memory elements to define complex input-output ...
Abstract: In this paper, we propose a reconstruction method of Boolean networks from input-output data sets. A Boolean network is a mathematical model where dynamics are modeled by Boolean functions.
It’s 2026, and we’re no longer just playing with AI. The sandbox phase is over. Across industries—from finance to pharma to federal agencies—AI has moved from pet projects to real operations. Not just ...
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