“To maximize the likelihood that applications and patents will be found eligible under Section 101 by the USPTO and courts [after Recentive], applicants should carefully craft a narrative of a ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

Long gone are the days of only discovering the existence of cyber threats and deciding what to name each of them. Cyberthreats grow—not only in complexity but in frequency, and one of the things that ...

Understanding and predicting the optical and optoelectronic properties of matter via excited-state calculations is crucial for a range of highly relevant technological applications, from photovoltaics ...

The development of accurate and efficient machine learning models for predicting the structure and properties of molecular crystals has been hindered by the scarcity of publicly available datasets ...

Both countries face challenges in scaling these capabilities, but once they do, it could be game-changing.

Bio: Taylor is a senior in the Honors program at Fordham University majoring in Computer Science and minoring in Cybersecurity and French. She is also in the accelerated program for her MS in Data ...