“On appeal, the CAFC agreed that ‘the patents are directed to the abstract idea of using a generic machine learning technique in a particular environment, with no inventive concept’.” The U.S. Supreme ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Catalog description: Presents the underlying theory behind machine learning in proofs-based format. Answers fundamental questions about what learning means and what can be learned via formal models of ...

“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 ...

In agricultural and remote sensing research, accurately estimating wheat's Leaf Area Index (LAI) using unmanned aerial vehicle-based multispectral data is essential for monitoring crop health and ...

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

Create new power and memory efficient hardware architectures to meet next-generation machine learning hardware demands. Moving machine learning to the edge has critical requirements on power and ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...