Founder and CEO of FortySeven Software Professionals, with over a decade of experience advising F500 companies and growth-stage startups. Artificial intelligence (AI) is gaining a lot of traction ...

DirectML has been popular; it’s made it a lot easier for game developers to add machine learning features to their code, and it’s supported scientific computing applications that have been ...

The second key to a successful machine learning (ML) project is an ability to process collected data. The introduction of general-purpose GPUs in 2006 and their continued evolution has unlocked ...

This article looks at 13 open source projects that are remaking the world of AI and machine learning. Some are elaborate software packages that support new algorithms. Others are more subtly ...

So when I performed the first part of our no-code/low-code machine learning experiment and got better than a 90 percent accuracy rate on a model, I suspected I had done something wrong.

The lifecycle of machine learning projects. ... stakeholders are consulted, and the project’s implementation life cycle starts. ... because if we only show people code snippets, ...

The proliferation of open-source and proprietary software has revolutionized development, enabling rapid innovation and ...

Demonstrating the wide-ranging benefits of Glow NN compiler for vision- and voice-based machine learning applications- NXP is the first semiconductor vendor to deliver a 2-3 x performance jump for ...

Intel and Daedalean present a reference design for a computational platform that can carry a machine-learned application and that is also certifiable.