In this special guest feature, Chris Haddock, a software product manager with ADEC Innovations, discusses how the foundation of a machine learning project for companies large and small is training ...

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their ...

How tinyML differs from mainstream machine learning. How tinyML is being applied. What are some of the better-known tinyML frameworks, and where can you get more information? In the ebb and flow of ...

Data processing these days is exhibiting a split personality. ‘Cloud’ computing grabs the headlines for sheer scale and computing power, while ‘edge’ computing puts the processing at the ‘coal face’ ...

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 ...

Back in the ancient days of machine learning, before you could use large language models (LLMs) as foundations for tuned models, you essentially had to train every possible machine learning model on ...

Why it’s important not to over-engineer. Equipped with suitable hardware, IDEs, development tools and kits, frameworks, datasets, and open-source models, engineers can develop ML/AI-enabled, ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...