We’ve gotten pretty good at building machine learning models. From legacy platforms like SAS to modern MPP databases and Hadoop clusters, if you want to train up regression or classification models, ...

In this special guest feature, Neil Cohen, Vice President at Edge Intelligence, examines the question: where should businesses develop and execute machine learning? This article explores the pros and ...

With so many machine learning projects failing to launch – never achieving model deployment – the ML team has got to do everything in their power to anticipate any impediments to model ...

Machine learning might be the world’s most important general-purpose technology, but it’s notoriously difficult to launch. Outside of Big Tech and a handful of other leading companies, machine ...

The global economy is shifting from software intelligence to embodied AI — where algorithms meet physical production.

The partnership will transform the development process from concept to production for embedded machine learning in micropower devices. Eta Compute and Edge Impulse have announced that they are ...

Overview: NVIDIA’s H100 and A100 dominate large-scale AI training with unmatched tensor performance and massive VRAM capacity ...

z System users with data behind their firewalls can now access IBM's training and deployment system for machine learning, packaged for convenience If you’re intrigued by IBM’s Watson AI as a service, ...

Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...