Creating a center of gravity around open source data and AI technologies from IBM.

We are in the midst of a sea change in the data and AI landscape these days. Throughout the entire stack, from hardware to distributed data processing, all the way up to advanced machine learning and deep learning, these changes will have a profound impact on our society. According to a study by McKinsey, in their survey of 3,000 AI-aware C-level executives, only 20% said they currently use any AI-related technology at scale or in a core part of their businesses. There is definitely a growing gap between early AI adopters and the rest of the community.

With the advent of open source deep learning engines like TensorFlow, PyTorch, Keras, etc., there’s a rapidly growing need for skills and technologies that provide a consistent and standardized way to interact with these different machine learning engines. We need to drive standardized approaches in the industry (for example, ONNX) to ensure we are all marching towards a common goal with a common set of standards and technologies. In addition, we want these technologies to be democratized so that they’re easily accessible to and consumable by developers, both in open source and enterprises.

At IBM, we’ve been a key community member and driver of this revolution. We believe these advances need to happen out in the open, driven by open standards, open code, open communities, and open governance. I’ve talked previously about the rich history of IBM and its contributions to open standards, as well as the work IBM is doing with IBM Code around democratizing these technologies using code, content, and community.

Sourse: ibm.com