Managing AI and ML in the Enterprise
The AI and ML deployments are well underway, but for CXOs the biggest issue will be managing these initiatives, figuring out where the data science team fits in and figuring out what algorithms to buy vs. build.
For IBM, AutoAI is part of a Watson Studio build out as well as a broader data science portfolio that includes IBM Watson Assistant and Discovery and Watson Machine Learning.
Recent Watson moves include:
IBM updates Watson StudioIBM aims to make Watson a set of microservices that can run across multiple cloudsIBM aims to meld AI with human resources with Watson suiteIBM launches pretrained Watson packs for industriesThe AI, machine learning, and data science conundrum: Who will manage the algorithms?
Data science: Data analytics: A guide for business leaders (free PDF) (TechRepublic) | 10 signs you may not be cut out for a data scientist job | How to choose the right data analytics tools: 5 steps | Enterprise AI in 2019: What you need to know
Related Topics:
Big Data Analytics
Digital Transformation
CXO
Internet of Things
Innovation
Enterprise Software