At DATUM, we regularly speak with companies, institutions and government agencies that are increasingly interested in how AI and Machine Learning will fit into their business and data strategy. There are a number of available resources that address the AI explosion, deliver promises for the future and speak to how AI will reshape the way we work and live. Despite those resources, people continue to struggle to find a good foundational overview - one meant for the non-technical audience - that outlines the basics of AI, Machine Learning, and Deep Learning. In particular, what does the field of AI mean for the future of data governance? And, how will the roles of governance professionals change in an increasingly automated world?
This video series covers the basics along with some simple examples that will make you more fluent than the average business executive when it comes to AI.
Part 1 in the series answers the following questions:
- What’s the difference between AI, Machine Learning and Deep Learning?
- What are the business applications of AI today?
- What are the most common misconceptions?
- What are the defining characteristics and central goals of AI?
- What’s causing all of today’s hype?
- Why is Deep Learning a game-changer?
- How does data governance impact the AI strategy?
This is part one of a three-part video series about Artificial Intelligence, Machine Learning and Deep Learning. Part Two "How do Machine Learning and Deep Learning Work" can be found here. Part Three will be released in the coming weeks.