Two complementary half-day seminars by Dr. Barry Devlin positioning emerging AI technology in the context of familiar paradigms such as such as BI and analytics, exploring the application of different types of machine learning and algorithms, and exploring the relationship between big data from multiple sources and the many types of AI /machine learning using it.
From Analytics to AI: Transforming Decisions in Digital Business
With the enormous growth of big data, now is the time to start building the skills and infrastructure in artificial intelligence (AI) to transform BI and analytics in support of decision making.
Under a range of names—deep learning, machine learning, cognitive computing, robotics, algorithms and more—AI, combined with big data, IoT and automation, are revolutionising all aspects of IT, business and, indeed, society. What do you need to know about them? How should you prepare for and react to their growing importance in your business and IT environments, especially in their likely transformation of decision-making support?
In this half-day seminar, Dr Barry Devlin positions emerging AI technology in the context of familiar paradigms such as such as BI and analytics, exploring the application of different types of machine learning and algorithms. He extrapolates from the rapid growth of AI in the consumer world to where and how it will drive business and impact internal IT. Based on new models of organisational and personal decision making, he examines where to apply augmentation and automation in AI.
Data-Driven AI: Opportunities and Threats
Advances in artificial intelligence (AI) are being driven not so much by improved techniques and innovative algorithms but by the breadth and volume of data available on the Internet from social media and the Internet of Things (IoT). The implications of this dependence on data are significant.
In this half-day seminar, Dr Barry Devlin explores the relationship between big data from multiple sources and the many types of AI /machine learning using it. The opportunities offered by this data for new types of decisions must be balanced against the dangers arising from poor quality data, legal implications of using personally identifiable information (PII), and other issues. The question is what solutions are available. Barry will also address the ethical, economic and social implications of widespread adoption of artificial intelligence.