The majority of AI projects traditionally stalled, failed, or never delivered the value that was originally envisioned. Why was this the case? Because traditional AI relied on correlations, and fitting a model to old data rather than understanding the relationships between the data and desired outcomes.
Some proposed that more data was needed, but merely throwing more data at the problem didn't address the fundamental issues, and could sometimes exacerbate issues such as biases, explainability (XAI), and ethical concerns.
In this webinar, Stuart Frost, CEO of Geminos Software and successful serial software entrepreneur, discussed the reason why causal AI was gaining industry attention, and how his company was working with clients that were applying causal AI.
Joining Stuart was Judith Hurwitz, Geminos’ chief evangelist and author of more than a dozen books focused on applying emerging technologies such as Artificial Intelligence, machine learning, and big data to business challenges.