As enterprises around the world deploy machine learning and AI in actual production, it’s becoming increasingly critical that AI can be trusted to produce not just accurate, but also fair and ethical results. An interesting market opportunity has opened up to equip enterprises with the tools to address those issues.
At our most recent Data Driven NYC, we had a great chat with Krishna Gade, co-founder and CEO of Fiddler, a platform to “monitor, observe, analyze and explain your machine learning models in production with an overall mission to make AI trustworthy for all enterprises”. Fiddler has aised $45 million in venture capital to date, most recently a $32 million Series B just last year in 2021.
We got a chance to cover some great topics, including:
- What does “explainability” mean, in the context of ML/AI? What is “bias detection”?
- What are some examples of business impact of “models gone bad”?
- A dive into the Fiddler product and how it addresses the above?
- Where are we in the cycle of actually deploying ML/AI in the enterprise? What’s the actual state of the market?
Below is the video and full transcript. As always, please subscribe to our YouTube channel to be notified when new videos are released, and give your favorite videos a “like”!
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