Vinay Seth Mohta is Managing Director at Manifold, an artificial intelligence engineering services firm with offices in Boston and Silicon Valley. Vinay has helped develop Manifold’s Lean AI process to build useful and accurate machine learning apps for a wide variety of customers.

During today’s episode, Vinay and I discuss common misconceptions about machine learning. Some of the other topics we cover are:

• The 3 buckets of machine learning problems and applications.
• Differences between traditional product development and developing apps with machine learning from Vinay’s perspective.
• Vinay’s opinion of what will change as a result of growth in the machine learning industry
• Maintaining a vision of a product while building it

Resources and Links:

• CRISP-DM
• Ways to Think About Machine Learning by Benedict Evans
• The Lean AI process
• Vinay Seth Mohta on LinkedIn
• Big Data, Big Dupe: A little book about a big bunch of nonsense by Stephen Few

Quotes from Vinay on today’s episode:

“We want to try and get them to dial back a little bit on the enthusiasm and the pixie dust aspect of AI and really, start thinking about it, more like a tool, or set of tools, or set of ideas that enable them with some new capabilities.”

“We have a process we called Lean AI and what we’ve incorporated into that is this idea of a feedback loop between a business understanding, a data understanding, then doing some engineering – so this is the data engineering, and then doing some modeling and then putting something in front of users.”

“Usually, team members who have domain knowledge [also] have pretty good intuition of what the data should show. And that is a good way to normalize everybody’s expectations.”

“You can really bring in some of the intuition that [clients] already have around their data and bring that into the conversation and that becomes an almost shared decision about what to do [with the data].”