On Driving Value with DevOps and AI (AI at Work Podcast)

David DumasDataOps, AI & ML Services, Strategy and Planning

AI at work Introspectdata

Our CEO recently appears on the “AI at Work” Podcast hosted by Rob May. Please give it a listen as we delve into the past, present, and future of DevOps and AI moving forward.

Summary

AI technologies continue to grow both in the breadth and depth of applications. As a result, many companies are at a loss when it comes to figuring out how to get started. How can firms leverage these advances for their business processes?

IntrospectData is a consulting and product-focused firm that’s poised to help organizations make sense of AI and ML technologies. Not just with how they can be adopted, but also how they can be applied to each company’s work. Patrick McClory is the CEO and founder of IntrospectData. On Episode 33 of AI at Work, he joins host Rob May, CEO and co-founder of Talla to talk about exciting trends in the world of AI. We discuss opportunities that lie ahead, and how companies can decide when it is the right time to deploy AI.

Current Trends in the World of AI

The AI landscape is growing in two dimensions. “It’s growing in breadth in terms of different types of tools and different types of focal areas. Then also in depth. As it grows, it gets much deeper and much more diverse inside of that ecosystem,” Patrick explains. He cites TensorFlow as an example of the latter.

On the engineering side, Patrick says he focuses much of his attention on natural language processing these days. There are so many exciting advances coming out that, he admits. “It is daunting to keep on top of the ever-growing landscape.”

“On a business side,” Patrick says, “what I find is that the basic tooling, the basic stuff, is really still pretty revolutionary to businesses. They’re looking to leverage the data they have under the hood to go in and do something interesting. The first steps, and the ones that organizations are holding on to, in my experience, has been really just some of the basics to start these days. We’re still in the early days on that side, I think.”

As someone whose expertise lies in helping companies find entry points for bringing AI onboard, Patrick reflects that the contingent of organizations that actually knows what they want to do is very small. Especially compared to those who hold a more general mindset of exploring and understanding. “Most organizations, even in the sort of high-end, big enterprise world are still very much looking to AI and ML to be the big win. However, they’re still struggling to understand how or where that can be their big win.”

Opportunities Ahead

A question that often comes up for companies contemplating AI technologies is whether the right approach is to jump in or take a wait-and-see approach. For Patrick, the low costs of experimentation and the ready availability of tools points to a clear answer.

“For organizations that are already in the cloud, regardless of which provider, the tools are there to go. I don’t want to put it lightly, but to literally go and play and do some discovery, and understand what they can do with that data? It’s easier than ever. For organizations that aren’t, there are some great ways to even do this. You don’t need a pile of GPUs to just get started, try out your basic Tensor or NLP or other tool sets.”

And the best way to see the impact this technology can have? Test it out for yourself. “When you can actually rapidly put something like that in someone’s hands, it really begins that art of the possible discussion,” says Patrick. “That’s where I find organizations really start to take hold of these things. I am a big advocate for taking speculative first steps, even without a whole lot of intent to use it in production, to then begin that kind of deeper discussion around what is possible, how they can leverage it, and how they can move forward with those technologies.”

Where Next?

As the AI at Work podcast wrapped up, we looked to the future. Currently, most AI, ML, and data science tools are really geared towards engineers and data scientists. Looking ahead, Patrick hopes that this gap in the market will close. Furthermore, he hopes businesses will be able to connect directly with the tools in a straightforward and intuitive manner. Giving this capability to businesses to experiment and iterate will likely spark many creative revolutions, so let us stay tuned and see what the AI-driven future has in store.

To listen to Episode 33 of the AI at Work Podcast, click the link and let us know what you think!