I had the chance to sit down with Scott Clark, Founder & CEO of SigOpt, a Founding sponsor of the upcoming TWIMLcon: AI Platforms! Scott discusses what SigOpt has been up to, the unique value he sees #TWIMLcon bringing to the ML/AI industry and what you can expect from the expert-driven SigOpt session and booth!
Sam Charrington: [00:00:00] All right everyone, I am excited to have Scott Clark, founder and CEO of SigOpt. If you know Scott’s name, it’s because he’s one of the few who has been on the TWIML AI podcast multiple times. Scott, welcome once again.
Scott Clark: [00:00:13] Thanks, Sam. Always a pleasure to chat.
Sam Charrington: [00:00:16] For those who haven’t heard one of the previous episodes, why don’t we get started by having you give us a really brief overview of your background.
Scott Clark: [00:00:23] Yep. So I did my PhD in optimization in applied mathematics at Cornell. Spent a couple years at Yelp on their advertising team, helping them tune the various aspects of it, and working on releasing things like the Yelp academic dataset challenge. And then about five years ago, started SigOpt.
Sam Charrington: [00:00:42] And so what is SigOpt?
Scott Clark: [00:00:45] We’re a software company. We build tools to help people build better models. We do this via an experimentation and optimization platform that bolts on top of any model or AI platform, allowing people to tune and tweak all the various configuration parameters of their models better, faster, and cheaper than alternative methods. We do that today with asset managers with over $300 billion of combined asset center management, Fortune 500 firms with $500 billion of total market cap, several dozen universities and research institutes around the world, as well as the US intelligence community, and many many more. Basically, anyone who has a model, we help them configure it and experiment with it to get it to the best performance.
Sam Charrington: [00:01:29] So, Scott, SigOpt, and you personally as well, have been huge supporters of everything that we’ve done here at the podcast in terms of AI platforms, from the e-book that we recently published, The Definitive Guide to Machine Learning Platforms, to the upcoming conference, TWIMLcon: AI Platforms. Tell us a little bit about why you’re so excited about the conference, TWIMLcon: AI Platforms, and the space in general around machine learning platforms.
Scott Clark: [00:02:03] Definitely. We’re super excited about this because we have the privilege of working with some of the most advanced firms in the world when it comes to AI and ML, and we’ve noticed that a lot of them have started to build these platforms over the last few years. As you start to productionalize AI, as you start to solve some of the low hanging fruit problems, you start to notice areas of overlap. Areas where engineers can build tools to make the entire modeling process a little bit more efficient, a little bit more scalable, a little bit more robust, et cetera. So a lot of our customers have been building these over the last few years, and SigOpt is kind of a seamless component, via our rest API, to bolt into them and help supercharge that experimentation and configuration tuning aspect of modeling.
So we’re very excited to have someone be shining a light on the problem, and helping those firms that may not have been doing modeling and production for the last decade kind of get a leg up and skip over some of the trials and tribulations that those that went before them have already solved.
Sam Charrington: [00:03:04] That’s awesome. And so you’re personally going to be delivering a session at the conference. What can attendees expect to get out of your session?
Scott Clark: [00:03:15] Yeah. I’ll be building upon some of the stuff in your ebook, talking about how people can make different trade-offs as they look to standardize various components of their machine learning platforms. How they think about what things need to be bespoke and built for their very specific use cases, and other things that can be standardized. Whether that’s using open source tools or partnering with firms like SigOpt. I’ll talk about the different trade-offs there, and how you can have standardization without necessarily constraining what your researchers and modelers are doing as well.
Sam Charrington: [00:03:51] Yeah, I’m really glad that you’re going to be talking about that because I think one of the things that I try to convey in the e-book is that there’s really no one size fits all. Everyone’s coming from a different technology legacy, solving a different set of problems, have a different set of skill sets, and it is important that everyone that starts off on this journey or, you know, is just taking the next step on their journey to figure out, you know, what are the things that make the most sense for them, and how to evaluate the increasing number of options that are available in this space, from open source to commercial products, to as-a-service offerings.
It sounds like you get a pretty broad view of that across the different customers that you get a chance to work with.
Scott Clark: [00:04:38] Definitely, and we see that every customer has a unique, domain they’re working in, a unique set of problems, a unique context that they need to be aware of, and what might work well for market making high frequency trading firm is fundamentally different than an oil and gas company, which is fundamentally different than a credit card company. And by making sure that you leverage your expertise where- … it can make a difference, and then use the best tools in the world where it’s an orthogonal approach can really allow you to accelerate and amplify what you can do individually with constrained resources.
Sam Charrington: [00:05:15] And so your session is called Exploring Trade-Offs and Experiment Management as Part of AI Platforms, and it’ll be on Tuesday at 10:50 on our technology track. SigOpt is also going to have a presence in our community hall. Can you tell us a little bit about what folks can expect to find when they show up to your booth?
Scott Clark: [00:05:37] Definitely. We’ll have a handful of experts from our team on site walking through all the different lessons we’ve learned from working with these leading firms for many years now. We’ll talk about different trade-offs they found, different pitfalls they found, and how they leverage experimentation to really empower their experts to get the most out of their modeling.
Sam Charrington: [00:05:57] Awesome. Awesome. Well, I’m really looking forward to seeing you and the team at TWIMLcon, and I really can’t express enough my thanks to you and the company for supporting the conference. Really, really excited about this.
Scott Clark: [00:06:11] Likewise, Sam. It’s always a pleasure to chat, and we’re really looking forward to seeing you and this amazing conference that you put together.
Sam Charrington: [00:06:17] Awesome. Thanks, Scott.
Scott Clark: [00:06:19] Cheers.
TWIMLcon: AI Platforms will be held on October 1st and 2nd at the Mission Bay Conference Center in San Francisco. Click here to learn more
