Steve Shillingford highlights the use of AI, NLP, and deep learning in analysing customer behavior. He focuses on transparency to help the progress of start-ups.
1. Tell us about your role at DeepSee. How much of your typical day is involved in innovating AI tech for your customers?
Every second of my workday is focused on delivering on the promise of AI to be in service to human beings, rather than the other way around. So, I guess, ironically, I’m a slave to the project of freedom.
2. What are the applications or rather opportunities you seek to have with your product?
We believe the era of buying Lego pieces in the form of AI technology are over. This has been a result of a 5-10-year orgy of buying and hiring. But, after unfulfilled promises and failed deployments, business executives are telling us they want turnkey solutions that extend and enhance those investments while solving real-world business problems. Whether these are ways to implement AI-powered automation to reduce the expense of manual paper processes, greater efficiency and efficacy to mitigate their business risks, or simply to gain strategic advantage in highly competitive, margin-compressed industries, these executives are under tremendous pressure to operationalize their technology investments in people and products in ways that clearly provide value.
3. How did you approach your first 100 days at DeepSee?
My background is in building cloud-scale platforms that support millions of users and billions of transactions. I supported this at Oracle, where I watched Salesforce.com commoditize their computing platforms to solve the business problems of automating sales cycles. I helped found the first large-scale cybersecurity platform for Big Data Analytics supporting massive systems inside the intelligence apparatus and Fortune 500 companies, and I’ve watched as hype cycle after hype cycle ends the same way: Niche providers consolidate around platforms that serve the greatest audience with the fastest time to value.
That background informed my views on AI…that it’s at peak point solution and that the next 5-10 years will be spent consolidating around the value and the results that AI can provide. Rather than building with Legos and no map, we want to provide the map and curate the best pieces of that Lego set to accelerate AI-powered productivity gains in the enterprise.
4. What are the industries that DeepSee caters to?
The first island(s) for us are capital markets and insurance. Both are highly regulated, highly competitive and undergoing tremendous margin compression. Ergo, they need to do more with less, faster.
5. What are some of the unique lessons you have learnt from analyzing your customer behavior?
The technology that the nerds think is the best isn’t the one that usually wins. The technology that gets deployed the most will. In that vein, we think about the problems people are trying to solve, identify the ways in which AI, NLP, and deep learning can help solve those, and wrap the solution in an easy to use, easy to understand package. Recalling Salesforce, and as a former sales executive myself, I can attest to that fact that business executives don’t care much if you’re using “K nearest neighbor” deep learning techniques to solve the model issues. They care about whether the extraction, analysis, and dispositions are processed accurately and with verifiability for any internal or external auditor.
6. DeepSee Recognized in Gartner’s “Emerging Technologies and Trends Impact Radar for Artificial Intelligence”. Can you elaborate more on the same?
We’re grateful that Gartner agrees with our outlook on the market and the adoption of AI technology broadly. As efforts like “hyper automation,” “composite AI,” and “explainable AI” become commonplace in technology circles, we’re confident this message will resonate with line-of-business executives. Front of mind for many of them will be “Great! Here are faster, better, cheaper ways to use all the available AI techniques in ways that I can explain to my bosses.”
7. What advice would you like to give to the upcoming AI-based tech start-ups?
The most important element of building a successful startup is making your early adopters successful…at all costs. They’re your development partners, so treat them as part of the team, don’t nickel and dime them, and make sure to be transparent and direct with them. They’ll appreciate your acknowledge of a fuck up as much as your promise of a new feature. They want to be able to trust you have their success in mind. Do that and you’ll have a good customer and a great advocate.
8. Can you give us a sneak peek into some of the upcoming product upgrades that your customers can look forward to?
We’re thinking a lot about how to marry the productivity of AI with the record-keeping of the blockchain. We think there’s a path to bring smart contracts to the mainstream. Stay tuned.
9. Which is the one tech breakthrough you will be on the lookout for in the upcoming year?
I think GPT-3 taught us that generative language, that is machine-generated text that “looks and feels” like human-generated content is closer than we think. I even think we’ll see a gradually creeping up the value stack of GPT-3 tools for code generation. That should make every developer sit up in their chair.
10. Please share a recent piece of content (can be video, podcast, blog, movie, webinar) that resonated the most with you with respect to tech or your work in general?
Like most nerds, I loved Ex Machina. I think it’s a great case study in the ultimate challenge for AI—the codification of the most unpredictable organism on earth…humans.
11. What is the one quote that has stayed with you throughout your professional life?
“Are you seeking to know what is wrong with the world? All the disasters that have wrecked your world, came from your leaders’ attempt to evade the fact that A is A. All the secret evil you dread to face within you and all the pain you have ever endured, came from your own attempt to evade the fact that A is A.”
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President and CEO of DeepSee.ai
He is President and CEO of DeepSee.ai, creator of the Knowledge Process Automation industry category, delivering AI-powered automation and productivity via easy to deploy, cloud-based business flows for critical business operations in the Capital Markets and Insurance verticals. He has led several startup enterprises, building cloud-scale platforms supporting millions of users and billions of transactions, and helped found a successful cybersecurity platform for big data analytics supporting network surveillance systems for a range of verticals, from intelligence agencies to Fortune 500 companies. A dedicated advocate for privacy and technology in service of people, he has been featured in USA Today, Fox News, CNN, TechCrunch, Digital Trends, and TEDx.