Understanding IP Matters: AI Beyond ChatGPT — How a Healthcare Investor and INDYCAR Engineer are Taming Big Data

OpenAI shocked the world when it released its spectacularly helpful, free generative AI platform, ChatGPT, on November 30, 2022. AI has existed in various forms for decades but it has never been so widely accessible or boldly efficient. No one can deny that we’ve been living in an AI world ever since.

But ChatGPT is just one example of how AI is being used by businesses.

To unpack why and how different forms of artificial intelligence are being adopted by businesses and their impact on intellectual property rights, Bruce Berman hosts two innovative exponents of AI on the seventh episode of the third season of his podcast “Understanding IP Matters.”

Alex Castrounis is founder and CEO of Why of AI, an author, and a professor of AI at Northwestern University’s Kellogg and McCormick MBAi program. He has two decades of experience advising startups to Fortune 500 companies on using data, analytics, and AI models to drive business growth and customer success. He is a former IndyCar engineer, race strategist, and data scientist.

Armando Pauker is co-founder and general partner at Tensility Venture Partners, whose investments include artificial intelligence, digital health, cyber security, and fintech. He has served on the boards of six companies, all of which have exited positively through acquisition.

Key Responses

Armando, as an investor, what attracts you to AI today?

Armando Pauker: “There are many things. Business intelligence is about really about making predictions and AI goes beyond that, from being predictive to prescriptive. That’s the next frontier….

We see within AI the ability to look at those things that humans have a hard time looking at and being able to look at the totality of potential answers. The nice thing about AI is that when it looks at a data set, it looks at all the strategies, all the potential outcomes. It goes beyond human bias. Because, as humans, we kind of know what’s going to work and what’s not going to work. We put our efforts into what we think is going to work — but AI can free us from that and look at all of these things that we thought were not possible.”

In generative and other AI models, data sets can be a mystery. A lot of unlicensed content gets scraped and included whether the owner likes it or not. Unlicensed is sometimes under fair use, sometimes it still has yet to be determined. The lack of transparency is troubling. Can anything be done to improve this?

Alex Castrounis: “This question is very interesting. Obviously — maybe it’s not so obvious —we’re going to see a lot of activity around the legal aspects of this. Probably going up to the Supreme Court in the not so distant future in terms of the copyright issue, which we’re seeing with the strikes that happened in Hollywood, with SAG AFRA, and everything else. It’s a concern, especially for creative people who make a living creating content….

These models are scraping the Internet. They’re using Wikipedia, books, and scripts, podcast audio that’s been transcribed — you name it….

Once that happens, you have this model that — to Armando’s earlier point about it all being mathematics — just sits there and can be hundreds of billions of numbers; what we call in the field ‘parameters.’ When you put a prompt in, all that really happens is those numbers, those parameters, do mathematical operations and then spit something out.

The model is not pulling from a database. The parameters have no understanding of the script from the movie Die Hard or some painting that someone did or whatever. It’s just a bunch of numbers. The thing is hopefully creating something new, but [my point is] it doesn’t understand any of that stuff….

In many ways, it’s going to come down to is copyright laws and where they stand and whether or not they’re even updated enough to handle this AI thing that’s happening. And then secondly, what are the terms of use on these sites, right? Wikipedia is open, but other sites in their terms of use say, Hey, it’s not okay to scrape our data.”

How do you see AI working with medical research?

Armando: “Life science is about 25% of the investments we do…. We humans are limited — we’re limited by what we know….

What AI drug discovery does is try things that we know don’t work to see if they could work — and many times they do. The reason is because we’re too tied in one vertical, in one silo.

So, yes, pharma can do this. But historically, you know, startups move very fast. Startups can create new data sets very fast and then use the very new techniques to be able to generate new formulations. This has been done since the beginning of time. Yes, they do a lot of in-house, but pharma’s model many times is that they also buy a lot of startups once the startups have those formulations tested and have gone through FDA clearance.”

What is an idea or concept you would like to leave listeners with?

Armando Pauker: “The biggest thing is that AI is a set of math. It’s not only math; it’s probabilistic math. So, anything that it gives you are the probabilities of something happening… For anyone who is thinking, ‘This thing is thinking!’ or that it has a conscience — we’re years away from that.”

Alex Castrounis: “Learn about AI. Learn how to write prompts, learn more about it, learn what you can do with it, whether for yourself or your organization. We’re seeing a lot more AI stuff and it’s going to keep going. It’s not going backwards.

The train has left the station, and so it’s really important for people to understand it as well as they can. You don’t need to become an AI expert or a data scientist or machine learning engineer. Understand it and start to figure out how you can use it in your daily life and work.”

More Highlights

Listen to the entire episode to learn why the algorithims underlying AI aren’t likely to be patented; the three basic types of AI being used by businesses today; the technology companies leading the field and their different approaches to commercialing and monetizing AI products; and how IndyCar racing uses AI to make sense of immense amounts of data in real time to make cars go even faster.

Meet Alex and Armando at the Intellectual Property Awareness Summit in Evanston, Illinois at Northwestern University on March 18th, where they’ll be speaking about AI. IPWatchdog readers are eligible for discounts.