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Well, every first Wednesday of the month, we are talking about the world of artificial intelligence. We obviously
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know how important this topic is and these discussions are at the moment. Once again, pleasure to be joined by
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Stephano Pantoni, marketing professor here at the Wharton School and co-director of Wharton Human AI
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research. Stephano, great to have you back with us. Thanks for your time. >> Thank you. Then,
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>> you know, it's funny you noted to me earlier this week, I know this is
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something you've looked at. Uh we're starting to see some interesting partnerships kind of play out in the
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world of AI. Uh OpenAI is partnering with Nvidia. We're seeing other types of
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deals right now. So you've called it a a vertical integration going on. What do
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you make of this going on and how it could potentially impact the future success of AI?
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>> Yeah, we've seen just earlier this week Nvidia announcing a deal with OpenAI
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where Nvidia will invest 100 billion. So we're talking about massive amounts of
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capital into open AI and that has been uh one of many such deals between companies that are un matched in this AI
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space. One that you probably read in the news recently was Oracle. Um we've seen
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tie-ups between the big um cloud computing companies and AI labs for example Microsoft and OpenAI um AWS and
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Antropic. And a lot of these deals uh I think you can look at them from a point of view of vertical integration. Somehow
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I could imagine that for example Nvidia collaborated with OpenAI could help Nvidia understand how to best design
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chips for AI training. So perhaps there is interesting transfer learning this way. But some people are also wondering
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about a a certain circularity in this investments where Nvidia will put money into OpenAI. OpenAI then gives the money
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back to Nvidia by buying the chips and the similar you know um AWS gives money to Entropic and then Entropic gives
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money back to AWS by buying cloud computing. So uh some people are also worried a little bit about this um
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inbreeding let's say of investments. So basically the money comes and goes and
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kind of changes hands but it stays in the same loop. Um but uh certainly big news on that front. Yeah,
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>> it doesn't feel like though that we should be surprised to see all of this
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play out when you think about how seemingly important we believe AI is going to be to so much of what we do
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over the next many years. >> Yeah, for sure. And if you uh if you believe the assumption made by many in
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the you know in the tech sector that we are you know not very many months away from artificial general intelligence or
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something like that that will be able to perform many many tasks then spending those enormous amounts of money
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certainly makes sense. >> Uh one of the other areas I know you're focused on is copyright issues and we're
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seeing some of these cases play out in the court. Anthropic being the latest. They just settled a a lawsuit.
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>> Yeah, that was an interesting piece of news came also a few days ago. We've
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seen judge agreeing to a uh settlement that um um Anthropic basically um is making with a set of content creators
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for uh um the claim that Antropic has used pir pirated books to train its AI models. They settled for 1.5 billion and
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this is the first settlement of this kind and I think we're going to see more
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of this agreements between the I companies that need data for training these models and content creators,
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publishers, authors who have been providing uh that data. I think that's the interesting thing because, you know,
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I think the assumption was for for many many years that the distributors had the
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the edge, had the control in this process, but we're starting to see the content creators, and we're seeing this
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play out in the music industry a little bit, that the content creators feel like
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they have more of a say right now. >> Yeah. And I think increasingly creating
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good uh content that can be used by AI tools to uh um AI companies to create AI models. I think it's a very strong uh
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value creation um you know potential and if you look at for example few months ago Reddit's IPO a lot of the um
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narrative around the stock was about the value of Reddit data for training IM models. So it's really economically
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significant. Uh you guys recently just finished a Gen AI conference. Give us a little uh background on what some of the
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important themes of the conference were. >> Yeah, we hosted our generative AI for
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business conference uh three weeks ago in San Francisco. the third year running we're doing this and it's a great way of
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bringing top researchers working at the uh cutting edge of AI applications in business over to our San Francisco
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campus to discuss AI uh for a couple of days lots of interesting stuff to talk more but we don't have the time but just
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to highlight one topic where we've seen a few sessions there were three or four
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sessions where researchers were exploring the power of synthetic data where basically the idea would be can We
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learn something useful about people by talking not to people but to AI models. And the idea will be predicated on the
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fact that these AI models are trained on so much human data. They know so much about how people behave and how people
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think that you might be able to get some useful insights about for example your customers, what they like and how they
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think about the product category um by just interrogating those networks rather than uh going to talk to real consumers.
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maybe you know in addition I would say but we've seen quite a few interesting
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use cases and we are just learning how this is going to work but it's a very
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interesting new frontiers in the uh industry of marketing services and customer insights
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>> and I'll finish up I know you had maybe wanted to touch if we had time on a new
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study that had come out of Columbia University as well >> yeah that was one of the studies being
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presented at the conference was really interesting they uh um a team of researchers led by Olivia Tuba has
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created a uh digital twin data set where they are interviewed interviewed for several weeks, 2,000 people and then
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they uh created a model of these people based on all the answers that they got on over 500 questions and now you can
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have a synthetic version of this panel that you can use to run studies, ask questions and so forth. So it it would
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be used just specifically for that because it seems like a very unique kind of development and how it could
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potentially be used uh larger scale in the public moving forward. >> Yeah. And lots of researchers are
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interested in using this kind of data to test the capabilities of AI exactly in this domain of synthetic data.
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>> Stephano, always great to talk with you. Thanks very much for your time this
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week. >> Thank you Dan. Stephano Pantoni, marketing professor here at the Wharton
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School and co-director of Wharton Human AI research.