On the morning you took over as CEO in 2020, you sent an email to employees saying you'll focus on AI and hybrid cloud as the future's technologies. How has your view on AI's use in business – real-life use cases, saturation – changed since that day?

If you don't mind, I'll use a baseball analogy just because it helps to sort of say – at the time when I called those two technologies, I think people understood cloud and AI as 'Okay, he's saying it, but not clear – is that a market, is it big, is it small, is it really that important? Cloud is 10 times bigger.' So to use a baseball analogy, at that point cloud was maybe the third inning, and AI had not even entered the field. 

If you fast-forward to today, I will tell you cloud is probably in its fifth or sixth inning of a game – so you know how it's going, it's a mature game, you kind of know where it's going to play out. AI is in the first inning, so still unclear who all will be the winners, who all will not win, et cetera. The difference is that it is on the field, so it is a major league game. Unclear on who exactly is going to win – that may be the only question. 

 

Biden's recent executive order had a long list of sections that related to AI-generated content and the risks involved, including the order that AI companies share safety test results with the U.S. government before the official release of AI systems. What changes will IBM need to make?

We are one of, I think, a total of a dozen companies who participated in the signing of the executive order on the 30th of October, and we endorsed it with no qualifications. Look, to me… all regulation is going to be imperfect, by its very nature. There's no way that, even in this case a 100-page document, can capture the subtleties of such a massive, emerging, impactful, nascent technology. So if I put that [thought] on it, then we are completely fine with the EO as written – we support it, we believe that having something is better than not having something, we believe that having safeguards is better than having no guardrails. 

 

Critics say that IBM has fallen behind in the AI race. What would you tell them?

Well, let’s see. Deep Blue was 1996, 1997 – we certainly did monetize it. And then I’d look at it tongue-in-cheek and say, “I don’t know, maybe 20 years of… all the supercomputing records had something to do with the fact that we built Deep Blue.” Because I think from ’96 to 2015, we typically had a supercomputer in the world’s top five list… and all of the work we did there, I think, applied to the way we did weather modeling…

 

Let’s talk about the business of generative AI. This past quarter, IBM released Granite generative AI models for composing and summarizing text. And there are consumer apps galore but what does the technology really mean for businesses?

I think I would separate it across domains. In pure language, I think there will be a lot of – maybe not thousands, but there will be tens – of very successful models. I’ve got to give credit, in language, to what OpenAI does, what Microsoft does, what Google does, what Facebook does, because human language is a lot of what any consumer app is going to deal with.

Now, you would say, “Okay, you give credit to all these people, and you’re acknowledging their very good models – why don’t you do it?” Well, because I do need a model in which I can offer indemnity to our clients, so I have to have something for which I know the data that is ingested, I know the guardrails built in… so we do our own.

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