At the recent TechSurge Deep Tech Summit, Alphabet Chairman John Hennessy sat down with Axios journalist Kia Kokalitcheva for a wide-ranging fireside chat discussion on current tech trends.

You can read a brief transcript of part of the discussion or watch the full interview with John below.

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Q: What do you think of ChatGPT? Are you impressed?

A: Well, I'm impressed with two things. One, first of all, the quality of the natural language abilities, both to interpret a query, but also to respond to something. The generative function. Also, I'm impressed that it manages to, at least at a fairly superficial level, get a lot of things right. Maybe the third thing I'm impressed by is it's always confident that it has the right answer even when it doesn't. That's, of course, one of the flaws of these kinds of technologies. They can't tell whether they actually have the right answer. But I think it's a big step forward. It builds on long history of investments in AI.

Q: You're the chairman of Alphabet. I'm curious how you think about this from that standpoint. What is the place of these types of apps for big technology companies? 

A: Part of it is just a demo to show that this capability exists. I don't think it's yet productized, but you can imagine a time when people sit down in front of their computer and say, "Write me this report on this subject or something that's really close." It's early days yet. We just have to continue to push, get the technology out there and then make it practical.

I think we're going to have to tame the cost of these things, figure out how to get models which are more appropriate, maybe even more fine tuned for particular tasks. Rather than try to build one system that does everything, we build systems which are focused on particular things. 

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I have never in my entire time as a computer scientist – which is now getting to be many decades – seen a technology move as fast as the deep neural network machine learning technologies are moving right now.

‍- John Hennessy

Q: Besides chat apps and even image generators like DALL-E, what do you think will be the other sort of contributions from generative AI? 

A: I think a good way to think about this is how do you use this as an amplifier of human ability? I like that word, amplifier, because you're not really replacing it. Take DALL-E, right? Suppose I need some graphics done for something. I need a picture generated from some text. Like PowerPoint. How do I get that, right? I may not get exactly what I want. Or same thing with Stable Diffusion as a version of the video app. Same thing. I may not get a video that's perfect or a PowerPoint presentation or a paragraph that's perfect. But maybe I get something I can really work with and enhance and then use some human intelligence to make it even better. That's why I like the word amplifier.

I think the world is going to change as this technology gets better and better. Some of us thought that point at which we'd have artificial general intelligence was 40 or 50 years away. I think everybody's horizon has moved in by probably 10 or 20 years. Now we'll see what happens. I mean it is amazing when you think about this. These models keep getting bigger and every time we make a jump up in the size of the model, we seem to be able to do new tasks. We don't know where that's going to plateau yet. I think we're just still figuring it out.

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Q: We're seeing companies shed a lot of employees, tightening their belts. How do you think about the ability for big tech companies to continue to innovate and provide some of that new cutting-edge technology if they're seemingly de-prioritizing the resources?

A: First of all, this is a challenging time for the industry. We were coming off of when the pandemic began to wane. Technology just took off and everybody was growing. There was an incredible war for talent in the Valley. I think nobody really saw the macroeconomic shift that was going to occur. Now we have to deal with that issue and pay the price of it. I

Jim Morgan, who was the CEO of Applied Materials for many years, said something to me that I always remember: "Great companies do really well in downturns because they make tough decisions. Then when the upturn comes, they're in a better position." I think one of the things that happens is when things are going gangbusters, you start whole new sets of projects sometimes without thinking which things are really aligned with your market. You get too many products; you get too much spreading out.

I'm reminded that when Steve Jobs returned to Apple, the first thing he did wasn't invent new technology. He cut the number of products that Apple was shipping in half because he said we have too many products, and as a result, we have too many things which are B-level or C-level things as opposed to A-level things.

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