What Google Cloud Can Teach Enterprises Developing & Rolling Out AI Tools, With Kawal Gandhi

**Sarah Guo** (0:05)
This week, Elad and I are joined by Kawal Gandhi. He works in the office of the CTO at Google Cloud, where he's the lead for Generative AI.
Gandhi comes from a long history of working on search and ads at Google before Cloud. Welcome, Gandhi.

**Kawal Gandhi** (0:17)
Thank you.

**Sarah Guo** (0:18)
How did you end up working on Cloud and then AI in particular from other projects at Google?

**Kawal Gandhi** (0:24)
Sure. I really worked deeply with a lot of our advertisers around search and ads for shopping and travel, especially commercial-based queries. As working with them, they required a lot of storage, compute infrastructure constantly around making their ads perform better, which led us to Cloud and then Cloud solutions around using some of that to create smart analytics, machine learning pipelines, more around documentation AI, conversational AI.
Here we are. We've been doing it for a while, but now it's Generative AI, where how can you make that customer experience much better with the information that they have?

**Sarah Guo** (1:07)
Just in terms of beginning to broadly at Google, incorporate AI into GCP, what was the origin story of that? Is it TPUs, APIs, some customer need that you specifically saw?

**Kawal Gandhi** (1:20)
As we were getting into the Google Cloud, this goes back into how can we provide them with latency, high response, better experience with data, is how our customers started leaning towards Google, in my mind. From the beginning, it was more around machine learning and AI as a differentiator to work with Google, and how could they use that data better on our platform was a constant ask. So as we were on the journey of Google Cloud, it was all about data, AI, storage, privacy, security, and kind of having that same deep technology that we used inside Google, how could we leverage that and offer that in market?
So lots of learnings because what we built internally, we had tools, frameworks, et cetera, that took us time to kind of make our platform rich for our customers from regulated to non-regulated environment and how to leverage some of their current investments on our platform.

**Elad Gil** (2:23)
What are some of the internal use cases that have really driven that behavior in terms of the stuff that you ended up building for your customers? I know that a lot of what Google does is sort of dog food its own APIs or products, and then it starts launching them externally as sort of a service that other people can use.
What were some of those first applications of generative AI that occurred internally that then caused you to decide to do these things externally?

**Kawal Gandhi** (2:43)
Yeah, the only ones I think it's all public now was around workspace.
Just using our documentation, our email, you'll, I'm sure, use it. So it was like, can you summarize this better? Can you personalize this better? Can you offer me a suggestion?
And all this kind of gradually, as we tested it internally in Dogfood, we gradually launched it externally because we see a lot of progress that we make internally in terms of efficiency, productivity gains, folks can use it in their spreadsheet creation, et cetera, was gradually launched and now it's Duet AI, part of Workspace. So these are constantly being Dogfood and tested. We call them experiments. And as the research team leans in and looks at some of these, we add it to the platform and bring it forward in our products.

**Sarah Guo** (3:34)
Is there a single feature or a product you launched within the internal Google version of Duet, the Workspace AI products that have gotten the most uptake or that you're most proud of?

**Kawal Gandhi** (3:44)
Yeah, I think we're seeing it across the board. A-ha moments, as we launch, we're seeing it in documents, in terms of generation, summarization. We're seeing it now in slides with suggestions on images and new image creation, which is to take time for someone to go ask a studio or an agency and you have a prompt that you can give and say, here's something I'm thinking about. So Sarah, we've seen kind of intake on all those features. Also email generation has been super helpful from productivity perspective, not only for the consumers, but for enterprises as well.
Security, we don't talk about it a lot. I think it's super secure how it's sent, how the links are used.
Those are something we really take it seriously.

**Sarah Guo** (4:32)
How far do you think we can take it with email generation? Cause I maybe spend four hours of my workday just trying to keep up with my inbox. So this is of great personal importance to me.