Person
1 episodes · 21 quoted claims
Google's first internal generative AI uses were in Workspace, covering documents and email, such as summarizing and personalizing text.
“Was was around workspace, just using our documentation, our email. You all, I'm sure, use it. So it was like, can you summarize this better?”
Google's internally tested Workspace generative AI features were launched externally as Duet AI.
“Was gradually launched, and now it's Duet AI, uh, part of workspace.”
Kawal Gandhi uses Gmail's translation feature so his mother, who speaks Hindi, can read his emails in that language.
“I like the translation feature for my mom because, uh, she speaks Hindi, she's really fluent in it.”
Google Cloud's Vertex AI Model Garden includes domain-specific models such as Med-PaLM and Sec-PaLM.
“That's where we have domain specific models, so it's Med Palm, uh, sec palm.”
Kawal Gandhi said open source models such as Llama and Stable Diffusion were coming to Google Cloud's platform.
“I'm really excited to see, like Llama, stable diffusion, uh, other variations coming onto the platform”
Gandhi said Google Cloud has invested in model operations, including handling model drift, tooling and safety.
“Because we've spent a lot of time really specializing around the model drift, operations, tooling, safety around it.”
Gandhi described enterprise AI adoption as moving in order from efficiency to productivity gains to creativity.
“it's like efficiency, productivity gains, and also creativity. And I did it in in order because inside the enterprise”
Gandhi gave customer support as an early use case, where the key measure is that customer satisfaction (CSAT) does not drop.
“How can I make my support better? So and not drop my CSAT, that's the KPI I'm going to look at.”
Gandhi said enterprise interest in generative AI started in sales and marketing.
“It started from sales and marketing, like as soon as these came out.”
Gandhi named gaming as an industry already scaling multimodal AI.
“I think gaming is a really good industry which is kind of scaling out multimodality.”
Gandhi said more than 10,000 people had been certified in generative AI on Google Cloud Platform.
“We have more than 10,000 people certified now, just more on GCP, uh, generative AI globally”
Gandhi said fine-tuned adapter models and related artifacts stay within the customer's own tenant on Google Cloud.
“The adapter model, the certification, everything stays in their tenant.”
Gandhi said engineering teams were adopting AI coding models faster than he expected.
“I'm seeing engineering adopt it much faster internally now, uh, with the coding models, with the open source”
Gandhi said GPUs are widely available and many engineers are trained on them, which is a consideration when choosing between TPUs and GPUs.
“Because there is this that was, you know, externally available, and a lot of people are trained up.”
Gandhi said Google was investing heavily in its next TPU generation, which he referred to as V5, with a focus on scaling inference.
“We have V5V, etcetera. We are investing, uh, heavily, and you know, others are doing.”
Gandhi said the NVIDIA GPU shortage comes up in customer conversations with Google Cloud.
“It definitely is mentioned, uh, as we think about it in the conversations, uh, it's always the the discussion that comes up.”
Gandhi said Google Cloud aims to make new models such as Llama available in its Model Garden so customers can use them within existing applications.
“can we make it available like Llama inside our model garden? And then they can use it inside their application”
Gandhi estimated that models make up about 50-60% of the work in an enterprise AI project, with integration and operations making up the rest.
“Um, and I think models, in my mind, are like, fifty, sixty is the is the work around, and how do you leverage your current investment?”
Gandhi said Google Cloud is exploring synthetic data, including for use in regulated industries.
“And we're also looking at synthetic data as well. Can we use in regulated industry some of the synthetic stuff”
Google Cloud offers data labeling and related services through a partner marketplace integrated into its platform.
“So we have, uh, the partner ecosystem through that, we provide a lot of partners, so exactly the marketplace.”
Gandhi said data from partner labeling services is kept in the customer's project and not shared with other customers.
“So we make sure those pipelines and entitlements stay in the project.”