The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
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Ash Fontana: Search-as-a-service incumbents are AltaVista while Constructor.io is Google
“A lot of the, all the companies in the market today for search as a service are AltaVista, and constructor is Google.”
AI startups must reject on-premise deployments to build defensible data moats
“And some of those customers will ask you to do an on-prem private deployment, will ask you to not use their data to train anything that you do, and you need to reject those customers. Because you are not going to build a company that has any sort of moat aroun…”
Fontana: Zetta maintains a firm thesis against horizontal AI investments
“From the very beginning of our fund, we just said we're not going to invest in anything that's horizontal.”
Ash Fontana: Zetta does not look for revenue traction in seed AI startups
“What we don't look for is traction, right? Like by the time a company has revenue and whatever else, it's sort of, One, if you think of what my job is, it's to find things that other people can't find that are valuable, and it's pretty obvious at the point whe…”
Fontana: Zetta was the first fund focused on intelligent systems
“We lay claim, which sounds like a funny claim to lay today as being the first fund completely focused on intelligent systems.”
Zetta avoids consumer AI and superficial AI overlays due to data disadvantages
“What we're not spending time on are things where AI, well, we don't spend any time in the consumer stuff because a lot of that data is owned by bigger companies, and it's very hard to get a data advantage there, and we don't really spend time on things that ha…”
Fontana: Vertical AI wins through specialized data collection and model tuning
“To make us only invest in vertically focused applications, because that's where you can really get ahead of everyone else by focusing on tuning a model for a very specific purpose, getting data to train a model for a very specific purpose.”
Fontana: 2017 data science tools are like software tools in the 1980s
“The tools that data scientists have available today are like what software developers had in the eighties.”
Ash Fontana: Data isolation prevents Algolia and Elastic from improving search algorithms
“Now, Algolia, Elastic, like, all these companies do that. They make it very easy to deploy a very fast search box on your website, but the thing is, because they guarantee you that they're not going to share any data in any way with anyone they can't really im…”
AI startups boost productivity by hiring from biology, physics, and econometrics
“Looking really far, you know, relative to Silicon Valley mindset, really far afield into some of those disciplines to hire people has been immensely productive for companies that we work for.”
Early AI startups with under $5M in funding hire 50 data labelers
“So, we'll have early stage companies, like companies with, like, you know, less than ten million dollars in funding, some of them less than five million dollars in funding, and they're hiring teams of 40 to 50 data labelers.”
Fontana: Zetta invests when startups prove dataset predictive value
“We're really interested when a company has a unique data set, and they've started to show that it has some predictive value. So it can, you know, they've run an experiment to show that it's predictive of something at a very high level of accuracy or they've pu…”