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Many companies that are building AI products for their users are not primarily AI companies. Today on No Priors, Sarah and Elad are joined by Emily Glassberg Sands who is the Head of Information at Stripe. They talk about how Stripe prioritizes AI projects and builds these tools from the inside out. Stripe was an early adopter of utilizing LLMs to help their end user. Emily talks about how they decided it was time to meaningfully invest in AI given the trajectory of the industry and the wealth of information Stripe has access to. The company’s goal with utilizing AI is to empower non-technical users to code using natural language and for technical users to be able to work much quicker and in this episode she talks about how their Radar Assistant and Sigma Assistant achieve those goals.
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Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @emilygsands
Show Notes:
(0:00) Background
(0:38) Emily’s role at Stripe
(2:31) Adopting early gen AI models
(4:44) Promoting internal usage of AI
(8:17) Applied ML accelerator teams
(10:36) Radar fraud assistant
(13:30) Sigma assistant
(14:32) How will AI affect Stripe in 3 years
(17:00) Knowing when it’s time to invest more fully in AI
(18:28) Deciding how to proliferate models
(22:04) Whitespace for fintechs employing AI
(25:41) Leveraging payments data for customers
(27:51) Labor economics and data
(30:10) Macro economic trends for strategic decisions
(32:54) How will AI impact education
(35:36) Unique needs of AI startups
4.6
9393 ratings
Many companies that are building AI products for their users are not primarily AI companies. Today on No Priors, Sarah and Elad are joined by Emily Glassberg Sands who is the Head of Information at Stripe. They talk about how Stripe prioritizes AI projects and builds these tools from the inside out. Stripe was an early adopter of utilizing LLMs to help their end user. Emily talks about how they decided it was time to meaningfully invest in AI given the trajectory of the industry and the wealth of information Stripe has access to. The company’s goal with utilizing AI is to empower non-technical users to code using natural language and for technical users to be able to work much quicker and in this episode she talks about how their Radar Assistant and Sigma Assistant achieve those goals.
Sign up for new podcasts every week. Email feedback to [email protected]
Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @emilygsands
Show Notes:
(0:00) Background
(0:38) Emily’s role at Stripe
(2:31) Adopting early gen AI models
(4:44) Promoting internal usage of AI
(8:17) Applied ML accelerator teams
(10:36) Radar fraud assistant
(13:30) Sigma assistant
(14:32) How will AI affect Stripe in 3 years
(17:00) Knowing when it’s time to invest more fully in AI
(18:28) Deciding how to proliferate models
(22:04) Whitespace for fintechs employing AI
(25:41) Leveraging payments data for customers
(27:51) Labor economics and data
(30:10) Macro economic trends for strategic decisions
(32:54) How will AI impact education
(35:36) Unique needs of AI startups
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