Their tech. Their products. Their stories. In a tech startup, how do you get from an idea on the back of a napkin to a fully functioning product? Code Story is a podcast featuring tech leaders, reflecting the roads they travelled and the products they created. On the show, we interview tech visionaries, digging into the critical moments of what it takes to change an industry, and build (and lead) a team that has your back. Hosted by Noah Labhart, this show is a window into the digital startup world. In their own words, tech veterans share what it feels like to create a world class product, how to recover from critical mistakes, and how to scale your solution to the masses. This podcast is for the tech leader, CTO, CEO, developer, software architect, startup leader, disruptive visionary - or the curious minded individual, who wants to know what a builder goes through in creating world changing technology.
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Beyond Bots - Ilia Zintchenko, Ntropy
Today we are dropping another special episode of the Code Story podcast, as part of our series entailed Beyond Bots: the REAL impact of AI on financial services, brought to you by our friends at Ntropy. As a reminder, Ntropy is the most accurate financial data standardization and enrichment API. They can take in any data source, any geography, and understand / enrich a financial transition in milliseconds. Made for developers, for fast, easy implementation. Check out their product at Ntropy.com.
Guest: Ilia Zintchenko, CTO & Co-founder of Ntropy
Questions:
- We talked with Nare about Ntropy and LLM's. But let's dig in more.... what is your LLM stack? How did you choose it, what were the considerations?
- What are the system costs in doing this?
- How do you optimize on reliability - what sort of lever are you pulling to ensure reliability?'
- How are you thinking about predictive vs generative learning?
- You guys have been using small and large LM's since the beginning - why is this significant?
- What data sources have you been using, and are there some that are better than others?'
- Have you had to scrub these data sources in any way to prep them for your LM?
- What is the major benefit that Ntropy is providing by using LLM?
- What would you go back and change if you could?
Links
- Website: https://www.ntropy.com/
- LinkedIn: https://www.linkedin.com/in/iliazintchenko/
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