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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