Today we are kicking off a special and new 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: Naré Vardanyan, CEO & Co-founder of Ntropy

Questions:

• Tell me what a large language model is. Is there any difference between this and deep learning models?
• What is the difference between language models and LLM's?
• What sort of data sets were your models pre-trained on? How long does that take?
• How does the cost of training these models factor into your offering?
• Can you talk about latency as a key factor in this process?
• You've told me Ntropy has been doing this since the beginning, but give me a little more - how does this fit into Ntropy's approach?
• What is in the future for Ntropy in this space, specifically as it relates to LLM's and financial services?

Links

• Website: https://www.ntropy.com/
• LinkedIn: https://www.linkedin.com/in/narevardanyan/

Support this podcast at — https://redcircle.com/code-story-insights-from-startup-tech-leaders/donations

Advertising Inquiries: https://redcircle.com/brands

Privacy & Opt-Out: https://redcircle.com/privacy