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 NtropyQuestions: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?LinksWebsite: 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/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy