698: How Firms Can Actually Adopt A.I. — with Rehgan Avon

Pre-LLM Era

Rehgan Avon reflects on the evolution of AI perceptions in enterprises from 2017 to the present. Initially, industries like insurance and banking used basic machine learning models for compliance and explainability, but the advent of large language models has shifted this perspective significantly 1. Companies now see clearer ROI from AI investments, prompting a willingness to explore more complex models. Jon Krohn notes that the barriers to entry have lowered, with tools enabling non-technical users to build and fine-tune models, making AI more accessible 2.

   

Post-LLM Shift

The release of large language models like ChatGPT has transformed enterprise attitudes towards AI. Rehgan Avon explains that these models have sparked interest beyond simple classification or clustering tasks, offering more substantial ROI opportunities 1. The complexity of these models, however, means that understanding their inner workings is challenging, yet the potential benefits drive adoption. Jon Krohn highlights the role of open-source LLMs and parameter-efficient fine-tuning techniques in making AI adoption more feasible for businesses 2.