Scaling BERT and GPT for Financial Services with Jennifer Glore - #561
Analysis
This podcast episode from Practical AI features Jennifer Glore, VP of customer engineering at SambaNova Systems. The discussion centers on SambaNova's development of a GPT language model tailored for the financial services industry. The conversation covers the progress of financial institutions in adopting transformer models, highlighting successes and challenges. The episode also delves into SambaNova's experience replicating the GPT-3 paper, addressing issues like predictability, controllability, and governance. The focus is on the practical application of large language models (LLMs) in a specific industry and the hardware infrastructure that supports them.
Key Takeaways
- •SambaNova is building hardware to support machine learning applications, specifically for the financial services industry.
- •The episode discusses the challenges and successes of using transformer models in banking and finance.
- •The conversation explores the practical aspects of replicating and deploying large language models like GPT-3.
“Jennifer shares her thoughts on the progress of industries like banking and finance, as well as other traditional organizations, in their attempts at using transformers and other models, and where they’ve begun to see success, as well as some of the hidden challenges that orgs run into that impede their progress.”