M&A Science
How to Make AI Practical in M&A
Jun 17, 2024
Michael Bachman, Head of Research, Architecture, and AI, shares insights on practical AI applications in M&A. Topics include retrieval augmented generation, large language models, discriminative vs generative AI, fine-tuning, and agents. Learn how AI is revolutionizing deal sourcing and execution.
37:36
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Quick takeaways
- Practical AI in M&A involves using Large Language Models for tasks like RAG, fine-tuning, and building agents.
- RAG enhances AI models by providing relevant information beyond their training scope, improving accuracy in summarizing documents.
Deep dives
The Significance of Making AI Practical in M&A Deals
Making AI practical in M&A deals involves understanding goals and orchestrating the use of Large Language Models (LLMs) for tasks such as RAG (Retrieve Augment Generate), fine-tuning, and building agents. By focusing on practical applications like RAG fine-tuning agents, LLMs can be enhanced with logic and additional data, improving their functionality. Boomi's platform integration allows for AI model enhancement by incorporating data connectivity, transformation, and logic, aiding in creating efficient designs that include AI alongside other elements.
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