This document discusses harnessing large language models (LLMs) for business applications. It provides an overview of how LLMs have progressed from foundational models to today's large language models. The document then discusses several potential use cases for LLMs in business, including for sales. It notes that LLMs have potential benefits but also risks like lack of transparency, bias, and unreliability that must be addressed. The document proposes a framework for assessing the feasibility of LLMs for different business uses.

1. Harnessing the Power of Language Models (LMs)
for Business Applications
Babar M Bhatti
June 15 2023

2. Babar M Bhatti
https://www.linkedin.com/in/bbhatti/
https://thebabar.medium.com
Dallas AI (2017-Present)
Largest AI Meetup in Texas (5,000+ members)
MutualMind (2010-17)
Social Media Analytics, SaaS
CoreLogic (2018-2021)
Digital, AI, ML
IBM (2021-)
Customer Success - Data and AI

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1. How did we get to Large Language Models (LLMs)
2. What’s different and exciting?
3. The business use cases for Large Language Models (LLMs)
4. Unlocking the power of LLMs : prompts agents and more
5. Tips on how to be successful with LLMs for business
Overview of Today’s Talk

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Generative AI

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Foundation Models

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Large Language Models

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What Changed?

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Generative AI Applications
From Business to Technology, Reasoning and Poetry

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Sample Use Case: Sales
Sales is well-suited to the capabilities of
generative AI models. Selling is interaction and
transaction intensive, producing large volumes
of data, including text from email chains, audio
of phone conversations, and video of personal
interactions.
These are exactly the types of unstructured
data the models are designed to work with.
The creative and organic nature of selling
creates immense opportunities for generative
AI to interpret, learn, link, and customize.

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LLMs are Powerful But Potentially Toxic and Hazardous
Transparency,
Intellectual Property,
Privacy, Black Box,
Lack of groundedness,
Inaccuracy, Bias,
Non-representative

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FMs / LLMs Have Forever Changed the Way We Work
Are these AI models reliable and trustworthy?

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Conversational AI is the New Default for Customer
Interactions

16. Framework to Assess Feasibility of Large Language Models For Business
Assessing
Feasibility of
LLMs
If Yes, Exit
Requires accurate or
factually correct
information?
If No, Exit
Are there sufficient filters
and guardrails in place
(e.g. human reviewers)?
If Yes, Exit
Model results need to be
explainable?
If No, Exit
Can the AI meet legal or
compliance requirements, if any?
If Unsure, Exit
Is the potential harm within
acceptable risk range?

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Human-like Intelligence Or Stochastic Parrots?
What if AI is sentient? Nick Bostrom

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Extract Value from Black Box LLMs via Prompts

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Questions for Business Leaders
How to make the LMs reliable? One Model or Custom Models?

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Which AI will you use: Closed or Open Source?

21. Babar M Bhatti
https://www.linkedin.com/in/bbhatti/
https://thebabar.medium.com
Dallas AI (2017-Present)
Largest AI Meetup in Texas (5,000+ members)
MutualMind (2010-17)
Social Media Analytics, SaaS
CoreLogic (2018-2021)
Digital, AI, ML
IBM (2021-)
Customer Success - Data and AI