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As with all the discussions of AI, and particularly LLM's and Generative AI, this is a discussion of the challenges of getting it right, making it useful, and using these tools successfully in a business.

Major Points:

1. There are a large number of commercial and open-source models available.
2. Tens and even hundreds of millions of dollars were spent, and equal amounts of person years were expended to create these models. Your business cannot and should not duplicate this effort and expense.
3. You therefore must know the best way to use the models, and that is to collect enough data about your operations to extend the models to know about your enterprise.
4. You also must have enough subject matter expertise to know when the models are producing incorrect answers, such as "hallucinations".
5. You must be aware of the security challenges the models represent, particularly in sensitive industries such as finance and health care.
6. You must be able to create testing to ensure you know and limit the risks of incorrect answers, and security problems

There is no such thing as a free lunch. You must expend the effort necessary to teach the models you use, test those models, and ensure that you have limited the scope of security problems from the models.

Cory Doctorow - Human in the Middle AI

ChatGPT 

Gemini 

Anthropic Claude

Episode Transcript