AI Rewind: Upskilling, Data Privacy, and Choosing LLMs

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This week, my newsletter was about Considerations for Enterprise GenAI Adoption in 2024, which could have been more than just a newsletter. It could have been a book.

So here are a couple of things to consider when adopting Generative AI. It’s a short list that applies to almost everyone.

  • Upskilling - Most everyone reading this is a skilled operator in some domain. We will all need the skills to use these new AI tools effectively. Here are a couple of resources I think are useful:

  • Data Privacy - I’ve been working with some clients around this topic, and it’s hot. When we use AI systems, there’s a big risk of how data we put into them being used or privately leaked. Here’s a very basic but good primer from the Congressional Research Service from last year that was prepared for Congress.

  • Model Choice - Models are the brains of the chatbots we use, like ChatGPT. While ChatGPT’s GPT is the most powerful and widely used, several great models can do things better than ChatGPT. For example:

    • Claude - I think this writes better than ChatGPT and doesn’t have the weird AI speak with things like paradigm, delves, landscape, and other consistently weird word usage.

    • Perplexity - This is a better search experience than Google and uses

    • Poe - This chatbot from Quora allows you to interact with several models to try them out from a single interface.

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