I have been working with AI since the ‘90s, case-based reasoning since 2010, and generative AI for the past year. I have seen it go from a wonder in the eyes of the more geeky public to an eyesore as they put in terrible prompts and then berated the answers.
I have heard of lawyers using hallucinated case law to justify their position in court. And perhaps most egregious: I read there was Chicago pizza in Florida. When I asked chatGPT it told me the name Nancy’s Pizza, with an address only 30 minutes from home. How could I not know: Nancy’s Pizza, who I give credit for inventing Chicago Pizza, actually had a location nearby. As I calmed down and started planning a trip, I checked Google Maps. No Nancy’s pizza in Florida. Oh no… How could I not have supported Chicago Pizza, and now it was gone? Using old-fashioned Google, I learned there had never been Nancy’s pizza in Florida. Just a Hallucination. This was probably 6 months ago, before chatGPT 4o. I just tried and ghatGPT only recommended two real pizza places in the area.
Now I describe AI’s timeline as “one AI month is equal to 8 dog years” So now I ask chatGPT (or the other AI models I am leaning toward) to justify their answers and warn me of hallucinations.
I have been spending significant time trying to identify where generative AI goes wrong and how to remove hallucinations, first with prompt engineering, then with fine-tuning, and RAG (using our own data or third party data) lowering the temperature (reducing creativity of the AI model) and more.
I am fortunate that I am working with AI from several directions: Non-Profit organizations providing answers to sometimes hard questions, and SEERai, describing the characteristics of engineering products so the SEER models can provide cost, schedule, and risk.
I realize anything I write may be wrong in a few months. For example, just this weekend, a new AI model based on Llama was introduced that allegedly self-corrects errors. And now people are contesting it, illustrating my dog year analogy.
I will be blogging about this journey and the lessons learned.
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Dan Galorath
Dan Galorath is a software developer, businessman, author, and founder and CEO of Galorath.
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