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Message: <blockquote data-quote="Gorgon Zee" data-source="post: 9289373" data-attributes="member: 75787">This is a little bit late coming to the thread, but in case anyone reads this thread in the future, let me give some hopefully helpful comments. My job is as an AI/ML Architect and I've followed this discipline for 20+ years. I am currently spending about 50% of my time researching ways to use Generative AI's to improve health care. I work for a not-for-profit; our motivation is simply to make healthcare better.<ul> <li data-xf-list-type="ul">A very high level take on Generative AI's is that they produce new text/images/whatever by starting with a random pattern of variables that represent an answer and repeatedly modifying that random answer with probabilities related to the model's parameters until the solution is stable.</li> <li data-xf-list-type="ul">They are thus inherently non-deterministic. However you can set two sets of parameters to make them more so:<ul> <li data-xf-list-type="ul">Start with the same seed in the random number generator so the initial state is determined by that seed (only really useful if you want to reproduce an experiment)</li> <li data-xf-list-type="ul">Set the temperature parameter to a low value. That means that at each iteration, it is more likely to choose the "most likely" next state of answer. With temperature zero, it will always chose the "best" answer state and so will always iterate to the same solution.</li> </ul></li> <li data-xf-list-type="ul">Training a GenAI model does not modify code; it simply sets parameters. Roughly, it's the same as training any neural net or even basic Baysian models. You present it with an example, and the parameters are modified a little bit to make it more likely to be able to reproduce that example.</li> <li data-xf-list-type="ul">The reason that GenAI is not easily explicable is simply that there are a lot of parameters. Typically billions. And they interact non-linearly and are not tied directly to properties of the inputs. Contrast that with something like linear regression which has few parameters, each of them is tied to specific input features, and they interact in linear, predictable manners.</li> <li data-xf-list-type="ul">When we say a GenAI "hallucinates" or "says something false", we are trying to think of the way we answer a question and apply it to the GenAI. If I am asked "Who killed Richard III" I search my memory for facts and try to find the right one. An error I make is to believe something is truthful when it isn't. A GenAI program has absolutely no concept of truth at all. It is simply trying to find a set of words in the sea of all possible words that when place at the end of the words "Who killed Richard III?" best fits the set of probabilities that it has been trained on.</li> </ul>The above is obviously very simplified, but hopefully helpful.</blockquote>

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