| Re: Aliza [message #97284 is a reply to message #97281] |
Wed, 27 December 2023 09:13  |
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Wayne Parham
Messages: 18752
Registered: January 2001
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Illuminati (33rd Degree) |
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There are a lot of similar technologies in chatbots these days. Most are transformers using a large language model, which is a form of recursive neural network. Some use multi-modal models, having access to text, images and sometimes sound. Those are tricky to get the individual modes to tie together but the goal is better accuracy.
Some think that will cause emergent behavior - which I agree, that's the whole point of any of these kinds of systems - but I still think we have some addition hurdles to cross. I think we need models that continuously learn rather than being trained before use. Emergent behavior is always the result of complex systems, but how close that emergent behavior resembles true intelligence requires understanding of concepts, in my opinion, and I think that will require both multi-modal approaches and a continuous learning mechanism. Only then can it gain experience and eventually, perhaps, self-reflection.
But back to your question, most of the "widgets" or automated assistants use either a rules-based approach or a limited database targeted for the subject desired. Aliza is a "generative" system, meaning its goal is to create new content based on the data it has been trained upon. I have it dialed way back at "temperature 0.0," which is a configuration setting that makes it be as definite as possible.
At this setting, if it doesn't "know" something, it will still make inferences - actually, it will always make inferences or rather try to combine words and phrases that are often used together - but the point is that the matches need to be closer than if the temperature setting were higher.
I have also started "fine-tuning" training in cases where I found it inaccurate and will continue to do that as I find need. So please provide feedback if you find inaccuracies.
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