Like with deep learning before, data remains important in the context of large language models. But this time around, since somebody else trained the foundation model, it is impossible to tell what data is really in there. Since lack of data causes hallucinations etc. this ignorance has pretty severe consequences.
If an AI sometimes lies to me, is it of any use at all? We examine the areas of application for which lying AI is suitable and where it has no place.
What is ChatGPT capable of? Instead of uncritical applause or doomsday scenarios, a level-headed look at the underlying technologies and the possibilities that arise from them.
ChatGPT may help software developers in some cases, but it won't replace them. It can be helpful to a certain degree, but its eagerness to give wrong answers can be counterproductive. (Automatically generated summary)
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