Microsoft and Alphabet both reported mostly strong results Tuesday, but the disparate reactions from investors showed that Wall Street only cares about AI now.
As long as LLM AI models are prone to hallucinating and there is no way to audit how they derive results (eg to verify accuracy), relying on them will have roadblocks/limitations. Once they solve this issue though, that will be a whole different story, I agree. As for other AIs such as image or video generation, I don’t have enough experience to tell…
Hallucinations can be heavily reduced today by providing the LLM with grounding truth. People use naked LLMs as knowledge databases, which is prone to hallucinations indeed. However, provide them with verified data from the side and they are very, very good at keeping to the truth. I know, because we deploy these with clients to great avail.
Image, music, video models are making great strides and are already part of various pipelines, all the way up to the big boy tools like Photoshop (generative fill, for example).
The tech is being incorporated at a large scale by a lot of companies, from SME to megacorp. I don’t see it going away any time soon, even if it doesn’t improve from here on out (which it undoubtedly will).
In Africa, there are three countries that start with the letter “K”:
Kenya
Kingdom of Eswatini (although it’s often referred to simply as Eswatini)
Kiribati
However, it’s worth noting that Kiribati is not in Africa; it’s a Pacific island nation. So, only Kenya and the Kingdom of Eswatini in Africa start with the letter “K”, but most people just refer to Eswatini without the “Kingdom” prefix. If you meant countries solely with the prominent “K” at the start, then it’s just Kenya.
Anecdotal evidence is useless because it can be contradicted with anecdotal evidence.
This mentality is the same as saying Wikipedia is not a source. I agree, there are better regulations that need to be implemented, but the speed at which these things are being churned out and tuned is mind blowing. It’s like if Wikipedia started branching off into sub categories that each have their own specialty, which can be more easily moderated, and then folded back into the more general system.
As long as LLM AI models are prone to hallucinating and there is no way to audit how they derive results (eg to verify accuracy), relying on them will have roadblocks/limitations. Once they solve this issue though, that will be a whole different story, I agree. As for other AIs such as image or video generation, I don’t have enough experience to tell…
Hallucinations can be heavily reduced today by providing the LLM with grounding truth. People use naked LLMs as knowledge databases, which is prone to hallucinations indeed. However, provide them with verified data from the side and they are very, very good at keeping to the truth. I know, because we deploy these with clients to great avail.
Image, music, video models are making great strides and are already part of various pipelines, all the way up to the big boy tools like Photoshop (generative fill, for example).
The tech is being incorporated at a large scale by a lot of companies, from SME to megacorp. I don’t see it going away any time soon, even if it doesn’t improve from here on out (which it undoubtedly will).
The issue is that there are from time to time they still confidently hallucinate and there is no way to detect if they are right or not.
How many countries start with the letter K in Africa?
GPT-4:
Anecdotal evidence is useless because it can be contradicted with anecdotal evidence.
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Hallucinations aren’t the only issue with LLMs, they also have a limited amount of context they can recall and that problem won’t go away.
That problem is very much being worked on
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This mentality is the same as saying Wikipedia is not a source. I agree, there are better regulations that need to be implemented, but the speed at which these things are being churned out and tuned is mind blowing. It’s like if Wikipedia started branching off into sub categories that each have their own specialty, which can be more easily moderated, and then folded back into the more general system.