Support NeoGAF

[IntentionalPun]

The problem even with improving hallucination rate, is it's still really bad. It means people trust the models more, which means they use them for more or bigger things, and the actual amount of hallucinations ending up in some sort of output used for business (say, production code) doesn't necessarily decrease.

The models are getting insanely powerful but the more you do with them the more out of control it all sort of becomes. And it's all at a massive amount of cost, all the solutions to solve issues with AI tend to not just be the model itself but by all kinds of post-processing.

 

[AJUMP23]

So like most humans.

All humans can be original, but only a few are exceptional at it.

 

[Zacfoldor]

The problem even with improving hallucination rate, is it's still really bad. It means people trust the models more, which means they use them for more or bigger things, and the actual amount of hallucinations ending up in some sort of output used for business (say, production code) doesn't necessarily decrease.

The models are getting insanely powerful but the more you do with them the more out of control it all sort of becomes. And it's all at a massive amount of cost, all the solutions to solve issues with AI tend to not just be the model itself but by all kinds of post-processing.

Hallucinations can also be addressed by an AI aggregator, which is what copilot is amongst other things.

So an AI aggregator allows you to ask multiple AI agents across different platforms the same question.

You can read all 5 outputs or you can ask for aggregate output, which will eliminate outliers.

Thus, no hallucination.

Similar to humans who have seizures, diseases, collapses. The answer to hallucination is more AI. Since multiple ai agents will never hallucinate in exactly the same way(especially across platforms/models) a consensus will only ever be formed around correct data. This is actually a very easy problem to solve. The OP could do that and eliminate them today. So you can put thousands of humans on one problem. You can do so with AI as well. The tools are already built in. Just buy the 300 dollar a month grok plan and select team of experts, or use copilot to survey all the AIs at once.

 

[IntentionalPun]

Hallucinations can also be addressed by an AI aggregator, which is what copilot is amongst other things.

So an AI aggregator allows you to ask multiple AI agents across different platforms the same question.

You can read all 5 outputs or you can ask for aggregate output, which will eliminate outliers.

Thus, no hallucination.

Eh, I don't think this is true in any way. GitHub Co-Pilot like a lot of tools allows you to select a different model, or it has an auto-select mode where it picks a model based on your query. There is no option to tell it to go try all the models and aggregate them.

And none of that eliminates hallucinations even if it could do that. Either way what you just described is incredibly expensive lol

Source: I've used GitHub Copilot and I have taken 2 different trainings that utilize it. Possible I missed something but I doubt it, I just used it on a project last Friday.