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Lamini Memory Tuning: 10x Fewer Hallucinations

lamini.ai

21–30 of 63 posts

Re: Lamini Memory Tuning: 10x Fewer Hallucinations

#21
post #18

Doesn't this make the "AI" even less creative and more like full-text-search instead? What makes some data a "fact"? If everything is written in the training data, in the end, won't everything be treated like a fact? So the LLM will have 100% accuracy and 0% creativity.

Sounds like compression to me

Re: Lamini Memory Tuning: 10x Fewer Hallucinations

#22
post #18

Doesn't this make the "AI" even less creative and more like full-text-search instead? What makes some data a "fact"? If everything is written in the training data, in the end, won't everything be treated like a fact? So the LLM will have 100% accuracy and 0% creativity.

Creativity is clearly not the goal here. Machine learning models are trained to be robust to errors in the training data.

Re: Lamini Memory Tuning: 10x Fewer Hallucinations

#23
post #21
post #18

Doesn't this make the "AI" even less creative and more like full-text-search instead? What makes some data a "fact"? If everything is written in the training data, in the end, won't everything be treated like a fact? So the LLM will have 100% accuracy and 0% creativity.

Sounds like compression to me

"Compressing" 500MB of data into a 70GB model.

Re: Lamini Memory Tuning: 10x Fewer Hallucinations

#24

Am I the only one that cringes at "10x fewer?" How do I multiply positive numbers and get something smaller? Is "1/10th" or "90% less" not better arithmetic? Maybe I should have done more gooder at math but it hurts my ears (eyes).

They are overloading "fewer" to mean division as well as subtraction. According to this logic "twice fewer" means "half as much".

Re: Lamini Memory Tuning: 10x Fewer Hallucinations

#25

Am I the only one that cringes at "10x fewer?" How do I multiply positive numbers and get something smaller? Is "1/10th" or "90% less" not better arithmetic? Maybe I should have done more gooder at math but it hurts my ears (eyes).

> How do I multiply positive numbers and get something smaller?

fractions are gonna blow your mind

Re: Lamini Memory Tuning: 10x Fewer Hallucinations

#26

Am I the only one that cringes at "10x fewer?" How do I multiply positive numbers and get something smaller? Is "1/10th" or "90% less" not better arithmetic? Maybe I should have done more gooder at math but it hurts my ears (eyes).

Bigger number better, obviously!

I am also annoyed by most modern tech marketing using percentages incorrectly and inconsistently. But 150% is a bigger number than 1.5x so I suppose their hands are tied.

Re: Lamini Memory Tuning: 10x Fewer Hallucinations

#28

Am I the only one that cringes at "10x fewer?" How do I multiply positive numbers and get something smaller? Is "1/10th" or "90% less" not better arithmetic? Maybe I should have done more gooder at math but it hurts my ears (eyes).

I think it depends how you think of the initial number, I think of it as a fraction and the multiplier applies to the denominator.

eg. if hallucinations occur roughly 1 in 20 prompts then 10x fewer is 1 in 200 prompts, rather than 0.1 in 20 prompts.

Re: Lamini Memory Tuning: 10x Fewer Hallucinations

#29
post #18

Doesn't this make the "AI" even less creative and more like full-text-search instead? What makes some data a "fact"? If everything is written in the training data, in the end, won't everything be treated like a fact? So the LLM will have 100% accuracy and 0% creativity.

"Ten times less" is a common English usage with a clear meaning.

Re: Lamini Memory Tuning: 10x Fewer Hallucinations

#30
post #6

"Hallucinations" are the creative aspect of LLMs, which is what they are more useful for- if anything we want more of them. We already have much simpler systems that search and regurgitate facts. We need more intelligent hallucinations that are consistent with and extend rather than conflict with the data.

Is it even possible to measure and distinguish the output as being hallucinated or not? All LLM output is hallucinated, it's only by statistics or chance that some of the output reflects facts, and we're only able to make that assessment because we can compare the output to facts. The model can't make that assessment itself.

Going from 50% "accurate" to 90% "accurate" may actually be more insidious because it changes the utility from being a coin flip to trying to determine which 10% is inaccurate, or downplaying the existence of inaccuracies because at 90% it is "mostly correct".

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