MrThink

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In some cases I agree, for example it doesn't matter if GPT4 is a stochastic parrot or capable of deeper reasoning as long as it is useful to whatever need we have.

Two out of the five metrics are predicting the future, so it is an important part of knowing who is right, but I don't think that is all we need? If we have other factors that also correlates with being correct, why not add those in?

Also, I don't see where we risk Goodharting? Which of the metrics do you see being gamed, without a significantly increased chance of being correct also being increase?

True, would be interesting to conduct an actual study and see which metrics are more useful predictors.

MrThink10

I think it in large part was correlated with general risk apetite of the market, primarily a reaction to interest rates.

MrThink10

Nvidia is up 250%, Google up like 11%. So portfolio average would be greatly better than the market. So this was a great prediction after all, just needed some time.

MrThink71

I agree it is not clear if it is net postive or negative that they open source the models, here are the main arguments for and against I could think of:


Pros with open sourcing models

- Gives AI alignment researchers access to smarter models to experiment on

- Decreases income for leading AI labs such as OpenAI and Google, since people can use open source models instead.



Cons with open sourcing models

- Capability researchers can do better experiements on how to improve capabilities

-  The open source community could develop code to faster train and run inference on models, indirectly enhancing capability development.

- Better open source models could lead to more AI startups succeeding, which might lead to more AI research funding. This seems like a stretch to me.

- If Meta would share any meaningful improvements on how to train models that is of course directly contributing to other labs capabilities, but llama to me doesn't seem that innovative. I'm happy to be corrected if I am wrong on this point.

MrThink40

I think one reason for the low number of upvotes was that it was not clear to me until the second time I briefly checked this article why it mattered.

I did not know what DoD was short for (U.S. Department of Defense), and why I should care about what they were funding.

Cause overall I do think it is interesting information.

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