Why don't machine learning research agents overfit?

52 points - today at 4:32 PM

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diddid today at 5:51 PM
I always get annoyed when people misinterpret Occam’s razor. It’s not that the simplest is more likely to be correct, it’s that you should prefer it, because it’s simple.

It’s just like the Hopper quote. She said it’s better to ask for forgiveness during the fog of war, doing something you thought was right, not to do something you knew they were going to say no to and now you are trying to get away with something.

signalbright today at 6:36 PM
> Why don't machine learning research agents overfit?

they do.

demibabs today at 5:19 PM
Even tech giants are putting out articles seemingly fully written by Claude.
vatsachak today at 6:34 PM
No point in reading anything AI related anymore. It's all slop.

We need to retvrn to rss feeds

nyeah today at 5:51 PM
They tend not to overfit ... when there are way more data points than parameters.
dguest today at 5:39 PM
32df179 today at 5:55 PM
Wherein Claude gives an honest assessment that it genuinely does not overfit. I also had Grok telling me that it isn't quantized.

Do the submitters really not notice that this is AI slop? Do they like this? It is a complete pain to read.

novaapi today at 5:48 PM
[flagged]
dominotw today at 4:52 PM
> Machine learning, at its core, is about generalization, not memorization.

Well they memorize the patterns.

memorization doesnt mean rote learning.