= 27d567bc2d48d9f40e9ccc20ea370b15)
Simon_Jester comments on Mathematical simplicity bias and exponential functions - Less Wrong
You are viewing a comment permalink. View the original post to see all comments and the full post content.
= 783df68a0f980790206b9ea87794c5b6)
Loading…= b715d02e85f7b3b4ae65ca3d3e450868)
Subscribe to RSS Feed
Powered by Reddit
= f037147d6e6c911a85753b9abdedda8d)
You are viewing a comment permalink. View the original post to see all comments and the full post content.
Comments (82)
I must disagree with premise that biology is not making progress while physics is. As far as I can tell biology is making progress many orders of magnitude larger and more practically significant than physics at the moment.
And it requires this messy complex paradigm of accumulating plenty of data and mining it for complicated regularities - even the closest things biology has to "physical laws" like the Central Dogma or how DNA sequences translate to protein sequences, each have enough exceptions and footnotes to fill a small book.
The world isn't simple. Simple models are usually very wrong. Exceptions to this pattern like basic physics are extremely unusual, and shouldn't be taken as a paradigm for all science.
The catch is that complex models are also usually very wrong. Most possible models of reality are wrong, because there are an infinite legion of models and only one reality. And if you try too hard to create a perfectly nuanced and detailed model, because you fear your bias in favor of simple mathematical models, there's a risk. You can fall prey to the opposing bias: the temptation to add an epicycle to your model instead of rethinking your premises. As one of the wiser teachers of one of my wiser teachers said, you can always come up with a function that fits 100 data points perfectly... if you use a 99th-order polynomial.
Naturally, this does not mean that the data are accurately described by a 99th-order polynomial, or that the polynomial has any predictive power worth giving a second glance. Tacking on more complexity and free parameters doesn't guarantee a good theory any more than abstracting them out does.