Using AI to design proteins is now easy. Making enzymes remains hard.

Enzyme mechanisms can be complex, and getting them to work is tricky.

See full article...

 

[sigmasirrus]

So... whatever is wrong with using fungus? Too slow?

https://www.sciencealert.com/scient...can-break-down-tough-plastic-in-just-140-days

According to that article:

“More than 400 microorganisms have so far been found to degrade plastic naturally, with fungi attracting a fair bit of attention for their versatility and ability to degrade all sorts of synthetic substrates with a powerful concoction of enzymes.”

Yet in the Ars article:

“Unfortunately, there isn't an enzyme for many reactions we would sorely like to catalyze—things like digesting plastics.”

So which is it?

 

[sigmasirrus]

A few years ago this article would have used ML instead of AI, and in my mind ML would still be a better fit. I'm not quite sure how forcing the AI to learn to go back a workable state is "generative AI" of the sort I normally think of as "Generative AI". Sure, this generates results, but so did any original ML algorithm. Random trees generate outputs, so is it a generative AI? The use of AI rather than ML, and especially generative AI, feels like more buzzword use rather than accurate description (but that's without reading the original paper).

I just think that machine learning is a better, less loaded term.