Comment by shevy-java
12 hours ago
> that predictive models are now producing faster than anyone can construct them.
Erm ... you have A T C G. You can have a gazillion of combinations there.
Of course BY DEFAULT it will always be slower than ANY combination you would desire to have - and you most definitely do not need AI slop to have that either. Do we need AI slop for generating any permutation of those 4 letters now? So what is the point of stating "can construct".
IF the synthesis method works, then that is the focus to be debated, not the AI slop is our master-thinker now.
> “We really want this to be an enabling platform,” says Robinson. “We want people to do cool things with the technology.”
And I think they patented this (if it really works), so ... enabling platform, right.
Interestingly the article omits many key questions to be asked here. If the method already works as-is, why isn't everyone using it? If it is cheaper and faster, then logically it would already be used or usable.
> > that predictive models are now producing faster than anyone can construct them.
> Erm ... you have A T C G. You can have a gazillion of combinations there.
> Of course BY DEFAULT it will always be slower than ANY combination you would desire to have - and you most definitely do not need AI slop to have that either. Do we need AI slop for generating any permutation of those 4 letters now? So what is the point of stating "can construct".
The bit right before your quote says why:
Also, predictive models is broader than Transformers, but even then Transformers in the context of DNA is somewhat different from the context of natural (or even programming) languages; and even more than that, given how effective even mediocre early models were for code not useful to dismiss all of it even when it is definitely "slop" in other domains: https://www.nature.com/articles/s41592-024-02523-z