The problem with models like this is they're built on very little actual training data we can trace back to verifiable protein data. The protein data back, and other sources of training data for stuff like this, has a lot of broken structures in them and "creative liberties" taken to infer a structure from instrument data. It's a very complex process that leaves a lot for interpretation.
On top of that, we don't have a clear understanding on how certain positions (conformations) of a structure affect underlying biological mechanisms.
Yes, these models can predict surprisingly accurate structures and sequences. Do we know if these outputs are biologically useful? Not quite.
This technology is amazing, don't get me wrong, but to the average person they might see this and wonder why we can't go full futurism and solve every pathology with models like these.
We've come a long way, but there's still a very very long way to go.
rubicon33 3 hours ago [-]
Can someone explain what one might use this model for? As a developer with a casual interest in biology it would be fun to play with but honestly not sure what I would do
colechristensen 3 hours ago [-]
You can get your feet wet with genetic engineering for surprisingly little money.
What makes this dataset or problem worth solving compared to other health datasets? Would the results on this task be broadly useful to health?
CyberDildonics 3 hours ago [-]
What other "datasets" are you talking about? How do you "solve a dataset" ?
1 hours ago [-]
khalic 4 hours ago [-]
> In Progress: CodonJEPA
JEPA is going to break the whole industry :D
digdugdirk 4 hours ago [-]
Can you explain this? I haven't heard of JEPA, and from a quick search it seems to be vision/robotics based?
khalic 3 hours ago [-]
It’s a self supervised learning architecture, and it’s pretty much universal. The loss function runs on embeddings, and some other smart architectural choices allover. Worth diving into for a few hours, Yann LeCun gives some interesting talks about it
On top of that, we don't have a clear understanding on how certain positions (conformations) of a structure affect underlying biological mechanisms.
Yes, these models can predict surprisingly accurate structures and sequences. Do we know if these outputs are biologically useful? Not quite.
This technology is amazing, don't get me wrong, but to the average person they might see this and wonder why we can't go full futurism and solve every pathology with models like these.
We've come a long way, but there's still a very very long way to go.
This guy shows a lot of how it's done: https://www.youtube.com/@thethoughtemporium
Basically you can design/edit/inject custom genes into things and see real results spending on the scale of $100-$1000.
JEPA is going to break the whole industry :D
Who says we don't?