The non-professional side of Organic Chemistry is one place where I think AI would really shine.
Feels complex like solving a Rubik's cube to write down synthesis steps but it is all a sequence of memorized tricks. Do Cannizaro if you want this, Bergmann to do that.
But the synthesis plan is only 10% of the actual work.
The gap between writing down the synthesis step and actually doing it is also extremely large.
Even if you get the right molecule, it might be the wrong way around or just clump up into a useless mess.
The Ritonavir episode of Veritasium is a great example of how all chemistry on paper is a mere shadow of what actually happens in real life.
> Feels complex like solving a Rubik's cube to write down synthesis steps but it is all a sequence of memorized tricks. Do Cannizaro if you want this, Bergmann to do that.
I remember two years ago, when I actually got into using graph data structures, wondering if maybe the "space" of available reactions for any given starter and target molecules could be mapped as a graph, with intermediates as nodes and reactions as weighted directed edges, so synthesis becomes pathfinding through chemical space.
Turns out, it’s a thing! [^0]
Edit: Makes you wonder how much interesting stuff is sitting in plain sight, waiting for someone with the right cross-domain awareness / knowledge / whatever to notice it.
There is a lot of graph theory in Chemistry - modelling chemicals as (vertex/edge coloured) graphs, reaction networks, etc.
Of course some molecules (eg aromatic systems, like ferrocene) are not naturally representable as graphs. I wonder if it is the same with synthesis - are there reactions hard to model as a graph (or petri net or whatever). One simple example I know is that you have to be careful with including a node for 'water' as it gets connected to everything else! Or at least in biochemistry it does.
Modern biochemistry (so far) IS vibe coding lol. You mostly have vibes on how the chemistry should work, based on (very strong) natural evidence coupled with theoretical development and lab studies. Then you mix and match, goading bacteria and praying that they produce what you want in good measure. Then you take their secretions and run chromatography studies on them to check if that's what you actually want, or whether it's just some random bullshit. If it's the latter, you have to toss that out and start all over again.
Organic chemistry seems like a discipline better done by chemists than forward deployed staff with their payoff function sharply truncated at an IPO which at this point may or may not happen on schedule.
If they succeed here, won't they have to gate access to this feature, too? For the same reasons as, "if I so much as mention mitochondria, it downgrades me to Opus."
Step 1. Make it so Claude can do anything — the whole point of AGI
Step 2. Wait, if the user can do Anything, that would be Very Bad!
Step 3. Err on the safe side with blanket bans of entire fields
The latter actually seems to me a sensible reaction to e.g. the compartmentalization used in the large scale cyber attack using Claude last year. Where they were able to do Bad Thing by dividing it into many, many Small, Seemingly Harmless Things.
Gated access sounds bad (and I agree it sounds bad!) but it might actually be the only sensible response to such a set of conditions. I'm not sure though.
--
I saw some studies recently which showed LLMs provide much more detailed information to expert users. So we can distinguish between competence and incompetence based on use of language, and that is a reasonable metric for harm reduction.
But I don't think we can reliably detect "user has harmful intentions", at least not at a sufficient level of sophistication of the attacker.
I think one time I asked opus about copyfail when it just came out and it did treat me like some sort of criminal, but are there really people that run into this on a regular basis other than cybersecurity experts (which cannot be a big enough group to generate all of this criticism)?
Combine it with automated lab like this[1][2][3][4][5] (and many others) and it will iterate much quicker. Some already do but at a smaller scale, AFAIK.
I feel like chemistry is one thing that current models will struggle with for the next while, because it's inherently 3D. In the micro world, shape = function. Maybe enough textual patterns will let it under chemistry, but like how do you describe a hydrogen shift without showing how it moves positions and rebalances bonds?
I think this is a very interesting concept/question. I feel like programming is more about shapes than anything else… but they seem to have mastered that fairly easily… but I totally get your point!
Feels complex like solving a Rubik's cube to write down synthesis steps but it is all a sequence of memorized tricks. Do Cannizaro if you want this, Bergmann to do that.
But the synthesis plan is only 10% of the actual work.
The gap between writing down the synthesis step and actually doing it is also extremely large.
Even if you get the right molecule, it might be the wrong way around or just clump up into a useless mess.
The Ritonavir episode of Veritasium is a great example of how all chemistry on paper is a mere shadow of what actually happens in real life.
I remember two years ago, when I actually got into using graph data structures, wondering if maybe the "space" of available reactions for any given starter and target molecules could be mapped as a graph, with intermediates as nodes and reactions as weighted directed edges, so synthesis becomes pathfinding through chemical space.
Turns out, it’s a thing! [^0]
Edit: Makes you wonder how much interesting stuff is sitting in plain sight, waiting for someone with the right cross-domain awareness / knowledge / whatever to notice it.
[0]: https://pmc.ncbi.nlm.nih.gov/articles/PMC9574932/
Of course some molecules (eg aromatic systems, like ferrocene) are not naturally representable as graphs. I wonder if it is the same with synthesis - are there reactions hard to model as a graph (or petri net or whatever). One simple example I know is that you have to be careful with including a node for 'water' as it gets connected to everything else! Or at least in biochemistry it does.
Sounds a lot like vibe coding lol
The world today is coding.
Step 1. Make it so Claude can do anything — the whole point of AGI
Step 2. Wait, if the user can do Anything, that would be Very Bad!
Step 3. Err on the safe side with blanket bans of entire fields
The latter actually seems to me a sensible reaction to e.g. the compartmentalization used in the large scale cyber attack using Claude last year. Where they were able to do Bad Thing by dividing it into many, many Small, Seemingly Harmless Things.
Gated access sounds bad (and I agree it sounds bad!) but it might actually be the only sensible response to such a set of conditions. I'm not sure though.
--
I saw some studies recently which showed LLMs provide much more detailed information to expert users. So we can distinguish between competence and incompetence based on use of language, and that is a reasonable metric for harm reduction.
But I don't think we can reliably detect "user has harmful intentions", at least not at a sufficient level of sophistication of the attacker.
They are following closely and the best offer 80-90% of the performance and come with a very small fraction of the costs.
Deepseek.v4.Pro.RePacked.LLMBoyz.part1.zstd
[1] https://www.ginkgo.bio/autonomous-lab
[2] https://www.emeraldcloudlab.com/
[3] https://www.kebotix.com/
[4] https://www.chemify.io/
[5] https://arxiv.org/abs/2507.01485
You can use those and they probably won't intentionally sabotage you.