Slashdot Mirror
AI Tool, Which Has Digested Nearly Every Reaction Ever Performed, Can Invent New Ways To Create Complex Molecules (nature.com)
An anonymous reader shares a research paper: Researchers have developed a 'deep learning' computer program that produces blueprints for the sequences of reactions needed to create small organic molecules, such as drug compounds. The pathways that the tool suggests look just as good on paper as those devised by human chemists. The tool is not the first software to wield AI instead of human skill and intuition. Yet chemists hail the development as a milestone, saying that it could speed up the process of drug discovery and make organic chemistry more efficient. "What we have seen here is that this kind of artificial intelligence can capture this expert knowledge," says Pablo Carbonell, who designs synthesis-predicting tools at the University of Manchester, UK, and was not involved in the work. He describes the effort as "a landmark paper."
[...] Chemists have conventionally scoured lists of reactions recorded by others, and drawn on their own intuition to work out a step-by-step pathway to make a particular compound. They usually work backwards, starting with the molecule they want to create and then analysing which readily available reagents and sequences of reactions could be used to synthesize it -- a process known as retrosynthesis, which can take hours or even days of planning. The new AI tool, developed by Marwin Segler, an organic chemist and artificial-intelligence researcher at the University of Munster in Germany, and his colleagues, uses deep-learning neural networks to imbibe essentially all known single-step organic-chemistry reactions -- about 12.4 million of them. This enables it to predict the chemical reactions that can be used in any single step. The tool repeatedly applies these neural networks in planning a multi-step synthesis, deconstructing the desired molecule until it ends up with the available starting reagents.
[...] Chemists have conventionally scoured lists of reactions recorded by others, and drawn on their own intuition to work out a step-by-step pathway to make a particular compound. They usually work backwards, starting with the molecule they want to create and then analysing which readily available reagents and sequences of reactions could be used to synthesize it -- a process known as retrosynthesis, which can take hours or even days of planning. The new AI tool, developed by Marwin Segler, an organic chemist and artificial-intelligence researcher at the University of Munster in Germany, and his colleagues, uses deep-learning neural networks to imbibe essentially all known single-step organic-chemistry reactions -- about 12.4 million of them. This enables it to predict the chemical reactions that can be used in any single step. The tool repeatedly applies these neural networks in planning a multi-step synthesis, deconstructing the desired molecule until it ends up with the available starting reagents.
I'm waiting for Slashdot to implement AI. To prevent duplicate posts like these.
https://science.slashdot.org/story/18/03/28/232206/new-deep-learning-software-knows-how-to-make-desired-organic-molecules
This could revolutionize the recreational pharmaceutical industry. Drug dealers could be a thing of the past. We can 3-D print our own opioids.
How about an AI tool that has digested every Slashdot article posted less than 48 hours ago so it doesn't get posted again? We can name it "Ed".
Hmm,, seems very familiar to me.
shrug
What if someone uses this to create on-the-fly recipes for nerve agents that can be made from common chemicals, like how the Soviets did with their Novichok program binary agents?
His name is Maynard
But... why does it keep calling itself "Skynet"?
I've abandoned my search for truth; now I'm just looking for some useful delusions.
If only we had the ability to come up with an AI that would identify duplicate slashdot stories....
"If it ain't broke, it doesn't have enough features yet"
How is this AI? Wouldn't this just be a while/for loop seeing how it's just repeatedly looking at all KNOWN single-step organic-chemistry reactions until there's none left?
Here is the article which the Nature summary linked in the ./ summary summarizes.
The Nature summary links to that article and states "The new AI tool, developed by Marwin Segler, an organic chemist and artificial-intelligence researcher at the University of Münster in Germany..." Weirdly, Segler is not listed as an author on the article and none of the article's authors are at Münster. Even stranger, Segler is not even cited.
Ceci n'est pas une signature.
What it's doing is a deep learning version of what can be done by a pruning branch analysis by working the reactions in reverse. The sections of indecision in reactions are replaced by the AI decision formed from data dumps as opposed to some programmed heuristic.
It's not a huge leap in AI or VI or whatever someone wants to call it these days, but it's a good application of 'deep learning'.
I don't read AC
Let me know when it gets incorporated into the crafting system of a next-gen VR MMORPG.
Queue up the guy that will say it isn't AI because it isn't Lt Cmdr Data! Anyhow, this sort of modeling sounds like it could be pretty useful.
Lets make this work for everyone.. Open source it.
ObXKCD
"Believe me!" -- Donald Trump
Great. Now we can really fix things.
The Russians have won. They have made the world a cesspool of distrust, greed, fear and hate.
And I'm happy to be that guy.
Not AI.
Some new antibiotics would be nice, maybe some not just copying what nature already created?
PLEASE do this with Diesels. This Tier 4 stuff is an incredible burden. The improvements from Tier 3 are minimal given the amount of headache involved.
Black Box, slap the 'AI' label on it, and ship, ship, ship! No worries, people are dumb, they'll never know the difference..
Perhaps this could be used to discover new Hypothetical types of biochemistry and we can then speculate about many more types of alternative biochemistries ("life as we don't know it").
Artificial Intelligence vs Natural Intelligence: the former is trying to match the latter.
When there are thousands of variants of AI's algorithms for a determined task, any of them could be useful.
Anybody up for Nano Tube production?