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New Deep-Learning Software Knows How To Make Desired Organic Molecules (nature.com)
dryriver shares a report from Nature about a neural network-based, deep-learning software that is as good as trained chemists in figuring out what reagents and reactions may lead to the successful creation of a desired organic molecule: Chemists have a new lab assistant: artificial intelligence. 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, described in Nature on March 28, is not the first software to wield artificial intelligence (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. 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 analyzing 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.
Next step is to miniaturize 3D printers to the point that I can print my own medications, food, and Star Trek DVDs...
Will it help make crystal meth? Asking for a friend.
"The deep-fried Mars bar is a symptom of a wider crisis." -- Nutritionist Ann Ralph, on the Scottish diet
home brewed custom illegal drugs...
then home brewed VX.
that were going to replace the manufacturing & tech jobs we outsourced? How's that working out for ya?
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No doubt this is potentially a highly significant development, and an early example of a powerful tool that shows the way to the future. I expect that this sort of technology will prove useful in developing many desirable chemicals for many purposes. But, one of the things I wonder about is the potential for reduced understanding and insight among the people using it, and where it might lead. Mathematics is already confronted by machine generated results that are beyond the ability of humans to check. And I remember reading of results that seemed to be correct, but the method that they were arrived at was impenetrable. Trust the machine(s)? How far? Is this another area where AI might prove dangerous to humanity?
Computer generated math proof is too large for humans to check
Chess computers are now pretty much able to beat any human. Amazingly now computers playing Go seem to be heading in the same direction. Brute strength and clever algorithms combine to search possibilities far beyond what a human can. Someday will AI search out a subtle "final solution" for humanity that will take 10 generations to come to fruition? Checkmate?
How can we safeguard our future from subtle, malevolent AI?
much of left-wing thought is a kind of playing with fire by people who don't even know that fire is hot - George Orwell
This article is full of "putty" terms which makes me doubt that their results are as great as they seem to be selling. "Worked" in organic synthesis is a very imprecise term. In some reactions a 5% yield is great in others 95% is poor. Did the deep learning suggested pathways provide better or worse yields than standard practice?
... I imagine, without knowing much about biotech (or RTFA). The bottleneck is the trial and experimentation, which takes a long time. You already have to be very discerning in deciding which synthesized compounds you want to try, what good does it do to you to be able to computer-generate more compounds?
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How can they patent or copyright the output of this when algorithmically generated content is supposed to be un-copyright/patentable as a result of limited human intervention and innovation?
Anyone remember a decade or two ago when that was used to claim algorithmically generated music couldn't be copyrighted unless it was primarily created by a human?
This is just further widening the divide between the haves and the have nots.
to determine whether to sing "It's life, Jim, but not as we know it, not as we know it, not as we know it."
It's a good idea, but is it safe? That the machine would deal with organic chemistry. Full control must take place in human observation
gardening
Seems you could go this with just searching a database of one-step reactions. When all you have is a hammer, etc..
This sounds like a problem involving scanning databases of known reactions, and doing detailed modeling. There might be an artificial neural network in there somewhere but I doubt it is the key.
It reflects the sad state of science journalism that anything vaguely intelligent becomes "Deep Learning", or whatever the current buzz phrase is.
Will it help make Gray Goo?
Part of the problem with relying on data from past reactions as found in the chemical literature is that failed reactions do not show up. When I design a synthetic pathway, I know not to try to use reagent A in solvent B. But there is no paper published containing that fact, because we don't write papers about what didn't work.
Can it create life? Wonderful stuff, this singularity.
I recently went through all of Derek Lowe's "Things I Won't Work With" columns (highly recommended for anyone with a sense of humor and an instinct for self-preservation), and in the aftermath spent some time reading some of his other articles. One in particular discusses the possibility of an automated chemist, performing reactions given a recipe. Today's article discusses this latest paper, which focuses on generating those recipes, and compares it to another AI approach previously covered.
Notably, Lowe focuses on the impact such developments will have on the field of chemistry, and compares it to the impact of the Deep Blue vs. Kasparov chess matches. In short, yes, the boring labor-intensive analytical jobs will be handed off to machines, and humans will take on the management role of deciding what new compounds society will need.
You do not have a moral or legal right to do absolutely anything you want.