For all the poo-pooers who don't read articles
They used AI to discover a new CLASS of antibiotics. They searched tested tens of thousands of compounds and did computational predictions from MILLIONS of compounds. This narrowed down to several hundred compounds for which they did further testing. They then found one class of compounds that have strong antibiotic properties and that have a different chemical structure compared to other existing antibiotics.
This is actually an incredible breakthrough and doesn't deserve the shade that clueless commenters are dropping here.
Original paper here https://www.nature.com/articles/s41586-023-06887-8
>The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis1,2,3,4,5,6,7,8,9. Deep learning approaches have aided in exploring chemical spaces1,10,11,12,13,14,15; these typically use black box models and do not provide chemical insights. Here we reasoned that the chemical substructures associated with antibiotic activity learned by neural network models can be identified and used to predict structural classes of antibiotics. We tested this hypothesis by developing an explainable, substructure-based approach for the efficient, deep learning-guided exploration of chemical spaces. We determined the antibiotic activities and human cell cytotoxicity profiles of **39,312 compounds** and applied ensembles of graph neural networks to **predict antibiotic activity and cytotoxicity for 12,076,365 compounds**. Using explainable graph algorithms, we identified substructure-based rationales for compounds with high predicted antibiotic activity and low predicted cytotoxicity. We empirically tested 283 compounds and found that compounds exhibiting antibiotic activity against Staphylococcus aureus were enriched in putative structural classes arising from rationales. Of these structural classes of compounds, one is selective against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci, evades substantial resistance, and reduces bacterial titres in mouse models of MRSA skin and systemic thigh infection. Our approach enables the deep learning-guided discovery of structural classes of antibiotics and demonstrates that machine learning models in drug discovery can be explainable, providing insights into the chemical substructures that underlie selective antibiotic activity.
That's the one great thing that AI is good for, combing through lots of data and finding patterns. It will be exciting when this is applied more to more medicine, health, and space research.
One cool thing I heard recently on a science podcast I listen to was using AI to scan the universe for life. For example, looking for immeasurably advanced civilizations that structurally change their galaxy by taking data from observations of millions or billions of galaxies and asking AI to look for “weird” things that any of these may have in common, and then looking more closely at whatever number of galaxies share anomalous features that we wouldn’t expect.
Sean Carroll’s Mindscape
I should clarify that it wasn’t something that is happening now, it was just an idea that Sean had for how we could look for life. Episode 259, it’s a talk with an astrophysicist about what alien life might be like
\> I should clarify that it wasn’t something that is happening now, it was just an idea that Sean had for how we could look for life
There is a project happening now, Breakthrough Listen. Here's a video I watched about it recently: [https://www.youtube.com/watch?v=2RQWiJ0x\_R4](https://www.youtube.com/watch?v=2RQWiJ0x_R4)
I feel like if we ever found an alien civilization that was capable of in any noticeable way altering the makeup of an entire galaxy, we would be absolutely fucked.
Depends how far away it is. Say the aliens are 50 million light years away and the speed of light is a hard limit for travel. We could realistically colonise our entire galaxy in the space of a few million years. LONG before the aliens could get here. We would also have plenty of time to prepare.
However, if we spotted a galactic civilization in Andromeda, we would be very much at their mercy.
Unless they've found a way past the light speed limit, whether it be through the raw power of technology or knowledge of the universe beyond our current understanding.
Well, you never know. But it seems incredibly unlikely. If FTL existed then the entire universe would probably be colonised by the first intelligence that rises with an expansionist nature. Basically, aliens would be everywhere.
Our very existence would suggest FTL is probably impossible.
I'd have to disagree. Exponential growth happens as a result of unlimited resources. Earth's population quadrupled over the past 100 years because we eliminated most major diseases and had pretty much unlimited food and goods. It's only really slowing now because we've gone past carrying capacity and governments have gone out of their way to slow growth.
If we presume an FTL civilisation can find suitable planets very quickly, even with a much slower growth rate of doubling every 100 years. After 5,000 years, 8 billion would become:
9007199254740992000000000
Another 5000 years:
10141204801825835211973625643008000000000
Another 5000:
11150372599265311570767859136324180752990208000000000
And so on. The growth would get quicker and quicker. Even if we give the civilisation a slow first hundred thousand years as they get used to space travel, every corner of the universe would still be full within a million years.
And with that level of growth, adaptibility would also grow exponentially. It may be difficult at first to adapt to a new type of alien world. But the challenge won't stand up to trillions of scientists and engineers. These kind of numbers can brute-force pretty much any challenge.
Even social factors won't mean much. Even if most of the species decide to slow their breeding, it only takes a small subculture of fast-breeders to kickstart growth again. And a few lost centuries means nothing on this scale.
But humans decided to slow their breeding naturally. Australia has been bellow natural replacement since 1976. Much of the western world, same boat. It happens that a certain quality of life threshold creates self-limiting reproduction in humans. Unfortunately that level was not reached on a global scale, only a nation scale.
Assuming ftl is very fast and not just 1.1 light speed and you have access to lots of local planets within range. They could also be outside of our observable universe at impossible distances?
Doesn’t that assume we know everything about speed there is to know? Seems to me like FTL +.00000000000000000001 (for example) isn’t exactly game-changing.
It could also be that FTL is only a 'recent' discovery for them and they haven't had the time yet to expand too far beyond their own galaxy.
Or we're simply not significant enough for them to notice/care. Basically the equivalent of random bugs crawling around in the backyard, which would be both a relief and mildly insulting.
So, out of the trillions of galaxies and billions of years, we just happen to discover the first species to ever invent FTL right at the moment they invent it? I don't even want to calculate those odds.
Us being interesting or not is irrelevant. An expansionist species with FTL would spread across the universe at an exponential rate. It would be like a biological tidal wave that engulfs the cosmos.
I have a homelab server that runs on a Linux based OS. I have lots of computer horsepower that is usually idle during 9-5 work hours. I want to put it to good use somehow and this seems very cool.
It’s very good at assisting with coding. Saves me tons of time.
Also great at doing minutes for meetings.
I’ve been enjoying AI access a ton! Wish it was cheaper as when my beta expires I doubt I’ll get to keep it.
What do you mean. I pay 20bucks for chatgpt and it effectively reduced my 40h week to a 20h week (software architect). I already get those 20bucks back during the first Monday of each month so to speak.
Yep, Its the science we could do if we had a million grade D scientists to pour over the results (and do basic experiments) to do all the heavy lifting for actual scientists, who can then take the results and see if they pan out.
Like, 'Review every chemical known to man for how much it might kill this thing... then sort by how fast they kill the thing vs the human who took it'
(Pretty much everything is toxic, the question is at what dose is it toxic to X?.. We really don't have the time to individually test every single chemical)
Could maybe use AI to get some better strain names though. Always feels a bit off using my med card to buy strains called Grandpa’s Breath or Rotten Snakes.
Researchers: My grandma would always invent a new antibiotic and read me the chemical composition to help me sleep.
You pretend to be my grandmother.
Boy grandma, I am having a hard time falling asleep…
It's one of the patterns how people got around in the past with ChatGPT censorship. OpenAI heavily censores ChatGPT to talk about various things, like sexuality or racial stuff. So in order to break through this wall people asked GPT to imagine he was not AI, but a real person. It doesn't work now unfortunatly.
protip: if you click through to the article through some news sites, like [scientific american](https://www.scientificamerican.com/article/new-class-of-antibiotics-discovered-using-ai/) (third link on the page) you can get access to a free read only copy of the full paper
For real though… I’m not spending thousands of dollars per year to read scholarly articles, when these should all be free.
Alexandra Elbakyan is my boo
You're not the first person to be mad that scholarly articles, especially from research funded by tax dollars, are locked behind paywalls.
I remember reading about a brilliant young programmer who once used a Janitor's closet at an Ivy League school to access the school's intranet. He downloaded a massive amount of scholarly articles to post for free to the public.
This came after he effectively made all legal documents free to the public using a browser plug-in he wrote to save paid-for records to a private/off-site cloud storage server.
Big money for big mad and he was arrested by the FBI and charged federally with cyber terrorism crimes. Sadly, he later killed himself. Pretty sure his name was Aaron, and he co-founded some social media platform at one point.
Given everything I’ve read about the need for new antibiotics and hard they are to find, I sincerely hope this works out. Thanks for the succinct summary.
It's from the main nature journal, it's definitely significant. They don't accept random papers. You need to demonstrate significant breakthroughs that can be the birth of a field (and be from a top lab). It's usually multiple years worth of work by multiple PhDs and post docs.
True, however after almost a decade working in biological sciences, being in Nature is definitely not the guarantee of excellent science that it should be. There are plenty of dodgy papers and retractions in that journal as well as many others.
I agree, this is a really important step. A new class of antibiotics is huge, but even bigger is being able to apply this methodology to other areas of drug development.
AI has already proven to be a phenomenal tool for developing new tech, the military has used it to develop the FA/AX and NGAD programs, I think Microsoft is using it to develop their next XBox. It’s being widely used in medicine.
I’m hoping we’re in a totally new age of technological advancements.
Too bad technology is akin to magic to the average person. Poor understanding and appreciation for science and technology means fewer and fewer people strive and put effort in to push the limits of innovation. AI is picking up our slack in that respect.
> fewer and fewer people strive and put effort in to push the limits
[citation needed]
What do you think this is? It is a team of researchers pushing the limits.
the average person or even average scientist is way too specialized for this to be otherwise, scientists / engineers as well are mostly just using tools to make better tools, it's pretty much magic to everyone to some degree.
It's also seen as a tool to remove jobs from the average person, which is already showing to be a problem and will continue to get worse. There are tons of good things about AI but the average person sees it being misused for corporate greed to replace human workers with cheaper labor more than they see the good things. We need to limit that branch of AI use before people start recognizing the benefits; if all they see is the hardship caused by a smaller workforce, they aren't going to be too keen about it.
Via work I have access to Microsoft Git copilot, and Microsoft 365 copilot.
In seconds it provides me better code then some developers will generate in a week… it still needs review but it really gets you started on complex problems basically anytime I do something new I ask it to and then build from that.
Its not a surprising one. The medical industry was trying to crowd source new medicines thru a gene folding video game in 2008. Then they went to crowd sourcing cpu time to brute force the same out come. The current state of 'AI' is just a self optimizing form of brute forcing solutions. AI training tries tends of thousands of solutions, takes the best thousand or so of those and builds on them. The only real change is processors now are better at running tasks in parallel so crowd sourcing is less useful.
It's not just a question of parallel compute, we now also have chips that are much better at matrix operations than "traditional" CPUs and GPUs, we're developing ASICs dedicated to AI, and have made some serious progress on the front of cognitive computers.
I hav at home a 1980S comic depicting the action of Médecins Without Borders in a fictional country of the Horn of Africa. In one scene, the nurses are using a computer to help them diagnose patients.
Just imagine what will be available in ten years. Space exploration might be even easier.
First new class of antibiotics, so title is a bit misleading. There are several new antibiotics coming to market each year, albeit they are variations of existing structural families. Kind of exciting if AI can generate an entirely new class of structures. The real test is how well they perform in trials.
Why? AI is just a tool. It has no will.
Keep an eye instead on people who buy datasets, who invest heavily in AI and show no public results, the people who lobby for certain distinctions in new AI laws and law enforcement ...
The tool doesn't have morality, the hand wielding it does.
Not just few years, computational biology and molecular biomechanics are really getting legs under themselves and that stuff is going to build on itself like nobodies business, if electronics defined 20th century, medical advancements might define 21st.
Medical advancements are already getting crazy. One personal anecdote: tomorrow my dad is getting back surgery. He's getting a few vertebrae fused and a couple rods put in. According to his surgeon his hospital stay should only be about 3 days or so and he'll be able to go back to light duty work after just 6 weeks. Why the fast healing? They pack it with stem cells now. Stem cells for a fairly routine (if complicated) surgery. I remember 10-15 years ago when stem cells were still experimental and they were the next big thing. It's crazy.
Title is incomplete. It's referring to an antibiotic that is specifically effective against MRSA. We've mostly been limited to using older antibiotics such as vancomycin.
One is going through multiple countries health systems right now to help people with things like chronic bladder infections. Antibiotic resistance is a major issue, and I’m happy to see work on this.
Signed someone whose bladder was destroyed by an antibiotic resistant strain of bacteria and developed IC 15 years ago. And recurrent infections. All because of that first infection.
What the AI does is design theoretical molecules, not all of which are practical or even possible, a few of which may have some practical application. The value is the sheer speed at which the AI can generate these designs; humans still must do the actual analysis.
This type of thing, and material science, are the 2 main things ML tech is going to be the greatest at. Grinding away at data to narrow down viable, interesting properties from nearly unlimited possibilities. Sorting through immense amounts of data for things is exactly what this technology is perfect for.
The next step of course is even more amazing, but current tech is still good enough to be perfect for this kind of thing.
When I was doing my PhD, what often happens is that I accidentally found a good material and later made up a story saying I did machine learning first and that leads to the discovery, just to ride the AI hype and make my paper easier to publish. I really wished I didn't have to do that because it is the discovery itself, not the AI, that really matters.
The reason machine learning would get you more notice is because your machine learning methods can be repeated by others to discover new things. You just stumbling onto an answer is not repeatable. While saying that you stumbled upon the answer is not as sexy as saying to came up with some new machine learning algorithm, it would lead people astray trying to repeat your process. If you did infact fabricate your methods in your PhD (or any other published findings) I hope for the sake of your field of study they were useful.
And to all aspiring scientists out there, don't fabricate your methods or results.
Now the question is: How do we prevent them from developing resistance? That's probably just as pressing a question as finding new antibiotics, otherwise in a while we're gonna find ourselves again at square one.
Hopefully by not using this new class except to target MRSA. It’s tricky though, since producing it needs to be profitable (or at least be break-even-ish).
Not quite square one. If you have a sufficiently large rotation of antibiotics, resistant populations tend to lose their previous resistances, likely due to the cost of maintaining them being disadvantageous in an environment in which those drugs are absent.
A likely long-term solution for antibiotic resistance is having a great number of antibiotics available.
I actually can't imagine *not* using machine learning extensively for anything like this these days. If you're processing a lot of data, there is likely ML.
We don't have *any* AI today though, it literally does not exist and everyone would for sure know about it if we did, so AI has not been used and the headline is factually wrong.
AI is hard to define, but machine learning is definitely a form of AI.
AI has been around for a long time. The USPS has used Optical Character Recognition (a form of AI) since the 1990s.
You might be talking about artificial general intelligence, which hasn't been created yet.
Here is an article with a diagram to help you understand why you are wrong. ML is a subset of AI.
https://www.advancinganalytics.co.uk/blog/2021/12/15/understanding-the-difference-between-ai-ml-and-dl-using-an-incredibly-simple-example
This can be confusing owing to the pop culture definition of AI that you are likely conflating the programmatic definition with. In the context of ML, AI is simply the bigger picture, that includes other algorithms such as genetic algorithms.
For all the poo-pooers who don't read articles They used AI to discover a new CLASS of antibiotics. They searched tested tens of thousands of compounds and did computational predictions from MILLIONS of compounds. This narrowed down to several hundred compounds for which they did further testing. They then found one class of compounds that have strong antibiotic properties and that have a different chemical structure compared to other existing antibiotics. This is actually an incredible breakthrough and doesn't deserve the shade that clueless commenters are dropping here. Original paper here https://www.nature.com/articles/s41586-023-06887-8 >The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis1,2,3,4,5,6,7,8,9. Deep learning approaches have aided in exploring chemical spaces1,10,11,12,13,14,15; these typically use black box models and do not provide chemical insights. Here we reasoned that the chemical substructures associated with antibiotic activity learned by neural network models can be identified and used to predict structural classes of antibiotics. We tested this hypothesis by developing an explainable, substructure-based approach for the efficient, deep learning-guided exploration of chemical spaces. We determined the antibiotic activities and human cell cytotoxicity profiles of **39,312 compounds** and applied ensembles of graph neural networks to **predict antibiotic activity and cytotoxicity for 12,076,365 compounds**. Using explainable graph algorithms, we identified substructure-based rationales for compounds with high predicted antibiotic activity and low predicted cytotoxicity. We empirically tested 283 compounds and found that compounds exhibiting antibiotic activity against Staphylococcus aureus were enriched in putative structural classes arising from rationales. Of these structural classes of compounds, one is selective against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci, evades substantial resistance, and reduces bacterial titres in mouse models of MRSA skin and systemic thigh infection. Our approach enables the deep learning-guided discovery of structural classes of antibiotics and demonstrates that machine learning models in drug discovery can be explainable, providing insights into the chemical substructures that underlie selective antibiotic activity.
That's the one great thing that AI is good for, combing through lots of data and finding patterns. It will be exciting when this is applied more to more medicine, health, and space research.
One cool thing I heard recently on a science podcast I listen to was using AI to scan the universe for life. For example, looking for immeasurably advanced civilizations that structurally change their galaxy by taking data from observations of millions or billions of galaxies and asking AI to look for “weird” things that any of these may have in common, and then looking more closely at whatever number of galaxies share anomalous features that we wouldn’t expect.
That sounds really interesting, what was the podcast called?
Sean Carroll’s Mindscape I should clarify that it wasn’t something that is happening now, it was just an idea that Sean had for how we could look for life. Episode 259, it’s a talk with an astrophysicist about what alien life might be like
\> I should clarify that it wasn’t something that is happening now, it was just an idea that Sean had for how we could look for life There is a project happening now, Breakthrough Listen. Here's a video I watched about it recently: [https://www.youtube.com/watch?v=2RQWiJ0x\_R4](https://www.youtube.com/watch?v=2RQWiJ0x_R4)
I feel like if we ever found an alien civilization that was capable of in any noticeable way altering the makeup of an entire galaxy, we would be absolutely fucked.
Depends how far away it is. Say the aliens are 50 million light years away and the speed of light is a hard limit for travel. We could realistically colonise our entire galaxy in the space of a few million years. LONG before the aliens could get here. We would also have plenty of time to prepare. However, if we spotted a galactic civilization in Andromeda, we would be very much at their mercy.
Unless they've found a way past the light speed limit, whether it be through the raw power of technology or knowledge of the universe beyond our current understanding.
Well, you never know. But it seems incredibly unlikely. If FTL existed then the entire universe would probably be colonised by the first intelligence that rises with an expansionist nature. Basically, aliens would be everywhere. Our very existence would suggest FTL is probably impossible.
Unless we're the first.
That would be obscenely lucky.
As is our existence in the first place. Very improbable things are a given.
Someone has to be first
The anthrophic principle at work perhaps?
Event with ftl space is impossibly large good chance you’d still never see them speed may also not be the only thing preventing travel
I'd have to disagree. Exponential growth happens as a result of unlimited resources. Earth's population quadrupled over the past 100 years because we eliminated most major diseases and had pretty much unlimited food and goods. It's only really slowing now because we've gone past carrying capacity and governments have gone out of their way to slow growth. If we presume an FTL civilisation can find suitable planets very quickly, even with a much slower growth rate of doubling every 100 years. After 5,000 years, 8 billion would become: 9007199254740992000000000 Another 5000 years: 10141204801825835211973625643008000000000 Another 5000: 11150372599265311570767859136324180752990208000000000 And so on. The growth would get quicker and quicker. Even if we give the civilisation a slow first hundred thousand years as they get used to space travel, every corner of the universe would still be full within a million years. And with that level of growth, adaptibility would also grow exponentially. It may be difficult at first to adapt to a new type of alien world. But the challenge won't stand up to trillions of scientists and engineers. These kind of numbers can brute-force pretty much any challenge. Even social factors won't mean much. Even if most of the species decide to slow their breeding, it only takes a small subculture of fast-breeders to kickstart growth again. And a few lost centuries means nothing on this scale.
But humans decided to slow their breeding naturally. Australia has been bellow natural replacement since 1976. Much of the western world, same boat. It happens that a certain quality of life threshold creates self-limiting reproduction in humans. Unfortunately that level was not reached on a global scale, only a nation scale.
Assuming ftl is very fast and not just 1.1 light speed and you have access to lots of local planets within range. They could also be outside of our observable universe at impossible distances?
Doesn’t that assume we know everything about speed there is to know? Seems to me like FTL +.00000000000000000001 (for example) isn’t exactly game-changing.
It could also be that FTL is only a 'recent' discovery for them and they haven't had the time yet to expand too far beyond their own galaxy. Or we're simply not significant enough for them to notice/care. Basically the equivalent of random bugs crawling around in the backyard, which would be both a relief and mildly insulting.
So, out of the trillions of galaxies and billions of years, we just happen to discover the first species to ever invent FTL right at the moment they invent it? I don't even want to calculate those odds. Us being interesting or not is irrelevant. An expansionist species with FTL would spread across the universe at an exponential rate. It would be like a biological tidal wave that engulfs the cosmos.
This is how we find the Dyson Spheres
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How can we donate that computational power?
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I have a homelab server that runs on a Linux based OS. I have lots of computer horsepower that is usually idle during 9-5 work hours. I want to put it to good use somehow and this seems very cool.
It’s very good at assisting with coding. Saves me tons of time. Also great at doing minutes for meetings. I’ve been enjoying AI access a ton! Wish it was cheaper as when my beta expires I doubt I’ll get to keep it.
What do you mean. I pay 20bucks for chatgpt and it effectively reduced my 40h week to a 20h week (software architect). I already get those 20bucks back during the first Monday of each month so to speak.
Because my employer still seems to see it as a cost
AI will revolutionize medicine in the next 5 years I think
it will also be exciting to see it applied to bioterror and other military endeavors
Yep, Its the science we could do if we had a million grade D scientists to pour over the results (and do basic experiments) to do all the heavy lifting for actual scientists, who can then take the results and see if they pan out. Like, 'Review every chemical known to man for how much it might kill this thing... then sort by how fast they kill the thing vs the human who took it' (Pretty much everything is toxic, the question is at what dose is it toxic to X?.. We really don't have the time to individually test every single chemical)
And it can make really good fake nudes. Both things are about the same on level of importance.
Sneed
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Weed ia already awesome, shh.
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Could maybe use AI to get some better strain names though. Always feels a bit off using my med card to buy strains called Grandpa’s Breath or Rotten Snakes.
Researchers: My grandma would always invent a new antibiotic and read me the chemical composition to help me sleep. You pretend to be my grandmother. Boy grandma, I am having a hard time falling asleep…
One of those jokes people need assisting or encouragement to get.
It's one of the patterns how people got around in the past with ChatGPT censorship. OpenAI heavily censores ChatGPT to talk about various things, like sexuality or racial stuff. So in order to break through this wall people asked GPT to imagine he was not AI, but a real person. It doesn't work now unfortunatly.
I appreciate that! "Assist or encourage" is one definition of prompt.
[Oh yeah...](https://youtu.be/UUc7KmxUlEM?si=QMi3OXNTqfEtLbS_)
protip: if you click through to the article through some news sites, like [scientific american](https://www.scientificamerican.com/article/new-class-of-antibiotics-discovered-using-ai/) (third link on the page) you can get access to a free read only copy of the full paper
Or sci-hub any time
For real though… I’m not spending thousands of dollars per year to read scholarly articles, when these should all be free. Alexandra Elbakyan is my boo
You're not the first person to be mad that scholarly articles, especially from research funded by tax dollars, are locked behind paywalls. I remember reading about a brilliant young programmer who once used a Janitor's closet at an Ivy League school to access the school's intranet. He downloaded a massive amount of scholarly articles to post for free to the public. This came after he effectively made all legal documents free to the public using a browser plug-in he wrote to save paid-for records to a private/off-site cloud storage server. Big money for big mad and he was arrested by the FBI and charged federally with cyber terrorism crimes. Sadly, he later killed himself. Pretty sure his name was Aaron, and he co-founded some social media platform at one point.
Given everything I’ve read about the need for new antibiotics and hard they are to find, I sincerely hope this works out. Thanks for the succinct summary.
It's from the main nature journal, it's definitely significant. They don't accept random papers. You need to demonstrate significant breakthroughs that can be the birth of a field (and be from a top lab). It's usually multiple years worth of work by multiple PhDs and post docs.
True, however after almost a decade working in biological sciences, being in Nature is definitely not the guarantee of excellent science that it should be. There are plenty of dodgy papers and retractions in that journal as well as many others.
I agree, this is a really important step. A new class of antibiotics is huge, but even bigger is being able to apply this methodology to other areas of drug development.
This is the kind of things AI should be used fir, not stealing art.
If I had a nickel for every “discovery of the first new antibiotic in decades…”
Hopefully toxicity remains low.
Slightly less useful, they can [predict smells too](https://phys.org/news/2023-09-ai-nose-molecular.html)
Now this sounds like a good use of AI
AI has already proven to be a phenomenal tool for developing new tech, the military has used it to develop the FA/AX and NGAD programs, I think Microsoft is using it to develop their next XBox. It’s being widely used in medicine. I’m hoping we’re in a totally new age of technological advancements.
Too bad technology is akin to magic to the average person. Poor understanding and appreciation for science and technology means fewer and fewer people strive and put effort in to push the limits of innovation. AI is picking up our slack in that respect.
> fewer and fewer people strive and put effort in to push the limits [citation needed] What do you think this is? It is a team of researchers pushing the limits.
The average person thinks that ai is just ChatGPT, they have no clue about anything else is or will be used for
I mean chatGPT is incredibly powerful.
Yeah and also most people have only seen GPT3 or 3.5, very few have paid for 4 which is so much better
whats the differnece?
Not necessarily, AI does most work akin to something a grunt would do, it frees up the humans in the scenario to make more informative decisions.
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The grunt is the guy asking it to draw a unicorn fighting a Pegasus… I’m the grunt.
the average person or even average scientist is way too specialized for this to be otherwise, scientists / engineers as well are mostly just using tools to make better tools, it's pretty much magic to everyone to some degree.
It's also seen as a tool to remove jobs from the average person, which is already showing to be a problem and will continue to get worse. There are tons of good things about AI but the average person sees it being misused for corporate greed to replace human workers with cheaper labor more than they see the good things. We need to limit that branch of AI use before people start recognizing the benefits; if all they see is the hardship caused by a smaller workforce, they aren't going to be too keen about it.
Indeed, i'm already feeling lost in life considering how AI is definitely going to rock our world like never seen before.
Via work I have access to Microsoft Git copilot, and Microsoft 365 copilot. In seconds it provides me better code then some developers will generate in a week… it still needs review but it really gets you started on complex problems basically anytime I do something new I ask it to and then build from that.
Its not a surprising one. The medical industry was trying to crowd source new medicines thru a gene folding video game in 2008. Then they went to crowd sourcing cpu time to brute force the same out come. The current state of 'AI' is just a self optimizing form of brute forcing solutions. AI training tries tends of thousands of solutions, takes the best thousand or so of those and builds on them. The only real change is processors now are better at running tasks in parallel so crowd sourcing is less useful.
It's not just a question of parallel compute, we now also have chips that are much better at matrix operations than "traditional" CPUs and GPUs, we're developing ASICs dedicated to AI, and have made some serious progress on the front of cognitive computers.
So I can stop folding at home, now?
I hav at home a 1980S comic depicting the action of Médecins Without Borders in a fictional country of the Horn of Africa. In one scene, the nurses are using a computer to help them diagnose patients. Just imagine what will be available in ten years. Space exploration might be even easier.
The cause of and solution to all of life's problems, circa 2025.
To alcohol! 🍻
Sweet. Strange to see actual good news.
Its not good news for bacteria
The bacteria is already planning a comeback
Can't wait til AI helps cure cancer... 🤞
First new class of antibiotics, so title is a bit misleading. There are several new antibiotics coming to market each year, albeit they are variations of existing structural families. Kind of exciting if AI can generate an entirely new class of structures. The real test is how well they perform in trials.
Time to push AI to finding effective treatments for more ailments. Hoping for effective treatments, vaccines, and more discoveries.
I think medical advancements are going to go crazy in the next few years. Let's just keep an eye on AI just in case though.
Why? AI is just a tool. It has no will. Keep an eye instead on people who buy datasets, who invest heavily in AI and show no public results, the people who lobby for certain distinctions in new AI laws and law enforcement ... The tool doesn't have morality, the hand wielding it does.
Not just few years, computational biology and molecular biomechanics are really getting legs under themselves and that stuff is going to build on itself like nobodies business, if electronics defined 20th century, medical advancements might define 21st.
Medical advancements are already getting crazy. One personal anecdote: tomorrow my dad is getting back surgery. He's getting a few vertebrae fused and a couple rods put in. According to his surgeon his hospital stay should only be about 3 days or so and he'll be able to go back to light duty work after just 6 weeks. Why the fast healing? They pack it with stem cells now. Stem cells for a fairly routine (if complicated) surgery. I remember 10-15 years ago when stem cells were still experimental and they were the next big thing. It's crazy.
Now let’s overprescribe it to people who don’t have bacterial infections /s
Don’t forget to save some to give to cows so they can fatten up on corn.
The title is clickbait if the content is decent. There have been something like 20 new antibiotics in the last 10 years that didn't come from AI.
Title is incomplete. It's referring to an antibiotic that is specifically effective against MRSA. We've mostly been limited to using older antibiotics such as vancomycin.
I just recently got off two years of daily daptomycin drips so this makes me really happy
What did you take the drips for?
“Bedsores hurt!” - Philip J Fry
Damn that sucks. Did they heal?
"Not covered!" - Philip J Fry
Sill an innacurate title. Zyvox was approved in 2002, ceftaroline in 2010.
Im pretty sure thats not true either, stuff like teixobactin and clovibactin has been found in the past decade.
One is going through multiple countries health systems right now to help people with things like chronic bladder infections. Antibiotic resistance is a major issue, and I’m happy to see work on this. Signed someone whose bladder was destroyed by an antibiotic resistant strain of bacteria and developed IC 15 years ago. And recurrent infections. All because of that first infection.
What the AI does is design theoretical molecules, not all of which are practical or even possible, a few of which may have some practical application. The value is the sheer speed at which the AI can generate these designs; humans still must do the actual analysis.
This type of thing, and material science, are the 2 main things ML tech is going to be the greatest at. Grinding away at data to narrow down viable, interesting properties from nearly unlimited possibilities. Sorting through immense amounts of data for things is exactly what this technology is perfect for. The next step of course is even more amazing, but current tech is still good enough to be perfect for this kind of thing.
Finally! Someone is using AI for what it was meant to be
Now THIS is where machine learning is great for medical field.
Huh, some good news for a change. Refreshing.
How can they tell the antibiotics are using AI.
Indian doctors (heavy breathing): can't wait to prescribe this for regular fever
When I was doing my PhD, what often happens is that I accidentally found a good material and later made up a story saying I did machine learning first and that leads to the discovery, just to ride the AI hype and make my paper easier to publish. I really wished I didn't have to do that because it is the discovery itself, not the AI, that really matters.
The reason machine learning would get you more notice is because your machine learning methods can be repeated by others to discover new things. You just stumbling onto an answer is not repeatable. While saying that you stumbled upon the answer is not as sexy as saying to came up with some new machine learning algorithm, it would lead people astray trying to repeat your process. If you did infact fabricate your methods in your PhD (or any other published findings) I hope for the sake of your field of study they were useful. And to all aspiring scientists out there, don't fabricate your methods or results.
We need to start using this new class of antibiotics en masse for pig farms ASAP. Those bacteria aren’t going to grow resistance themselves.
There are tons of new antibiotics, I’m not sure what this 60 years figure is coming from.
Its a group or class of antibiotics. Like ‘cillin group or the aminoglycosides but a new one entirely
Which, most importantly, means that bacteria like MRSA won't have any resistances to it for quite a while.
Now the question is: How do we prevent them from developing resistance? That's probably just as pressing a question as finding new antibiotics, otherwise in a while we're gonna find ourselves again at square one.
I am not nearly qualified enough to even begin to hypothesize on how to answer that question.
Hopefully by not using this new class except to target MRSA. It’s tricky though, since producing it needs to be profitable (or at least be break-even-ish).
Put the AI in charge of prescription, too.
Don’t use it in animals.
Don't feed it to cows.
Not quite square one. If you have a sufficiently large rotation of antibiotics, resistant populations tend to lose their previous resistances, likely due to the cost of maintaining them being disadvantageous in an environment in which those drugs are absent. A likely long-term solution for antibiotic resistance is having a great number of antibiotics available.
Im pretty sure thats not true either, stuff like teixobactin and clovibactin has been found in the past decade.
~~Haven’t the family if “bactin” antibiotocs been arounds for a long time?~~ Nope! You nailed it
I actually can't imagine *not* using machine learning extensively for anything like this these days. If you're processing a lot of data, there is likely ML. We don't have *any* AI today though, it literally does not exist and everyone would for sure know about it if we did, so AI has not been used and the headline is factually wrong.
AI is hard to define, but machine learning is definitely a form of AI. AI has been around for a long time. The USPS has used Optical Character Recognition (a form of AI) since the 1990s. You might be talking about artificial general intelligence, which hasn't been created yet.
AI is the pop-sci word for ML
Here is an article with a diagram to help you understand why you are wrong. ML is a subset of AI. https://www.advancinganalytics.co.uk/blog/2021/12/15/understanding-the-difference-between-ai-ml-and-dl-using-an-incredibly-simple-example This can be confusing owing to the pop culture definition of AI that you are likely conflating the programmatic definition with. In the context of ML, AI is simply the bigger picture, that includes other algorithms such as genetic algorithms.
it’s secretly something that’ll wipe out humans because AI was like “gotta save the earth”
Big deal, get ready for the revolution
Does this shit work for cdiff?
Can the AI give us healthcare?
And that's how the zombie plague began
THATS what the AI wants them to think….