More automation may lead to more freedom in open ended exploration, stemming the dramatic decline that has happened in exploration. That would be a fantastic result.
And there is a distinct decline in open ended, personal exploration in academics. There are many reasons for this, but the syndrome is widespread throughout the West and throughout scientific disciplines. The first response to someone interested in recreating a published result or simply asking "What if?" is always "Who will pay for that?" Or more discretely, "Will it lead to a grant." Regardless if the cost is $100 in reagents and 8 hours of bench time in an idle lab, or $200 to machine a new reaction chamber the focus from administration is not enabling exploration but standing in line with your hand out.
hdivider 15 hours ago [-]
This is far bigger than people think.
So much advanced equipment is just sitting there in labs, waiting for humans to finally go and make experiments. Which they eventually get round to, sort of, when they can secure funding and when the grad student isn't ill or making mistakes or framing the problem the wrong way.
AI-driven labs can iterate 'good enough' hypotheses way faster than human R&D systems. Automated labs are going to be a major source of discovery.
vhiremath4 11 hours ago [-]
> Eve independently screened some 1,600 chemicals and modelled how their structure related to their activity to predict which ones were worth testing. King and his group armed the robot with background knowledge and a machine-learning framework for developing hypotheses. Eve then used those elements to design experiments to test these hypotheses and, crucially, performed them itself.
> King plans to use the system — which occupies one-fifth of floor space than Eve does — to model how genes, proteins and small molecules interact in cells. Part of that will involve taking around 10,000 mass-spectrometry measurements each day.
The throughput here is astounding, especially when driven by researchers who really know how to chart a path. I feel every time a critical feedback loop is made both faster and cheaper, it makes everyone participating better. I wonder whether we will see many more "whiz kid" scientific researchers than we have today.
xyzzy123 5 hours ago [-]
I don't really see why most existing equipment would be usable in this way. When you automate a thing you often have to rethink the entire problem. But more generally, automation is for _repeatable_ things and a lot of research is... not that.
The expensive equipment is usually a small (but crucial!) part of research activity, which involves things like talking to a lot of people, getting permission to do weird or new things, going out into the environment and collecting things in very specific ways, storing and transporting them carefully, observing, etc. Building or modifying existing lab instruments, doing various things with animals that are not co-operative ... and CLEANING. Who does all the cleaning?
Definitely use cases when you have a specific protocol you want to scale, but I'm also not sure how safe I would feel around AI with a license to experiment and access to dangerous reagents, high temperatures, etc. Or, god help us, an oligonucleotide synthesizer. Which is definitely going to happen (if it has not already).
dyauspitr 3 hours ago [-]
Probably like a ATLAS or a unitree robot.They are beginning to get very good.
magicalist 14 hours ago [-]
> So much advanced equipment is just sitting there in labs, waiting for humans to finally go and make experiments. Which they eventually get round to, sort of, when they can secure funding and when the grad student isn't ill or making mistakes or framing the problem the wrong way.
That's not really what the article is about though. Short of staffing it with humanoid robots, existing labs and their equipment will continue to be unused.
mmooss 11 hours ago [-]
> AI-driven labs can iterate 'good enough' hypotheses way faster than human R&D systems.
Is there evidence of that?
Rendered at 17:27:25 GMT+0000 (UTC) with Wasmer Edge.
And there is a distinct decline in open ended, personal exploration in academics. There are many reasons for this, but the syndrome is widespread throughout the West and throughout scientific disciplines. The first response to someone interested in recreating a published result or simply asking "What if?" is always "Who will pay for that?" Or more discretely, "Will it lead to a grant." Regardless if the cost is $100 in reagents and 8 hours of bench time in an idle lab, or $200 to machine a new reaction chamber the focus from administration is not enabling exploration but standing in line with your hand out.
So much advanced equipment is just sitting there in labs, waiting for humans to finally go and make experiments. Which they eventually get round to, sort of, when they can secure funding and when the grad student isn't ill or making mistakes or framing the problem the wrong way.
AI-driven labs can iterate 'good enough' hypotheses way faster than human R&D systems. Automated labs are going to be a major source of discovery.
> King plans to use the system — which occupies one-fifth of floor space than Eve does — to model how genes, proteins and small molecules interact in cells. Part of that will involve taking around 10,000 mass-spectrometry measurements each day.
The throughput here is astounding, especially when driven by researchers who really know how to chart a path. I feel every time a critical feedback loop is made both faster and cheaper, it makes everyone participating better. I wonder whether we will see many more "whiz kid" scientific researchers than we have today.
The expensive equipment is usually a small (but crucial!) part of research activity, which involves things like talking to a lot of people, getting permission to do weird or new things, going out into the environment and collecting things in very specific ways, storing and transporting them carefully, observing, etc. Building or modifying existing lab instruments, doing various things with animals that are not co-operative ... and CLEANING. Who does all the cleaning?
Definitely use cases when you have a specific protocol you want to scale, but I'm also not sure how safe I would feel around AI with a license to experiment and access to dangerous reagents, high temperatures, etc. Or, god help us, an oligonucleotide synthesizer. Which is definitely going to happen (if it has not already).
That's not really what the article is about though. Short of staffing it with humanoid robots, existing labs and their equipment will continue to be unused.
Is there evidence of that?