Researchers at MIT, working with Nokia Bell Labs and Arizona State, built a robotic arm that can assemble and align a tabletop optics experiment, completing roughly 50 steps in about 30 minutes. The system takes continuous measurements as it works, so it can detect misalignment and correct it rather than just following a fixed script. The hosts use this as an example of the execution and measurement step of science, which is distinct from AI's ability to design an experiment, and note that this kind of lens and laser alignment is a routine but time-consuming part of atomic, molecular, and optical physics experiments, including some quantum computing setups.
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The project was supported by funders including the National Science Foundation, the Army Research Office, and Shell.
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The hosts note that frontier AI labs tend to prioritize the design step of experiments because it does not require building the downstream robotics and automation pipeline, which is not their core business.
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One host compares the task to his own PhD lab work and that of named colleagues (Prateek Puri, Elliot Bora) who spend significant time manually aligning lenses and lasers in AMO experiments.
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1:23:22first step that the frontier labs think they can take is this design and prioritize because it does not require this connection to the downstream robotics and automation piece which is not their bread and butter. So now let's transition and this is something we've talked about a lot is this with the methods is this equipment and measurement. We talk a lot about tools >> on the pod. We talk a lot about being precise in our measurement in our methods and MIT actually gives us a great example of this automating step. This is not necessarily new as in new in the last couple of years. It's been happening for some time but understanding how this now connects to
1:24:03these AI workflows is a different way to start to think about these steps. So researchers at MIT working in collaboration with Nokia Bell Labs and Arizona State built a robotic system that can assemble and align uh an optical experiment and this was actually highlighted uh recently in September. uh this research always talk about the funders supported by National Science Foundation, Army Research Office and some other funders, private funders including Shell and this was one of their demonstration videos uh where they have a robotic arm that in 50 steps in 30 minutes can set up the these
1:24:45lenses for this optical experiment which we've talked about previously. And not only can it set up the lenses if any it's because it's constantly taking measurements, it can also make a change to fix something when there becomes when a misalignment arises as well. So it's both things. It's a >> this is crazy >> human designed setup. >> Yeah. >> But it can set up and iterate when there's a misalignment. I mean I mean so already this is giving me flashbacks to my PhD days. Like for example, the table that they're on. You see all those holes? There's little screws that you can put in um and you can fasten like
1:25:26mirrors and lenses. um any type of tabletop experiment, meaning atomic, molecular, optical, like if you want to do molecular traps, a lot of quantum computing experiments are literally just this, which is establishing lenses everywhere and then um you know, aligning them to the point where you can suspend atoms in a laser or you can, you know, isolate a single atom to to do some type of spect spectroscopy measurement. >> This reminds me of the MIT double slit experiment episode. Yeah, this this is all that is like a lot of these
1:26:07experiments are literally just this >> and just so I you know I want to ask you briefly like the comp the sensitivity and complexity cuz someone who's watching this might be like oh this looks >> pretty No, this is incredible. like if if they're able to align a laser and like make sure that the transition frequency is exactly aligned to whatever you know system that they're trying to control like that's that's pretty incredible. Like if they're able to do that just generally like that's >> that's like half the work of these PhD students like my roommates you know like
1:26:48uh Pratik Puri >> I I don't mean to call you out but this is half your job like you know like so >> um Elliot Bora another friend of the pod like this is something that he does a lot I mean obviously there's a lot more that's in his head right there's a lot more stuff that they could do perhaps if they didn't have to spend their time >> doing that >> aligning lenses and lasers. And this is this gets to this is this was a demonstration going back to our three stages of mainly this idea of execution and measurement because AI can design all these things but we still have to be able to execute and measure
1:27:28>> and this is for optical experiments not biological experiments so different category but I'm just trying to give the listeners a sense of where these component parts are that people are ultimately trying to connect in order to get this closed loop endto-end uh AI based research cycle um you know but that step might close the equipment control loop >> as one component part of that now the next video that this is sort of a promo video so there there's some
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