>I would like to take part in laying groundwork for future autonomic robots powered by AI that are capable of performing dental procedures.

Why?

ML is used as a tool in robotics, but there is much more to a successful robotics project than ML.

Also a cool read, thanks!

I agree that the tone of my original comment was overly snarky.

The challenge to learn ML for a middle-aged dentist is immense, and probably not where his best uses lie. I was fearful most on here would just tell him to take the plunge. But I see that others have gotten my point across much more eloquently (and not as snarky ;) ).

You can try to help by creating a speedy way to pass info, like an image from a X-ray to cartesian robots with and plastic extruder (aka 3D printers).

In this way you can make custom braces and prothesis very cheaply and a help a lot of people.

You know laser eye surgery has been around for a long time right? Blasting potentially blinding lasers into your eyes is risky too, these products only see the market after years of proving themselves in controlled settings.

Once a doctor passes their exams, that’s the last time anyone really pays attention to what they’re doing. That should make you more nervous.

I have just retired from another medical domain.

TBH 95%+ of my job could have been automated.

A nurse or similar with basic training could have operated the equipment, and an AI could have instructed her/him of the required actions.

My main contribution was quizzing the patient to elicit what really was going on, and not what they said was happening.

A personal AI avatar could do this work - or the nurse could be prompted to ask a series of targetted questions.

No doubt, many medical domains could be fully (or almost so) automated,

Medical robotics is a field that is booming now and that is hungry for tech-inclined licensed practitioners to join them. Just go advertise yourself to startups in the field, I am sure you will get interesting proposals.

I’ve seen many a doc not stop when they should have.

Source: Read 10 years of disciplinary reports and was positively horrified…. Way worse than I ever would have believed

I expect a human to stop when I flinch and I'm in pain. I don't expect a robot to do that. At least not until I see thousands of operations done automatically with no victims.

Important though to note are literally not enough people just taking stuff implemented in scikitlearn or whatever and applying that to their own problems, and in and of itself that can be novel and interesting even if its not a shiny new model.

> As I said domain knowledge and/or providing data and relying on the technical expertise of others is the most valuable direction to go.

Its mainly the way you wrote your comment that left a bad taste in my mouth, this line specifically is probs a fine recommendation for OP.

I took the plunge many years ago. Quit clinical work and dedicated myself to developing and emerging technologies. Was a difficult decision but I knew that’s where everything was headed.

Hate to say this, but being in the industry I can tell you that the public should be more terrified of people than the robots. Sure robots can make mistakes, but humans make many, many more.

There are already some products in use, Yomi is an FDA approved robotic solution for dental implant surgery. I have also seen a robot for automatic crown preps but it’s still in development.

Intraoral scanner companies have invested heavily in AI; first for better scan results, now for diagnostics and treatment planning.

And that’s just the start of it, it’s honestly been a privilege to be able to peek behind the curtain and see what’s coming next, it’s really amazing.

Like others said, working with Universities and research institutes is a great way to contribute your knowledge and potentially build something game changing. Good luck!

Only a small minority is able to make significant technical contributions. I may have misinterpreted his angle of groundwork, but as he mentioned resources to try and learn ML I assumed he meant technical. As I said domain knowledge and/or providing data and relying on the technical expertise of others is the most valuable direction to go. I think we are actually in agreement here.

I myself work with engineering groups on some applied projects and a lot of the 'applied ML' outside of CS is absolutely horrendous.

Robots make mistakes, but they’re heavily regulated. Being in the industry I know humans make many, many more mistakes .. worse still many of them don’t learn from their mistakes but keep making them it until they retire.

Seems terrifying bcs if you strart vibrating from pain a dentist will stop immediately while a robot will probably just hold your head with 1 hand and continue drilling. I really hope AI robots (autonomous or not) nvr come to fruition.

Do you actually work in ML research lol? About as important as fundamental research on architectures losses and optimisers is the applied end of things and tons of applied stuff is absolutely something other domain experts can contribute to, non ML non CS expertise is absolutely essential to i.e. the stuff my group does. "State of the art on some famous benchmark" is not the be all and end all of this field and "only a small minority is able to make significant contributions" is an absurdly incorrect statement.

Apparently it's An upsetting 2223 lines of code now.

I admire your passion and good intentions, but why do people think they can fundamentally contribute (laying the groundwork) to the SOTA of a technical field without any background and limited time. Thousands of PhDs working on AI dedicate almost every minute of their lives to this field, and only a small minority is able to make significant contributions that lay the groundwork for anything at all.

Nobody expects to be able to become a surgeon as a hobby; why do people expect to do excellent ML research as a hobby? Additionally, with all due respect, your paragraph further shows very limited understanding of current surgical robotic technology and ChatGPT.

The best way you can contribute is to work with ML experts and offer domain knowledge or data — do not expect to contribute on a technical/foundational level as a hobbyist.

Most valuable would probably be if you advise people what not to do. Or why it might be a bad idea. That would be much more valuable, as ML Engineers have no idea about that.

You’d be surprised, people who purchase services like this are targeted by advertising just as much as people buying commodity items.

If anything, this thread proves that these guys aren’t advertising enough with so many “DM me, I need guys like you” style comments.

agreed. MLs impact for dental health would be a orders of magnitude larger if channeled into biological discoveries or prevention based on saliva analysis or eating habits stats than with precision robots. Granted the latter would make much cooler headlines.

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Thanks! It depends on exactly what you're planning, but CodaLab (https://codalab.lisn.upsaclay.fr/competitions/) or their new platform CodaBench (https://www.codabench.org/) will probably work well.

They both allow you to run competitions for free, and people do use them for teaching purposes (you'll see some examples if you browse through the list of competitions).

I'm planning on writing a shorter blog post on running competitions soon.

I would encourage you to consider a biological approach. Many dental problems are caused by oral bacteria. If it’s possible to change the micro biome inside the mouth, it would be the biggest revolution in the history of dentistry.

Another, older post on this: https://thegradient.pub/state-of-ml-frameworks-2019-pytorch-dominates-research-tensorflow-dominates-industry/