Funding Friday: Make Your Own Robots

I just backed this project. I like the part in the video where the robot passes them spices for their dinner.


Comments (Archived):

  1. jason wright

    I’ll take a Tank Base with a Drone Top running on a Gun Control Cerebrum Core. That might give the NRA pause for thought.

    1. Kesha

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  2. Richard

    I think it was George Stephonoloplis who said It’s the cleanup stupid!When this robot can return everything back to where it belongs on my bathroom console, I’m all in!

  3. awaldstein

    Cool.I live in the neighborhood of Stuyvesant High downtown and the kids are always out on the street with robots they built.Listened (I’ll find) to an A16 podcast on the social relationships we may develop with a host of single function robotic helpers. Super fascinating and I think true and inevitable.

  4. Richard

    When the standards of twitter block anything but alllow this excrement, you’ve created a monster @twitter @jack.https://uploads.disquscdn.c

  5. sigmaalgebra

    Amazing. Astounding.Maybe one of the best toys I had growing up was the go cart I made out of some scrap materials in the garage and an old lawn mower engine: The thing taught me some about gasoline, piston engines — still good stuff to know.The toy here looks good but may not be as good as that go cart.So, it’s a toy and maybe a good toy.It is better than a toy? For this we come to a what appears to be a foundational issue: What the heck can we do with it? Or if so far nothing important, what the heck does it illustrate we might be able to do important in the future? I.e., that go cart I built taught me a lot that is still useful for evaluating, selecting, owning, driving, and maintaining a car, and, of course, also lawn mowers, and was part of why I was made a Full Member (not so easy to get) of the SAE — Society of Automotive Engineers.Or for any attempt at progress in technology, what the heck can we DO with it, that is, what is the utility, what is it good for?The world of applied research is awash in solutions looking for problems. These snap together general purpose modular robot parts look amazing where we suspect that they will be good at least for SOMETHING important or good learning toys for something important in the future.Then we come to: What the heck is the potential of such technology?When we look at an old tool chest we see lots of screwdrivers — different lengths, head types — blade, Phillips, Torx –, different head sizes, etc. We do know easily what the utility is. But what is the utility of these robot components or, more generally, such technology?Seems to me that is “the question”, whether just to assume some utility or, ask for proof first or just cast them away with the rest of the junk in a sea of troubles or some such mess made of the poor bard.In this case and quite generally it’s a darned important question: What the heck is the potential? Then, next, how the heck are we to look for, find, invent, evaluate work with good potential?Here is an approach I am taking:(1) Assume that quite broadly what will be of value is more information. From some obvious examples, that’s easy enough to accept, e.g., if we had good information about what pork bellies would be selling for next month, we could make a bundle in a hurry and provide financial security for the family, kids, grand kids, etc.(2) Likely the central and most important way to get more good information is to take available data and apply powerful manipulations. Well, those manipulations will necessarily be mathematical, understood or not, powerful or not.(3) Nicely enough, there is a lot in advanced pure math that shows in some senses that seem might be powerful some amazing manipulations. E.g., the math is in rock solid theorems and proofs, and sometimes the theorems say some just amazing things about the results of some manipulations — amazing, beyond belief.Here’s one: Just by some definitions based on some quite abstract foundations, essentially everything we can ever observe that might vary over time is a stochastic process. Yup, of course the stock market, all parts of the economy, the weather, everything we observe in medicine, astronomy, geology, etc. are stochastic processes. Then there is a theorem: Every stochastic process is the sum of a martingale part and a predictable part. And there’s another theorem: Each L^1 bounded martingale converges to some random variable. That is, given an such a martingale, there’s for it one random variable. Given one sample path of the martingale, it converges to one ‘sample’ of that random variable — converges exactly, right to the point, as accurately as we please. Moreover the rate of convergence is among the fastest of anything known in math. Astounding stuff — applies to everything there is, has ever been, and ever will be.What can we do with it? Well, there have been some applications. But right away we see some astounding results, totally beyond any confidence from any intuitive guessing, with no doubt, and maybe pointing to some powerful data manipulations. E.g., I was surprised once: I just wanted some stochastic process sample paths for some testing of an idea. So, I wrote some code but right away was disappointed because each sample path started off jumping around nicely as I wanted but soon calmed down and soon mostly quit moving at all — just went nearly constant. Each trial sample path went to a different constant, but each sample path went just to a constant, yes, a constant particular to that sample path but, still, just a numerical constant. Then looked again at my code to generate the sample paths and found that, yup, by accident I’d generated an L^1 bounded martingale. Yup, the theorem was correct! And the convergence to a constant was darned fast.And as amazing as the martingale convergence theorem is, the other part is down right a candidate for way too much — the other part is predictable, and, yup, that means just in the sense we would want for those pork bellies. Are we listening yet?Broadly stochastic processes are the vanilla case of wildness, unpredictability, chaos, randomness, but martingale theory shows that the wildness can’t be as wild as we would have thought intuitively and, in fact, can be significantly tamed to a cute kitten. So, disorder is not always as bad as we would guess intuitively, and we have some chances to bring some order to the disorder. So, this order looks like a source of what we were looking for — information out of data.Disclosure: My startup is based on some advanced pure math, not martingale theory but maybe as amazing. E.g., here at AVC I was asked how accurate my work was, and I responded “perfect” — in both theory and practice, that is essentially the case. A bit amazing.So, to bottom line it, if want more powerful data manipulations to do better getting valuable information out of available data, proceed mathematically, maybe with some advanced pure math that is able to say amazing things of great generality. Expect that that will be the mountain with the mother lode of tools for valuable information. Yes, that may not be the only way to get rich!So, what does computer science have to do with it? Sure, from that field we can see how to have machines do the data manipulation recipes we got from the math. But, and in public recently there has been a lot of hype and confusion on this point, computer science is not how to do the data manipulations, is not the math, but is just the grunt work for the manipulations specified by the math. So, right, the key is the math. Sorry, nearly no computer science profs or students studied nearly enough pure math.Instead of the robot components and instead of other intuitive guesses about what will be valuable, I suggest the role of math I outlined.