We're trying make small farms more automated and enable them as economically feasable businesses. Our main project is a precision farming robot, and within the next year were hoping to ship dev kits
I'm definitely your target audience. For the past few months ive been super curious about crispr and just enrolled in OChem to try to really understand this stuff. I probably have all those misunderstandings. Any pointers?
First, ochem is good and there are aspects of cas proteins that you need ochem to understand, but you'll probably want to take biochemistry as well since it deals directly with proteins and nucleic acids (though I assume ochem is a pre-req wherever you are anyway).
I really need to sit down and be thorough about this, but off the top of my head, here are some things I frequently see misunderstood:
1) not all diseases can be cured by changing the genome, even in principle
2) delivery is an unsolved problem! we can't get CRISPR into every cell, or necessarily any arbitrary tissue. This is probably the main roadblock right now for CRISPR therapeutics. For some genetic diseases this is fine. For example, there are some conditions where fixing only 20% of cells is enough to get a clinically-meaningful improvement, but for others this won't work. There are ex vivo techniques, where you remove some cells, modify them in vitro, and transplant them back, but that can't be done with all (most?) cell types.
3) Most traits aren't controlled by a single gene, and those interactions can get very complicated.
4) We don't know what every gene does
5) Even when a gene has been thoroughly characterized, we don't necessarily know what effect a particular modification will have
6) Biology is complicated af. Every change could potentially have unanticipated side effects.
7) Even if God descended from the clouds and granted us the ability to modify any genome in any and all cells of our choosing without any negative side effects, we wouldn't be able to cure every disease even when there's clearly a genetic component. Aging comes up on HN a lot but it's probably the least tractable disease I can think of.
I could go on, but I'm going to stop here and save it for the blog. To be sure, the technology is being developed rapidly, but there are some problems where it's just a matter of iterative engineering, and others where it's going to take a century of dedicated effort.
I'm trying to learn Haskell, but don't know anything about app development. Ultimately, I want to iterate and use this project to learn how to write idiomatic, production quality Haskell, and learn app development.
This is a draft of the game engine. Rules in README. Feedback is appreciated.
I'm self-taught too, and strictly interested in research-focused CS masters or PhD programs (as opposed to industry-focused cash-cows). I think I'm mostly interested in studying PL or program synthesis, but I'm also open to other ideas. How did you make that jump from self-taught to qualified for a PhD program?
I made this exact jump. The answer, for me, was a four year bachelor's degree.
I was a self-taught software engineer, not a self-taught computer scientist. I was writing production code for fairly normal stuff, not proving theorems or implementing research prototypes of new ideas. So YMMV.
If you can make it through TAPL or PFPL on your own, then you probably know enough to be useful to some random grad student somewhere. Latch onto an implementation effort, get authorship on a popl/splash/pldi paper or two, and that's probably enough to convince some faculty somewhere to take a chance on you.
But most good graduate programs still require a regionally accredited degree. Getting an exception to that rule will likely require a publication record. (Getting into good graduate programs often requires a publication record in any case. I recommend against attending not-good graduate programs.)
I think that CS vs SWE thing happens with a lot of people, and I got caught there, too. Luckily, I ended up really liking CS and it introduced me to the field, whereas otherwise I would've gone for SWE. There really needs to be a 'teachYourselfSWE' for people who are into that.
How can you tell which one is right for you? So many computer scientist graduates I know ended up pursuing software engineering that I've mistakingly conflated the two.
it's really theory (CS) vs building things (SWE). As you want to build larger projects, or build them better, you rely on CS ideas to do that. So SWE is really engineering assisted by applied CS. I've been studying CS for about two years and am only now learning any real application development. You can study CS without ever touching a computer or building an application (though doing both those things will give you context for why CS topics matter).
It's kinda like if you want to build a rocket to get to space, you can tinker with propellant, metal, and fire, and be a hobbyist that eventually you build a rocket to go to space. Or you can be a physicist and calculate everything on paper. To get to space you really need both those people, but the physicist can learn to build and the engineer can learn theory.
> but the physicist can learn to build and the engineer can learn theory.
So is this why frameworks exist? To abstract away the theory that proves something more "performant" or "sufficient", and allow the builder to do their thing?
More or less yes. The idea is that a framework (ideally) does some feature A the "right" way and programmers using the framework gain the benefits of convenience and safety, often at the cost of flexibility. Frameworks will usually try and balance the power or depth of the domain its abstracting with ease of use.
A good framework will stop beginners from making critical mistakes, decrease the amount of code its users have to write, and offer professionals well-constructed ways around its handholding as needed.
I strongly recommend OSSU! Both books and MOOCs have their place, and sometimes a MOOC is easier to stay motivated, provided a schedule, and exercises of appropriate number and difficulty.
I really like reading books too, but sometimes the completion-ist part of me is too strong and I shouldn't really do all the exercises.
In comparison with teachyourselfcs OSSU looks lame, serious. Structured badly, tons of links & strange YouTube channels. TYCS has chapters and 2-3 best resources about, ideal for this case.
For beginners I highly recommend Harvard CS50, the best of the best course available for free and paid too.
I agree that there seem to be a variety of links, but most of the courses linked there are of very high quality and I don't seem to see the "YouTube channels" that you're referring to. One thing I was unsatisfied with with TYCS is how it lists Crafting Compilers for the compilers/PL section of the curriculum. I would argue that more important than the specifics about compilers is a high-level understanding of various ideas in programming language design, and be able to understand the building blocks of different languages and compare the trade-offs of using one language compared with another. Of course, if you go through SICP as an entry point to computing, as suggested in TYCS, then you might be somewhat better off, but it's still not the same as a dedicated course on PL itself.
Dan Grossman from the University of Washington has an excellent course Programming Languages on Coursera: https://www.coursera.org/learn/programming-languages/, which I think would be far more relevant to modern programmers than studying compilers specifically. And I'm glad to see this course listed under the "Core Programming" section of OSSU.
It's remarkable how the course goes from zero to several complete projects in different domains and technologies in just a few weeks. CS50 is a real stepping stone.
I just got hired on a ~100 acre farm to basically do this. We have one other person who's been working on a auto weed puller (autonomous driving over rows and computer vision to pick weeds). Would love to talk more about this! my email is zach_asmith@yahoo.com
Just finished endurance about the first group to try and overland Antarctica. Failed, then was out at ice and seat for nearly 2 years. Just started endurance by Scott Kelly. So far it's good but the Antarctica one was better
The alternative is we either go extinct on earth or find another earth-like planet to go to, which won't have humans on in and may not be able to support us any better than mars
We're trying make small farms more automated and enable them as economically feasable businesses. Our main project is a precision farming robot, and within the next year were hoping to ship dev kits