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Maybe this is not the answer you're looking for: but I think CRISPR-Cas9 seems like the most exciting technology probably in all of science. It's a system that

Maybe this is not the answer you're looking for: but I think CRISPR-Cas9 seems like the most exciting technology probably in all of science. It's a system that can be used to literally change the DNA of living creatures, and on top of that it's highly accessible. Think of the hacker culture today and now imagine the same rate of change for biological engineering. We'll have massive libraries of re-usable "components" for interesting DNA-sequences. People will slowly slice together more complicated features, and freely trade organic components with each other via post. At some point in the future electronics will catch up to bioengineering, leading to better ways to make changes to DNA. We'll eventually be able to change DNA in something like a "biology IDE" and have usable components printed out the other end. After that point, our world probably won't look anything like it does today. It won't be long before someone decides to give themselves glowing skin or super strong muscles (and people have already tried the latter!) I for one welcome our super-human overlords.

K0SM0S 7y ago
> I think CRISPR-Cas9 seems like the most exciting technology probably in all of science. I tend to agree. However, having spoken at length about this with a friend doing her PhD, there are a few major problems between now and then. - Scope: if you thought Big Data (relating to human behavior) was a massive endeavor (still very much not solved, not by a long shot), try genetics. We're talking orders of magnitude Bigger Data. We have the PoC but finding practical solutions remains a hard problem as we speak (needle in a haystack). - Money: Bio-sectors don't pay software engineers enough to compete with the tech sector (almost no one does), and bio-experts are generally not good enough at it. So there's a huge lack in terms of dual [SE skills + domain knowledge] experts for this category of problems. Research funding is massive in big (private) pharma and comparably non-existent in basic research — and for now, CRISPR-Cas9 is mostly the latter. The first problem (resources) will probably solve itself as time goes by (assuming some Moore's Law continuation however it's done), however the second problem (domain / education politics? Idk how to call it) could virtually be forever — academia and big pharma aren't exactly known for being fast movers or innovators, let alone disruptors. Especially when CRISPR-Cas9 is a direct threat to well-established revenues in the trillions — curing whatever is much less profitable than selling drugs to ease symptoms over a lifetime. If this sounds like somptuous irony, it's probably because it is.
- Balgair 7y ago
  > We have the PoC but finding practical solutions remains a hard problem as we speak (needle in a haystack). One of my former lab mates was doing his thesis on some fluorescent cancers screening stuff, somewhat similar. In his presentations, he'd use a slide explaining the order of magnitude issues in finding cancer cells this way. To illustrate this he'd explain it wasn't like finding a needle i a haystack, but more like trying to find a 20-gauge needle in a Walmart filled with 19-gauge needles. >Bio-sectors don't pay software engineers enough to compete with the tech sector (almost no one does), and bio-experts are generally not good enough at it. I've a fair amount of programming (enough to be really dangerous), so other students would come to me with help every once in a while. One of my friends getting his PhD in neuroscience traded a case of beer for an afternoon in helping him. He was doing some vision research with gerbil and was trying to time neuron spikes with some images on a screen. By the 32nd nested 'if statement', I requested another case of beer. Generally, research-grade programming and software is, at best, spaghetti. At worst, you get answers that you think are right, but are wildly off. You can really lie to yourself, and the rest of the world, when you publish those errors as facts. Most grad students are learning programming by the seat of their threadbare pants, and it shows.
snowwrestler 7y ago
I get the heebie jeebies when I hear computer technologists getting excited about gene editing. Computing and biology are opposite one another as disciplines. Computing has been built up by people from invented principles; but in biology we are working our way down from observations to try to infer the principles underlying them. It’s easy to look at our global computing infrastructure and think we are good at understanding complexity. But we built that; we should understand it. Again: not true for biology. There’s no guarantee that we will ever fully understand the full scope of how life works. And computing still has problems! Side effects are rampant in software; we usually call those bugs or vulnerabilities and there are a lot of them. And electronic computing has fewer ethical concerns. It’s generally not considered unethical to risk crashing a computer. Very different story if you are risking deforming foetuses
- bluGill 7y ago
  Genetics has its own share of bugs. I'd love to edit high cholesterol our of my genes. Yes we must be careful, but it isn't like doing nothing is risk free: doing nothing means me and my family have heart attacks and die young.
Crinus 7y ago
> Think of the hacker culture today and now imagine the same rate of change for biological engineering. I can't wait for all the pre-alpha version creatures :-P
sghiassy 7y ago
DIY Cas9 Crisper DNA Kit: http://www.the-odin.com/diy-crispr-kit/ http://www.the-odin.com/diy-crispr-kit/ Not affiliated with the company. Just amazed at how accessible that tech is becoming.

K0SM0S 7y ago

> I think CRISPR-Cas9 seems like the most exciting technology probably in all of science. I tend to agree. However, having spoken at length about this with a friend doing her PhD, there are a few major problems between now and then. - Scope: if you thought Big Data (relating to human behavior) was a massive endeavor (still very much not solved, not by a long shot), try genetics. We're talking orders of magnitude Bigger Data. We have the PoC but finding practical solutions remains a hard problem as we speak (needle in a haystack). - Money: Bio-sectors don't pay software engineers enough to compete with the tech sector (almost no one does), and bio-experts are generally not good enough at it. So there's a huge lack in terms of dual [SE skills + domain knowledge] experts for this category of problems. Research funding is massive in big (private) pharma and comparably non-existent in basic research — and for now, CRISPR-Cas9 is mostly the latter. The first problem (resources) will probably solve itself as time goes by (assuming some Moore's Law continuation however it's done), however the second problem (domain / education politics? Idk how to call it) could virtually be forever — academia and big pharma aren't exactly known for being fast movers or innovators, let alone disruptors. Especially when CRISPR-Cas9 is a direct threat to well-established revenues in the trillions — curing whatever is much less profitable than selling drugs to ease symptoms over a lifetime. If this sounds like somptuous irony, it's probably because it is.

Balgair 7y ago
> We have the PoC but finding practical solutions remains a hard problem as we speak (needle in a haystack). One of my former lab mates was doing his thesis on some fluorescent cancers screening stuff, somewhat similar. In his presentations, he'd use a slide explaining the order of magnitude issues in finding cancer cells this way. To illustrate this he'd explain it wasn't like finding a needle i a haystack, but more like trying to find a 20-gauge needle in a Walmart filled with 19-gauge needles. >Bio-sectors don't pay software engineers enough to compete with the tech sector (almost no one does), and bio-experts are generally not good enough at it. I've a fair amount of programming (enough to be really dangerous), so other students would come to me with help every once in a while. One of my friends getting his PhD in neuroscience traded a case of beer for an afternoon in helping him. He was doing some vision research with gerbil and was trying to time neuron spikes with some images on a screen. By the 32nd nested 'if statement', I requested another case of beer. Generally, research-grade programming and software is, at best, spaghetti. At worst, you get answers that you think are right, but are wildly off. You can really lie to yourself, and the rest of the world, when you publish those errors as facts. Most grad students are learning programming by the seat of their threadbare pants, and it shows.

snowwrestler 7y ago

I get the heebie jeebies when I hear computer technologists getting excited about gene editing. Computing and biology are opposite one another as disciplines. Computing has been built up by people from invented principles; but in biology we are working our way down from observations to try to infer the principles underlying them. It’s easy to look at our global computing infrastructure and think we are good at understanding complexity. But we built that; we should understand it. Again: not true for biology. There’s no guarantee that we will ever fully understand the full scope of how life works. And computing still has problems! Side effects are rampant in software; we usually call those bugs or vulnerabilities and there are a lot of them. And electronic computing has fewer ethical concerns. It’s generally not considered unethical to risk crashing a computer. Very different story if you are risking deforming foetuses

bluGill 7y ago
Genetics has its own share of bugs. I'd love to edit high cholesterol our of my genes. Yes we must be careful, but it isn't like doing nothing is risk free: doing nothing means me and my family have heart attacks and die young.

Crinus 7y ago

> Think of the hacker culture today and now imagine the same rate of change for biological engineering. I can't wait for all the pre-alpha version creatures :-P

sghiassy 7y ago

DIY Cas9 Crisper DNA Kit: http://www.the-odin.com/diy-crispr-kit/ http://www.the-odin.com/diy-crispr-kit/ Not affiliated with the company. Just amazed at how accessible that tech is becoming.