4 ms·

The "pioneer of Crispr" got 3 years for endangering human lives, which is pretty much a slap on the wrist. I would've done more, and I'm one of those "bioengine

The "pioneer of Crispr" got 3 years for endangering human lives, which is pretty much a slap on the wrist. I would've done more, and I'm one of those "bioengineers" you talk about. Unsanctioned human experimentation isn't something we should applaud. As for animal experiments, they are not nearly as difficult to get going as people think, SOPs for mice take a month on average to get approved in my experience. The vast majority of my dislike towards animal testing lies in the realm of cosmetics, not animals, and I'm sure most people would agree. Even so, the trend in research now is to move away from traditional animal models to organ-on-chips, simulations, and other human substitute models. Finally, Biology is SLOW. You haven't seen a "unicorn" because an MVP for a biotech company in therapeutics is 10 years away from when it starts needing funding, in a lot of cases. There are very few options for series A-B funds to fill the gap between seed and revenue stages for biotech startups, which is why licensing and partnerships between researchers and industry are the predominant options seen today, alongside the traditional NIH/DARPA/NSF funds. Maybe I'm biased because of my location (huge Biotech hub) and affiliations, but anytime I read complaints about biotech and medicine from software devs it reads like ignorance from people who are used to "moving fast and breaking things".

sansnomme 7y ago
And there it is. The first assumption is that my background is in CS and not biology, that I do not understand the nature of your deeply mysterious arts. You yourself hang out on HN, I hope the irony isn't lost. This whole attitude is exactly why there is no decent seed funding for biology. Too conservative, too risk-adverse. The ivory tower knows best. The obsession with "better to die from cancer than from an untested treatment". It took decades for Right to Try to become reality and still there is tremendous opposition. Let's leave the orphan drug rent-seeking to private equity funds. Individual researchers should "know their place" and thrive only in the generosity and largesse of pharmaceutical giants. It is no wonder people are losing faith in the biological sciences. When computing is bringing breakthrough after breakthroughs, what has biology given us? Some new materials? Marginally improved treatments? How many magnitude level improvements have you seen? Where is my iPhone? Where are my VR goggles? Most if not all improvements are slow incremental gains built on the blood, sweat, and tears of poorly-paid phds who will be lucky to get paid 6 figures after graduation. It is easy to "look back on the decade" and pat yourself on the back, celebrating the oh-so-vast gains. The gains in biology hardly holds a candle to how much computing has advanced. The field of electronics has gotten cheaper than ever. Yet in biology, just how many people do you think have access to say, cryogenic electron microscopy? This isn't on Stanford light source level of difficulty, but there has been no effort at all to democratise the technology. Your ML researchers have access to ASICs for computing mere months after they get designed, both actual hardware and in the cloud. Tons of funding and development being put into improving developer user experience. Can you say the same for biology? The amount of "data processing" for a cryo microscope is trivial by modern cloud standards. Where are the Raspberry Pis, the Arduinos, of biology? Where are the cheap microscopy equipment clones? Because there is no market. There is no demand for biology.
- Konnstann 7y ago
  Looking at computing vs biology as two fields is disingenuous, given that computing hasn't been around long enough to stagnate, although looking at ML research it is slowing down significantly. Computing is slowing down advancement as well, with silicon-based systems reaching their limit. What has biotech given us? Cheap portable HIV testing for developing countries, non-invasive targeted treatment of various cancers, (Magnitude level). If you don't see gains in the bioengineering space you aren't looking hard enough, and you also aren't taking into account the FDA scrutinizing new technologies and treatments before they are released into the wild. The assumption is you don't have a bio background because you have no idea why progress is slow. I'm wondering what kind of bio background you do have where time isn't an issue. Sure I can spin up a bunch of GPUs on demand to train my image classifier, but what I'm training it on is months of experiments run non-stop, and that's with a relatively quick animal model.

sansnomme 7y ago

And there it is. The first assumption is that my background is in CS and not biology, that I do not understand the nature of your deeply mysterious arts. You yourself hang out on HN, I hope the irony isn't lost. This whole attitude is exactly why there is no decent seed funding for biology. Too conservative, too risk-adverse. The ivory tower knows best. The obsession with "better to die from cancer than from an untested treatment". It took decades for Right to Try to become reality and still there is tremendous opposition. Let's leave the orphan drug rent-seeking to private equity funds. Individual researchers should "know their place" and thrive only in the generosity and largesse of pharmaceutical giants. It is no wonder people are losing faith in the biological sciences. When computing is bringing breakthrough after breakthroughs, what has biology given us? Some new materials? Marginally improved treatments? How many magnitude level improvements have you seen? Where is my iPhone? Where are my VR goggles? Most if not all improvements are slow incremental gains built on the blood, sweat, and tears of poorly-paid phds who will be lucky to get paid 6 figures after graduation. It is easy to "look back on the decade" and pat yourself on the back, celebrating the oh-so-vast gains. The gains in biology hardly holds a candle to how much computing has advanced. The field of electronics has gotten cheaper than ever. Yet in biology, just how many people do you think have access to say, cryogenic electron microscopy? This isn't on Stanford light source level of difficulty, but there has been no effort at all to democratise the technology. Your ML researchers have access to ASICs for computing mere months after they get designed, both actual hardware and in the cloud. Tons of funding and development being put into improving developer user experience. Can you say the same for biology? The amount of "data processing" for a cryo microscope is trivial by modern cloud standards. Where are the Raspberry Pis, the Arduinos, of biology? Where are the cheap microscopy equipment clones? Because there is no market. There is no demand for biology.

Konnstann 7y ago
Looking at computing vs biology as two fields is disingenuous, given that computing hasn't been around long enough to stagnate, although looking at ML research it is slowing down significantly. Computing is slowing down advancement as well, with silicon-based systems reaching their limit. What has biotech given us? Cheap portable HIV testing for developing countries, non-invasive targeted treatment of various cancers, (Magnitude level). If you don't see gains in the bioengineering space you aren't looking hard enough, and you also aren't taking into account the FDA scrutinizing new technologies and treatments before they are released into the wild. The assumption is you don't have a bio background because you have no idea why progress is slow. I'm wondering what kind of bio background you do have where time isn't an issue. Sure I can spin up a bunch of GPUs on demand to train my image classifier, but what I'm training it on is months of experiments run non-stop, and that's with a relatively quick animal model.