

Leader of China’s genomics powerhouse steps down to pursue AI research - superfx
http://www.nature.com/news/visionary-leader-of-china-s-genomics-powerhouse-steps-down-1.18059

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superfx
This question on CRISPR vs. deep learning on Quora is possibly relevant:
[http://www.quora.com/Which-of-the-following-will-have-a-
more...](http://www.quora.com/Which-of-the-following-will-have-a-more-
profound-impact-on-humanity-within-the-next-50-years-CRISPR-or-Deep-Learning)

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dave_sullivan
Deep learning (or more powerful machine learning techniques generally) will be
important for making CRISPR useful.

For instance, we'll need to be able to more accurately predict the result of
highly complex interactions that would arise from modifying DNA. We do have
the ability to generate _tons_ of data, but we have less ability to analyze it
and build predictive models.

Deep learning is the best bet today of being able to do that on huge
quantities of data where the subject matter experts really don't know what
"high level" features they're looking for. But they know the "result" and want
to tell "good result" from "bad result" (or from 10,000 other results). Deep
learning is good at (and getting better at) filling in the blanks in between,
the high level features.

I've been interested in deep learning for several years, and CRISPR is
something that's recently come on my radar that I'm becoming convinced will be
similarly impactful. And to be clear about "impactful", I mean we're in 1992
if you compare The Internet to advances in machine learning (which, it is
hoped, will somehow lead us to a breakthrough in AGI, or at least a better
definition of intelligence). So the technology is here and will continue to
advance (probably exponentially) as it's productized, refined, and ultimately
commoditized over the next two decades.

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freewizard
BGI fails on its IPO plan, which is probably one reason behind Mr Wang's step
down.

My guess is it's not ML vs Bio-tech, but ML for Biotech in Mr Wang's next
move.

