I’m just midway through a masters in bioinformatics, and am currently applying for jobs at deep learning startups, so I’m fairly familiar with AI and genomics.
A few suggestions:
Have you considered cognitive genomics? This is very relevant to the future of intelligence in the absence of radically superhuman AI. Plomin and Steve Hsu (BGI) are the main relevant researchers in this area.
Have you considered identifying pathogenic sequences? Companies that allow biological sequences to be ordered need to be able to accurately identify pathogenic sequences to reduce probabilities of disasters. Don’t know much more about this but it’s pretty future-relevant and close to your area, possibly even closer than biosecurity risks at large, which is also a good suggestion by Luke.
If by AI, you’re interested in machine learning research, then it would make more sense to start with Numpy (or Matlab if you have it), you can transition easily from R, and then C/C++/CUDA for the lower levels and Caffe or Torch for higher-level programming. Java and Hadoop seem more useful for scaling existing algorithms than for researching AI and AI safety.
At some point, someone will need to crunch a lot of data in order to create some reliable heuristics by which a majority of virulent DNA could be flagged for further review or quarantine. Preferably the sequences could be uploaded and scanned automatically before they are synthesized. This would go a long way towards reducing a big extinction threat. The first true Virus Scanner?
To be effective, you might need to cooperate with someone who has more technical skills, but your partner would certainly need your assistance to interpret the DNA strands before they could be effective so it is a good match.
Yeah, cognitive genomics could help humans to be smarter when we have to deal with an AI. It could have bad consequences too, mind. There are only some dozens of people who have the guts to work directly on the problem of cognitive genomics, so if you got in this field, you wouldn’t have to worry that your research was pointless. Rather, you could become a useful point of contact for people thinking about future tech.
I’m just midway through a masters in bioinformatics, and am currently applying for jobs at deep learning startups, so I’m fairly familiar with AI and genomics.
A few suggestions:
Have you considered cognitive genomics? This is very relevant to the future of intelligence in the absence of radically superhuman AI. Plomin and Steve Hsu (BGI) are the main relevant researchers in this area.
Have you considered identifying pathogenic sequences? Companies that allow biological sequences to be ordered need to be able to accurately identify pathogenic sequences to reduce probabilities of disasters. Don’t know much more about this but it’s pretty future-relevant and close to your area, possibly even closer than biosecurity risks at large, which is also a good suggestion by Luke.
If by AI, you’re interested in machine learning research, then it would make more sense to start with Numpy (or Matlab if you have it), you can transition easily from R, and then C/C++/CUDA for the lower levels and Caffe or Torch for higher-level programming. Java and Hadoop seem more useful for scaling existing algorithms than for researching AI and AI safety.
At some point, someone will need to crunch a lot of data in order to create some reliable heuristics by which a majority of virulent DNA could be flagged for further review or quarantine. Preferably the sequences could be uploaded and scanned automatically before they are synthesized. This would go a long way towards reducing a big extinction threat. The first true Virus Scanner?
To be effective, you might need to cooperate with someone who has more technical skills, but your partner would certainly need your assistance to interpret the DNA strands before they could be effective so it is a good match.
Cognitive genomics is definitely something I”ll look into, thanks.
Yeah, cognitive genomics could help humans to be smarter when we have to deal with an AI. It could have bad consequences too, mind. There are only some dozens of people who have the guts to work directly on the problem of cognitive genomics, so if you got in this field, you wouldn’t have to worry that your research was pointless. Rather, you could become a useful point of contact for people thinking about future tech.
Here are a couple of relevant articles. https://intelligence.org/2013/08/31/stephen-hsu-on-cognitive-genomics/ http://arxiv.org/pdf/1408.3421.pdf