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While I was reading 1984, I had to put it down because it was so depressing. It would be the end result of our experimentation with surveillance state coupled w

While I was reading 1984, I had to put it down because it was so depressing. It would be the end result of our experimentation with surveillance state coupled with AI management that outperforms even the smartest human being. In the end, it won't be our willful submission to AI overlords but economies of scale heavily valued by our capitalist economy that will be our undoing. but this also means untold riches that build & sell the new AI driven economies of scale. we've previously seen titans arise from the industrial revolution by doing the same thing. It's no time to be a Luddite.

malux85 10y ago
I think one way to help with this is the democratisation of A.I. It's not a silver bullet to the problems you describe, but a step in the right direction. They key is that the technology is available to everyone very cheaply. Having worked with hundreds of data scientists and data engineers over the last couple of years the common theme is that they want to get into A.I. but configuration hell or poor documentation has stopped 50-80% of them from being able to experiment. So I built SignalBox - a Deep Learning web platform with a set of "blueprints" for common tasks. It deploys to a bulk standard linux platform and once deployed has a web interface for generating neural networks, evaluating them, training them in parallel. Coupled with common ingestion patterns and data collectors, and from any point you can jump into iPython and start modifying the code for yourself. This gives newbies a pre-built, optionally GPU accelerated platform that they can play with, but also the flexibility of jumping to code so they can grow. You know what I would love? 10 million pounds. Yes I am dreaming. But then I would release SignalBox for free, but due to the capitalistic nature of society I'm forced to sell it, which I am doing. If I had 10 million, I would pursue some of the advances in computational chemistry for drug discovery, I do this for fun when I'm not working on platform, did you know that about it's estimated 10^8 molecules have been synthesised, whereas the range of potential drug like molecules is estimated at between 10^23 -> 10^60. I think there's real potential here, also I would like to explore epistasis modelling which I have been reading a lot of papers on too, and auditing some code from some PhD students I am mentoring, it's showing some good promise. I dont want to work for a living, I want to spend 100% of my time working on using AI to help large numbers of people, but I've set my goal at 10 million first, that should be enough for me to never have to worry about money ever again, and buy enough GPU servers to advance state of the art
- brilliantcode 10y ago
  I have no idea why your comment was downvoted, I thought it was highly relevant and reflected on what I had written. First of all, I'm super curious about your product, I've reached out using my email in my profile. You are right on the money in that documentation and heterogenous nature of configuring and getting ML/DL packages up and running is a large blocker. Personally for me, the training, setting up just to begin experimenting was a frustrating experience. I think democratization is already taking place with open source alternatives like https://deepdetect.com/ https://deepdetect.com/, I've only been able to install and play with the API and I'm trying to evaluate it further by building an app with it. But it hits that pain point in that it actually enables me to be in a position where I can now begin experimenting without having to deal with configuration and documentation noise. $10 million pounds ($12m USD) is certainly not impossible and I think you are on your way. I'd love to have $28 million USD, I think I could live a comfortable life without having to work. The marginal utility really falls off beyond 70,000 USD / year according to stats multiplying by 40 years, it yields $2.8m USD not adjusted for inflation, so just to be safe, I multiply it by 10. I'd love it if it could be a 100x or even 1000x but the probability of that is pretty damn slim (but not impossible). Here's to both of us for a successful 2017!

malux85 10y ago

I think one way to help with this is the democratisation of A.I. It's not a silver bullet to the problems you describe, but a step in the right direction. They key is that the technology is available to everyone very cheaply. Having worked with hundreds of data scientists and data engineers over the last couple of years the common theme is that they want to get into A.I. but configuration hell or poor documentation has stopped 50-80% of them from being able to experiment. So I built SignalBox - a Deep Learning web platform with a set of "blueprints" for common tasks. It deploys to a bulk standard linux platform and once deployed has a web interface for generating neural networks, evaluating them, training them in parallel. Coupled with common ingestion patterns and data collectors, and from any point you can jump into iPython and start modifying the code for yourself. This gives newbies a pre-built, optionally GPU accelerated platform that they can play with, but also the flexibility of jumping to code so they can grow. You know what I would love? 10 million pounds. Yes I am dreaming. But then I would release SignalBox for free, but due to the capitalistic nature of society I'm forced to sell it, which I am doing. If I had 10 million, I would pursue some of the advances in computational chemistry for drug discovery, I do this for fun when I'm not working on platform, did you know that about it's estimated 10^8 molecules have been synthesised, whereas the range of potential drug like molecules is estimated at between 10^23 -> 10^60. I think there's real potential here, also I would like to explore epistasis modelling which I have been reading a lot of papers on too, and auditing some code from some PhD students I am mentoring, it's showing some good promise. I dont want to work for a living, I want to spend 100% of my time working on using AI to help large numbers of people, but I've set my goal at 10 million first, that should be enough for me to never have to worry about money ever again, and buy enough GPU servers to advance state of the art

brilliantcode 10y ago
I have no idea why your comment was downvoted, I thought it was highly relevant and reflected on what I had written. First of all, I'm super curious about your product, I've reached out using my email in my profile. You are right on the money in that documentation and heterogenous nature of configuring and getting ML/DL packages up and running is a large blocker. Personally for me, the training, setting up just to begin experimenting was a frustrating experience. I think democratization is already taking place with open source alternatives like https://deepdetect.com/ https://deepdetect.com/, I've only been able to install and play with the API and I'm trying to evaluate it further by building an app with it. But it hits that pain point in that it actually enables me to be in a position where I can now begin experimenting without having to deal with configuration and documentation noise. $10 million pounds ($12m USD) is certainly not impossible and I think you are on your way. I'd love to have $28 million USD, I think I could live a comfortable life without having to work. The marginal utility really falls off beyond 70,000 USD / year according to stats multiplying by 40 years, it yields $2.8m USD not adjusted for inflation, so just to be safe, I multiply it by 10. I'd love it if it could be a 100x or even 1000x but the probability of that is pretty damn slim (but not impossible). Here's to both of us for a successful 2017!