Inside OpenAI
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Inside OpenAI
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Re: Inside OpenAI
#2I often wonder about this. Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community.
I think AI research is one of the most open, and this openness is really at the center of its growth. So I am happy OpenAI has started since it is within this vein of sharing that the community has already built. But I certainly don't fully grasp how it can open AI to the world unless it can share rather valuable data sets (often impossible to get data such as personal health record), and make computation much much cheaper.
Let me illustrate my concern; Alphago required not just 30m game sets and complex understanding of both a policy and value network design, but also 1000 CPU and 200+ GPU instances. Something on the order of a few million dollars to build and utilize.
I look forward to the work coming from OpenAI. I hope it lives up to the hype. But I believe AI will more than likely remain squarely in large enterprise since the cost of developing applications will be high for the short and possibly for the near long term.
Re: Inside OpenAI
#3I often wonder about this. Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community. I think AI research is one of the most open, and this openness is really at the center of its growth. So I am happy OpenAI has started since it is within this vein of…
I believe AI will more than likely remain squarely in large enterprise since the cost of developing applications will be high.
For perspective, the same thing was said about search engines in 1995. At the time, server-class computers (big DEC and Sun boxes) were expensive. Altavista had a computer nobody could buy. But it turned out, with some cleverness you could use commodity PCs instead. NVidia is doing impressive work to bring the price/performance of hardware down. I think the vast majority of applications will be possible on a startup budget.
I also think data sets will become more common and less critical over time. Unsupervised and reinforcement learning require less external data. And so much data is available openly.
Re: Inside OpenAI
#4I often wonder about this. Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community. I think AI research is one of the most open, and this openness is really at the center of its growth. So I am happy OpenAI has started since it is within this vein of…
Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community.
Actually we have no idea what the constituent parts of AGI are.
What you mention are the current state of the art for narrow AI projects like classification and segmentation - which is basically 100% of machine/deep learning currently, but are not generalizable yet.
As an example the pre-eminant biologically inspired computing researcher Richard Granger is skeptical (and I agree) that parallel silicon will be able to scale to the flexibility that we see in biological learning (aka General intelligence).
Based on what I see so far from OpenAI I don't see them getting to AGI. They haven't stated it as an explicit goal, I think because they don't have a pathway (nobody does by the way).
Re: Inside OpenAI
#5I often wonder about this. Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community. I think AI research is one of the most open, and this openness is really at the center of its growth. So I am happy OpenAI has started since it is within this vein of…
I believe AI will more than likely remain squarely in large enterprise since the cost of developing applications will be high. For perspective, the same thing was said about search engines in 1995. At the time, server-class computers (big DEC and Sun boxes) were expensive. Altavista had a computer nobody could buy. But it turned out, with some cleverness you could use commodity PCs instead. NVidia is doing impressive…
"For perspective, the same thing was said about search engines in 1995"
yeah, and since then, we've basically had 2 major search engines developed. Google and Bing :) and bing development cost billions
Re: Inside OpenAI
#6I often wonder about this. Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community. I think AI research is one of the most open, and this openness is really at the center of its growth. So I am happy OpenAI has started since it is within this vein of…
Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community. Actually we have no idea what the constituent parts of AGI are. What you mention are the current state of the art for narrow AI projects like classification and segmentation - which is basicall…
> Actually we have no idea what the constituent parts of AGI are.
Yup. We don't even have a good test for knowing AGI.
Frankly, we don't even know if we are AI or if everything is predestined.
We don't know if true randomness exists.
Currently no AI system can define its own goals. I'd like to know how Open AI would solve that. To me, Open AI seems like it will just end up as a giant open sourced machine learning toolset. That's great but not the initially stated goal, and they risk souring investors on future AI tech that actually has merit when they fail to achieve AGI.
Re: Inside OpenAI
#7Earlier quoted context omitted.
Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community. Actually we have no idea what the constituent parts of AGI are. What you mention are the current state of the art for narrow AI projects like classification and segmentation - which is basicall…
> Actually we have no idea what the constituent parts of AGI are. Yup. We don't even have a good test for knowing AGI. Frankly, we don't even know if we are AI or if everything is predestined. We don't know if true randomness exists. Currently no AI system can define its own goals. I'd like to know how Open AI would solve that. To me, Open AI seems like it will just end up as a giant open sourced machine learning too…
Yup. We don't even have a good test for knowing AGI.
Very true and I think significantly overlooked.
The closest thing I have ever found was the Universal Anytime Intelligence Test [1]
Re: Inside OpenAI
#8I often wonder about this. Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community. I think AI research is one of the most open, and this openness is really at the center of its growth. So I am happy OpenAI has started since it is within this vein of…
Re:computation. I wonder if there are talks between OpenAI and BOINC to open up some of their computational resources. With the new OpenAI environments platform they include a peer review/validation process. That may help concerns that BOINC resources would be used commercially.
Re: Inside OpenAI
#9If it is time we, human being should imprint some logic laws into all AI projects which are intent to create unsupervised AI?
Re: Inside OpenAI
#10I often wonder about this. Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community. I think AI research is one of the most open, and this openness is really at the center of its growth. So I am happy OpenAI has started since it is within this vein of…
Four things are needed to truly build advanced AI's (read deep learning, deep reinforcement learning): new algorithms, complex data sets, and advanced GPU based computing (optimally GPU in any case) but also an open community. Actually we have no idea what the constituent parts of AGI are. What you mention are the current state of the art for narrow AI projects like classification and segmentation - which is basicall…
You are correct to point out that machine learning is NOT general intelligence, and what OpenAI is working on really have very little to do with AGI and super-intelligence, sadly.
But how can you say "we have no idea what the constituent parts of AGI are" or "they don't have a pathway (nobody does by the way)"? There is an active and vibrant (if sometimes eclipsed) AGI community. There is an annual AGI conference. There are a half dozen or so actively developed AGI projects with comprehensive architectures with attached roadmaps. It's an active area of research, but it's not like we have no idea how to build a general intelligence, or what such an architecture might look like.