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Inside OpenAI

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Re: Inside OpenAI

#11

Post by maaku »

tlb wrote: post #3
freddealmeida wrote: post #2

I 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…

Do you realize how much computing power is behind google search?

Re: Inside OpenAI

#12

Post by doctorpangloss »

freddealmeida wrote: post #2

I 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…

> how it can open AI to the world unless it can share rather valuable data sets

I think the spectacularly publishable performance from industry comes entirely from these massive datasets.

AlphaGo needed way more energy and data than a person did to perform as well as it did. To a set of pedantic but extremely well-meaning researchers, that could be interpreted as a huge failure.

Clearly whatever it's doing isn't the kind of intelligence that people have, since people don't need megawatts of power and 30 million game sets. But that's what big companies have that academic departments don't.

Journals publish both approaches though, and we all win from great discoveries.

Re: Inside OpenAI

#13

Post by argonaut »

maaku wrote: post #10
AndrewKemendo wrote: post #4

Earlier 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…

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. Th…

You can say that. Someone working on AGI != they have a good pathway to AGI. And anyone telling you they have a good pathway to AGI is being ridiculously and naively over-optimistic (recall that back in the 1960s people thought they had a pathway to AGI - repeat this every other decade).

None of those projects have yet shown any real progress towards AGI. A roadmap and "comprehensive architecture" are just plans and conjectures, not results. The AGI conference is also still fairly niche.

EDIT: Agreed with below. I also want to clarify that I'm not saying AGI is unworthy of research. It's just total early stages right now. Be aware that progress is incremental, and maintaining momentum (and research funding) is predicated on delivering tangible results and tools incrementally.

Re: Inside OpenAI

#14

Post by vhold »

doctorpangloss wrote: post #12
freddealmeida wrote: post #2

I 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…

> how it can open AI to the world unless it can share rather valuable data sets I think the spectacularly publishable performance from industry comes entirely from these massive datasets. AlphaGo needed way more energy and data than a person did to perform as well as it did. To a set of pedantic but extremely well-meaning researchers, that could be interpreted as a huge failure. Clearly whatever it's doing isn't the…

I think you're coming it at it from the perspective that making Lee Sedol was free? Imagine how many calories, all the fuel used to create those calories, his own direct transportation footprint, the time and money spent across creating him and his entire life. AlphaGo might not be relatively that inefficient.

Re: Inside OpenAI

#15

Post by mlinksva »

> OpenAI is not a charity.

https://backchannel.com/how-elon-musk-and-y-combinator-plan-... includes quote from Musk:

> And as a result of a number of conversations, we came to the conclusion that having a 501c3, a non-profit, with no obligation to maximize profitability, would probably be a good thing to do.

A 501c3 is a charity. Is "not a charity" inaccurate, or did OpenAI decide on some other organizational form, perhaps a trade association?

Re: Inside OpenAI

#16

Post by studentrob »

argonaut wrote: post #13
maaku wrote: post #10

Earlier quoted context omitted.

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. Th…

You can say that. Someone working on AGI != they have a good pathway to AGI. And anyone telling you they have a good pathway to AGI is being ridiculously and naively over-optimistic (recall that back in the 1960s people thought they had a pathway to AGI - repeat this every other decade). None of those projects have yet shown any real progress towards AGI. A roadmap and "comprehensive architecture" are just plans and…

Yup. There are also organizations who meet and research about contacting aliens. Doing research is not evidence of validity or progress.

One thing to note though is these efforts are often put forth by some hard working folks and the product can be something great.

For example, "Thinking Machines" [1] [2], founded in 1983 in Cambridge and defunct in 1994. The folks who spent effort there would later take their knowledge of parallel programming and built a tool called An Initio as a successor company. The tool was way ahead of its time. It'd maximize resource usage on a machine in parallel without much technical knowledge needed by the developer. They made a boat load off of deploying this tool on internal datasets at many major companies for what was then called "data warehousing".

[1] https://www.technologyreview.com/s/406781/thinking-machines/

[2] https://en.wikipedia.org/wiki/Thinking_Machines_Corporation

Re: Inside OpenAI

#17

Post by studentrob »

mlinksva wrote: post #15

> OpenAI is not a charity. https://backchannel.com/how-elon-musk-and-y-combinator-plan-... includes quote from Musk: > And as a result of a number of conversations, we came to the conclusion that having a 501c3, a non-profit, with no obligation to maximize profitability, would probably be a good thing to do. A 501c3 is a charity. Is "not a charity" inaccurate, or did OpenAI decide on some other organizational form, p…

This may help: Public Charity vs. Private Foundation [1]

Generally, I think charities are understood to use most of their funds to directly support the people in need rather than spending money on administration of the charity.

By the way, non-profits are not viewed as inherently good by those within the sector,

> Charity non-profits face many of the same challenges of corporate governance which face large, publicly traded corporations. Fundamentally, the challenges arise from the "agency problem" - the fact that the management which controls the charity is necessarily different from the people who the charity is designed to benefit [2]

[1] https://www.501c3.org/public-charity-vs-private-foundation/

[2] https://en.wikipedia.org/wiki/United_States_non-profit_laws#...

Re: Inside OpenAI

#18

Post by taneq »

maaku wrote: post #11
tlb wrote: post #3

Earlier quoted context omitted.

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…

Do you realize how much computing power is behind google search?

I'd be interested in the amount of computing power per searchable web page. Sure, there's a huge amount of computing power behind Google's web services but I'd lay odds that it's much more efficient than it used to be. The internet is huge.

Re: Inside OpenAI

#19

Post by AndrewKemendo »

maaku wrote: post #10
AndrewKemendo wrote: post #4

Earlier 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…

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. Th…

Uh, I go to the same conferences - in fact I'll be at AGI 16 this year and I was at AGI 14. Ben was my research advisor for my Masters.

I stand by my statements. The community, or even a handful of researchers haven't come up with a competent path to AGI. That's indisputable.

it's not like we have no idea how to build a general intelligence, or what such an architecture might look like

Show me one, I'd love to see it.

Listen, I love everyone working on them and many are my friends; but none of the attempts today have anything near the specificity of a project management roadmap to say with any certainty that AGI is even a probable outcome. Not OpenCOG, not Numenta, not MicroPsi.

That's not a hit on any of them either. The people and areas they are working on are awesome, amazing and fundamental to research but none of them would claim that they have a solid roadmap. Even the roadmap sessions at the conferences usually go nowhere because we just don't know enough about how generalizable intelligence works yet.

Re: Inside OpenAI

#20

Post by studentrob »

AndrewKemendo wrote: post #7
studentrob wrote: post #6

Earlier quoted context omitted.

> 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] [1] http://users.dsic.upv.es/proy/anynt/

That's a huge amount of links and information.

Can you summarize?

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