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Inside OpenAI

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21–26 of 26 posts

Re: Inside OpenAI

#21
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…

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…

> 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.

The keyword there is competent. You're making a subjective evaluation. Given your CV you must surely be aware that Goertzel has a 1,000 page book (two volumes, actually) laying out in great detail his roadmap to human-level intelligence. The leaders of other major projects in this space have their own ideas which they talk freely about at the AGI conferences, and are written down to varying degrees.

Re: Inside OpenAI

#22
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…

"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

And even with all that investment Bing is not even working that well. It is good, but not on a Google level.

Re: Inside OpenAI

#23

If it is time we, human being should imprint some logic laws into all AI projects which are intent to create unsupervised AI?

That's about as practical as making a computer capable of everything except intellectual property infringement.

Re: Inside OpenAI

#24
post #21

Earlier quoted context omitted.

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…

> 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. The keyword there is competent. You're making a subjective evaluation. Given your CV you must surely be aware that Goertzel has a 1,000 page book (two volumes, actually) laying out in great detail his roadmap to human-level intelligence. The leaders of other major projects in…

> book... roadmap... ideas

Notice a pattern?

Meanwhile, in deep learning (and FWIW I don't think any deep learning researchers are under the illusion deep learning provides a path to AGI), there are:

working systems that outperform humans at narrow visual tasks (image classification, segmentation, etc.), a working Go bot, early prototype systems that caption images, the list goes on and on.

Re: Inside OpenAI

#25

Earlier quoted context omitted.

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?

Can you summarize?

Not really - it's worth reading the whole thing.

Best I can do is state that the test basically has multiple different environments with different rules that are independent of how capable or fast they are.

Re: Inside OpenAI

#26
post #14

Earlier quoted context omitted.

> 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.

Let's do some Math!

Assuming 2000 Calories per day a megawatt is about 240.000 calories per second we can do some silly calculations. Assuming AlphaGo consumed one megawatt for 1 whole day then it consumed about 20,736,000,000. This is probably low. This is enough Calories for a human for 28,405 years. If we split the Calories accross 500 that accounts for 57 years apiece.

I had no clue where this would turn out when I start. If we presume AlphaGo can run on a 1,000 Watt machine we can still divide all these numbers by 1,000 and they still hold, so 28.4 years of human calories.

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