I know when the Singularity will occur

This post seems more appropriate for the Discussion section.

This seems overconfident and somewhat misinformed to me.

First of all, it seems reasonable to wager that Google servers already do a lot of work when traffic is light: log aggregation, data mining, etc.

Secondly, you make the assumption that the AI team would run the AI on Google's "empty space". That implies a huge number of unspoken assumptions. I'd expect a Google AI team to have a (huge) allocation of resources that they utilize at all times.

Thirdly, it's quite a leap to jump from "there's slightly less server load at these hours" to "therefore an AI would go super-intelligent in these hours". To make such a statement at your level of expressed confidence (with little to no support) strikes me as brazen and arrogant.

Finally, I don't see how it decreases risk of a foom. If you already believed that a small AI could foom given a large portion of the world's resources, then it seems like an AI that starts out with massive computing power should foom even faster.

(The "fooming" of a brute-force AI with a huge portion of the world's resources involves sharply reducing resource usage while maintaining or expanding resource control.)

If you're already afraid of small kludge AIs, shouldn't you be even more afraid of large kludge AIs? If you believe that small-AI is both possible and dangerous, then surely you should be even more afraid of large-AI searching for small-AI with a sizable portion of the world's resources already in hand. It seems to me like an AI with all of Google's servers available is likely to find the small-AI faster than a team of human researchers: it already has extraordinary computing power, and it's likely to have insights that humans are incapable of.

If that's the case, then a monolithic Google AI is bad news.

(Disclosure: I write software at Google.)

Well, it's more plausible than the bulk of speculations you'd see, I'll give you that, but it is still rather improbable. No, they do not have 2 executives out of 4 smartest; that's highly implausible, and if you include Thiel you ought to include dozens and dozens others. Nor do they have a particularly high fraction of world's most intelligent people.

What I envision is that Google is uniquely posed to create an AI that primarily relies on human knowledge, being capable of seemingly superhuman achievement while only requiring subhuman general problem solving capacity. I.e. the very stereotype of uncreative artificial intelligence. Watson on steroids; an automatic plagiarist of ideas.

More interesting (but also less likely) possibilities ought to benefit less from the availability of utterly massive dataset. After all, we humans grow up with a much smaller data set.

Well, first, let's just admit this: The race to win the Singularity is over, and Google has won.

I checked with Google trends. It seems as though they may yet face some competition. Also, 15 years of real time is quite a bit of internet time. Previously it looked as though Microsoft had won - and IBM had won.

If I had to take a gamble on what organization was best primed to cause the Singularity, I'd probably also pick Google, mainly because they seem to be gathering the world's best machine learning researchers together. They've already hired Geoffrey Hinton from Toronto and Andrew Ng from Stanford. Both of these researchers are considered among the foremost minds in machine learning, and both have been working on Deep Neural Networks that have shown a lot of promise with the pattern recognition problems like object recognition and speech recognition. Last I heard Google managed to improve the performance of their speech recognition software by something like 20% by switching to such neural nets.

It's my own opinion that machine learning is the key to AGI, because any general intelligence needs to be able to learn about things it hasn't been programmed to know already. That adaptability, the ability to change parameters or code to adapt to new information is, I think an essential element that separates a mere Optimization Algorithm, from something capable of developing General Intelligence. Also, this is just a personal intuition, but I think that being able to reason effectively about the world requires being able to semantically represent things like objects and concepts, which is something that artificial neural networks can hypothetically do, while things like expert systems tend to just shuffle around symbols syntactically without really understanding what they are.

The bottom up approach is also likely to be easier to reach superhuman intelligence levels sooner than some top down approach to A.I., as all we have to do is scale up artificial neural networks that copy the human brain's architecture, whereas it seems like a top down approach will have to come up with a lot of new math before they can really make progress there. But then, I'm a connectionist, so I'm kinda biased.

Perhaps one interesting thought is that if the first superintelligent A.I. is actually an artificial neural network, it'll probably be more "human-like" or at least similar to an evolved intelligence, than if it was created by top-down A.I. Not saying that that gets rid of the Orthogonality Thesis, but it might mean that an artificial neural network based A.I. might be more likely to land in the part of the mindspace that humans tend to fall into, because of similar architectures of sentience. Maybe.

I do believe "Google wins" is a likely scenario—more likely than "X wins" for any other single value of X.

This is something of a non-sequitur. "Google wins" might be more likely than any other "X wins" with an X than we can name today, and still very unlikely in absolute terms. Like a lottery with a thousand tickets where only one person has bought ten of them and all the others go to one person each. Let us be precise: conditional of there being a singularity before 2040, what is your probability that Google initiates it?

I disagree with your premises. The hard part of AI is the algorithm itself. Google's supercomputers would be an advantage if you had an AI already and wanted it to take off as fast as possible. Maybe an AI running on a Google computer would take off in a day instead of a month. Not to mention how fast computers will be in 30 years or what the distribution of computing power will then be. 30 years ago Google wasn't even around and computing power has grown enormously since then.

The amount of data available is an even smaller advantage. I don't really think it's an advantage at all. The internet has virtually unlimited data if you need it, and there is no reason an AI wouldn't be just as smart working with a very limited data set or just on some optimization problems with no external data at all.

Google doesn't make up the majority of AI research. A good portion sure, but not the majority. Further I don't think the approaches they are investing in are likely to lead to AGI.

Yudkowsky said it first:

Google is your friend. Trust in Google. Google is your Extended Long-Term Memory. Google is the Source of All Knowledge. Have you accepted Google into your heart?

...if we suppose that sometime in the next 30 years, an artificial intelligence will begin bootstrapping its own code and explode into a super-intelligence, I can give you 2.3 bits of further information on when the Singularity will occur.

Yes. If we begin by supposing random things out of the blue, there's no end to the cool conclusions we can draw !

What is the point of this post?

The race to win the Singularity is over, and Google has won

Counter-argument: NSA has a track record of having Math advanced decades beyond public. Also, quantum computing should be within reach in 30 years... might be NSA as well, since it'd make a perfect crypto cracker.