And the vision of what AI was becoming was voiced much earlier by Yudkowsky, whose Singularity Institute received funding from Thiel.
If anything, they heard what a few prophets were shouting. They saw some early demos in a startup pitch. They responded and DeepMind's work soon became as public as AI research is. That is to say, most people ignored it until the Google acquisition.
https://intelligence.org/2013/01/30/we-are-now-the-machine-i...
Thiel was an early backer of SI and attendee of the Singularity Summits that ran from 2006-2012.
https://en.wikipedia.org/wiki/Singularity_Summit
Soon after that, awareness of AI and superintelligence went mainstream, and we got FHI, FLI, etc.
I don't know if Thiel backs MIRI as he did SI. Arguably, he doesn't need to. He made his money on DeepMind and helped trigger a larger movement, and other institutions with a lot more resources, like Alphabet and MSFT, carry forward the torch.
It's probably not a state-of-the-art breakthrough at this point. Who knows what OpenAI has done in the intervening two years?
Here's an example: https://www.theverge.com/2016/6/2/11837566/elon-musk-one-ai-...
Read past the fluff and the skynet. He's telling us Google scares him and makes him concerned for democracy.
Very carefully. I mean, that's not much of an argument. Lots of stuff is successfully kept secret. The US managed to keep a lid on their surveilance for decades (iirc) before the lid got blown on that, and people used to give the same argument you are in that context, too.
What's the alternative? Do you think megacorps never keep illicit things under wraps for extended periods of time?
I guess you could use it in reverse and produce an upper limit on how many people could be involved in a conspiracy if you assume that it has been secret for five years.
That said, Elon Musk gives every impression of being a massive chatterbox who can’t keep his mouth shut even when its the SEC threatening to take Tesla away from him, so I very much doubt any conspiracy involves him.
[0] https://journals.plos.org/plosone/article?id=10.1371/journal...
Ahh... I'm not so sure; see the comment by blueyes. Had it been OpenAI's goal to engage in debate and regulation for this technology, they would have been vocal about that aspect of their work already.
"Not reading OP and spouting a non-quantitative conspiracy theory" = what you did.
but you'd have no way of enforcing any treaty so that's a moot point and they would know this.
I think making people aware of the importance of the control or value loading problems is a much better use of efforts.
As far as I can tell, this is what is going on: they do not have any such thing, because GB and DM do not believe in the scaling hypothesis the way that Sutskever, Amodei and others at OA do.
GB is entirely too practical and short-term focused to dabble in such esoteric & expensive speculation, although Quoc's group occasionally surprises you. They'll dabble in something like GShard, but mostly because they expect to be likely to be able to deploy it or something like it to production in Google Translate.
DM (particularly Hassabis, I'm not sure about Legg's current views) believes that AGI will require effectively replicating the human brain module by module, and that while these modules will be extremely large and expensive by contemporary standards, they still need to be invented and finetuned piece by piece, with little risk or surprise until the final assembly. That is how you get DM contraptions like Agent57 which are throwing the kitchen sink at the wall to see what sticks, and why they place such emphasis on neuroscience as inspiration and cross-fertilization. When someone seems to have come up with a scalable architecture for a problem, like AlphaZero or AlphaStar, they are willing to pour on the gas to make it scale, but otherwise, incremental refinement on ALE and then DMLab is the game plan. Because they have locked up so much talent and have so much proprietary code and believe all of that is a major moat to any competitor trying to replicate the complicated brain, they are fairly easygoing.
OA, lacking anything like DM's long-term funding from Google or its enormous headcount, is making a startup-like bet that they know the secret: the scaling hypothesis is true and very simple DRL algorithms like PPO on top of large simple architectures like RNNs or Transformers can emerge and meta-learn their way to powerful capabilities, enabling further funding for still more compute & scaling, in a virtuous cycle. And if OA is wrong to trust in the God of Straight Lines On Graphs, well, they never could compete with DM directly using DM's favored approach, and were always going to be an also-ran footnote.
While all of this hypothetically can be replicated relatively easily (never underestimate the amount of tweaking and special sauce it takes) by competitors if they wished (the necessary amounts of compute budgets are still trivial in terms of Big Science or other investments like AlphaGo or AlphaStar or Waymo, after all), said competitors are too hidebound and deeply philosophically wrong to ever admit fault and try to overtake OA until it's too late. This might seem absurd, but look at the repeated criticism of OA every time they release a new example of the scaling hypothesis, from GPT-1 to Dactyl to OA5 to GPT-2 to iGPT to GPT-3... (When faced with the choice between having to admit all their fancy hard work is a dead-end, swallow the bitter lesson, and start budgeting tens of millions of compute, or between writing a tweet explaining how, "actually, GPT-3 shows that scaling is a dead end and it's just imitation intelligence" - most people will get busy on the tweet!)