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Machine intelligence, part 2

blog.samaltman.com

81–90 of 157 posts

Re: Machine intelligence, part 2

#81
post #50

Earlier quoted context omitted.

A lot of experts also deny dangers coming from global warming and other invasions in complex systems we don't fully understand. Scientists in the 1940s also downplayed the danger of the atomic bomb. It's easy to brush away a hypothetical danger with arguments that resources might be wasted or that people in charge might embarrass themselves if their assumptions turn out to be wrong, or that research might suffer due…

By the time the atomic bomb was truly imminent (in the sense of it being within the reach of massive dedicated investment by the most powerful nations on Earth), scientists knew very well of the dangers [1]. As for global warming. No expert denies global warming, and you'll be hard pressed to find many that deny anthropic global warming [2]. This has been the case for many decades. I am not an AI expert, but from wha…

Fair enough, but I wouldn't exclude the possibility that AI experts are biased for at least three reasons, namely (1) that they believe in some sort of sanctity of the human mind (like many people do), (2) that they don't want to be regulated and (3) that they don't want to raise overblown expectations. There are definitely historical examples in which the majority of experts was wrong.

I also find it incredibly difficult to tell what is missing about an algorithm. Perhaps multiple breakthroughs are necessary, perhaps just one (there is no good reason to believe that an algorithm that yields AGI can't be considerably simpler than what happens in the human brain). Initially, nobody thought that search could be done in O(log n) and similarly not many researchers expected neural networks to perform useful tasks until back-propagation was invented and demonstrated.

Re: Machine intelligence, part 2

#82

Earlier quoted context omitted.

> On the other hand you have (essentially) the entire mainstream academic AI/ML community, who are mainly concerned that the hype is so intense it might lead to another AI winter This doesn't seem true. E.g. the signatories on the Future of Life Institute's recent open letter about AI progress and safety include: * Stuart Russell & Peter Norvig, co-authors of the #1 AI textbook * Tom Dietterich, AAAI President * Eric…

That letter is not about "superhuman machine intelligence", it is about "ensuring that AI remains robust and beneficial." Among the threats cited are: autonomous vehicles, machines that need to make ethical decisions, autonomous weapons, surveillance, and issues of verification, validity, and control. Words like "singularity", "superhuman", and "AGI" do not appear.

Superintelligence and intelligence explosion are mentioned as valuable things to investigate.

Re: Machine intelligence, part 2

#83
Sam Altman's (4) "provide lots of funding for R+D for groups that comply with all of this, especially for groups doing safety research" is especially important. Regulation is a mixed bag, but safety research is pure upside and research surrounding AGI safety has been severely under-funded in the past.

The Future of Life Institute has a grants program going on the subject, allocating a $10M donation from Elon Musk. Their abstract submission deadline was yesterday. I wonder how much good safety research they have asking for funds, as compared to their budget?

Re: Machine intelligence, part 2

#84
post #10

On the one hand we have lay people (including Altman and Musk) who are warning that AI is progressing too fast. On the other hand you have (essentially) the entire mainstream academic AI/ML community, who are mainly concerned that the hype is so intense it might lead to another AI winter[1]. The crux of the problem is that AI experts largely do not see meaningful progress on any axis that makes an AI doomsday scenari…

We have to start with a discussion about how this progress towards doomsday AI should be measured, and then formulate policy to directly address those scenarios. As long as Altman et al are extrapolating on axes I (for one) don't understand, I honestly think this conversation is unlikely to be productive. Fully agree with this. So far, all of this activism around the AI threat has amounted to "guys we really need to…

If you're looking to support AI safety, the Machine Intelligence Research Institute is researching it.

Re: Machine intelligence, part 2

#85
post #45

If you would have asked people in the 70s if the most influential software of the coming decades would be written by lone wolves in their garages or a group of very smart people with a lot of resources, they would have bet on the latter. But the smart money turned out to be on Gates, Jobs, Wozniak and countless others. The idea of regulating AGI/SMI is based on the premise that it will be developed primarily by peopl…

I totally agree with this guy. Regulation is futile, you can't regulate at a micro level in all the parts of the world. If you can't properly regulate drug trafficking in Santa Monica how do you plan to regulate a couple of scientists hidden in the soviet tundra? IMHO it's inevitable our encounter with an AI, even if that AI is a superhuman with augmented capabilities, or derives from an arms race (like the Manhattan…

If it's smart enough to be a threat, I wouldn't be surprised if it's smart enough to avoid getting EMPed.

Re: Machine intelligence, part 2

#87
post #16

"The US government, and all other governments, should regulate the development of SMI" This has basically the highest insanity * prominence of speaker product I've ever seen. The same geniuses who want to ban encryption and can't manage to get a CRUD website up and running without a 8-figure budget will regulate the existence of algorithms (i.e., math) routinely generated by groups of Of course, people will be glad t…

The US Government regulates all sorts of things that keep you safe - from pollution of your water supply through to seatbelts. It's not perfect, and it often fails at regulation. But your post doesn't give any help to understanding when it succeeds and when it fails.

But those are regulating current products or services. This is calling for regulation now of RESEARCH in a specific field.

Re: Machine intelligence, part 2

#88
post #33

I have a hard time taking these kinds of posts seriously. Maybe I'm not up to date on AI research, but I draw a distinction between a conscious program and strong AI. So what, a program can identify the type of clothing specific person is wearing from a video using cutting-edge machine learning and computer vision. So what, a program can interpret the movie I'm talking about just from hearing me describe a scene in i…

> So what, a program can identify the type of clothing specific person is wearing from a video using cutting-edge machine learning and computer vision. So what, a program can interpret the movie I'm talking about just from hearing me describe a scene in it. So what, a program can beat the human champion in Jeopardy. Are those programs super intelligent? All these programs are doing great at recognizing things. Neural…

As others have indicated, AI planning is a significant field, critical to self-driving cars, space probes, etc. Markov Decision Processes is a great sub-field.

> A good "cuccoo field" for that would be video games, where such planning systems would be a holy grail.

The game developer conventional wisdom for some time has been that very good AI is not worth building [1] because it is not very entertaining. I believe that's by far the dominant opinion. But, there are some interesting ways that AI is being explored in ways other than strong AI opponents [2].

[1] http://www.rockpapershotgun.com/2015/02/13/electric-dreams-p...

[2] http://web.eecs.umich.edu/~soar/sitemaker/workshop/27/vanLen...

Re: Machine intelligence, part 2

#90
post #51
post #10

On the one hand we have lay people (including Altman and Musk) who are warning that AI is progressing too fast. On the other hand you have (essentially) the entire mainstream academic AI/ML community, who are mainly concerned that the hype is so intense it might lead to another AI winter[1]. The crux of the problem is that AI experts largely do not see meaningful progress on any axis that makes an AI doomsday scenari…

I think you make a lot of good points. >We have to start with a discussion about how this progress towards doomsday AI should be measured, and then formulate policy directly those scenarios Here is my proposal. Since the whole of AI is a rather complicated and messy business let us just focus on a small part. That is, let's just talk about linear regression and simple decision making schemes based on estimated parame…

Google published a paper which I think is relevant to the topic, Machine Learning: The High Interest Credit Card of Technical Debt (2014).

http://research.google.com/pubs/pub43146.html

The conclusion seems to be that even this level of machine learning decreases controllability substantially. "We note that it is remarkably easy to incur massive ongoing maintenance costs at the system level when applying machine learning."

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