A Roadmap Towards Machine Intelligence
arxiv.org
arxiv.org
http://paultyma.blogspot.fr/2015/10/how-artificial-intellige...
Most people live in appalling, inhuman conditions:
$100 monthly income puts a person in the top 52.40% earners worldwide. [0] $300 monthly income puts a person in the top 28.35% earners worldwide. [0]
Human intelligence is obviously suboptimal for solving global problems, perhaps AI will do better.
That's misleading without considering numerous other variables - cost of things? It seems to me to be the kind of statement aimed at deceitfully triggering emotions, by the likes of charities. Charities are like police - there for good reason, but along with the good intentions they have a slightly seedy side. Of the countries I've lived in, the one where I was paid least had the highest standard of living.
Calculation methodology is available on the linked page:
"For currency conversion we use Purchasing Power Parity Dollars (PPP$) in order to take into account the difference in cost of living between countries; PPP$ are also less susceptible to short term fluctuations."
I've submitted it for HN discussion: https://news.ycombinator.com/item?id=10637207
On a long enough timeline, we're probably screwed by Fermi's Great Filter regardless, but a self-improving machine learning singularity can certainly accelerate the process!
I think this is affirmed by the fact that most state-of-the-art AI depends primarily on massive volumes of data rather than clever algorithms. Massive datasets are inherently concentrated in the hands of the few and powerful, so it seems unlikely that a rogue actor could acquire suitable data.
And yes, it is debatable, but as Tegmark puts it: relying on luck is probably not a good strategy.
It can't be about microprocessors, since we've had those for decades and don't have murderous AI yet.
The point is to suggest something that nobody would do by accident, but almost anyone can do intentionally, and nobody can stop others from doing. It's a thought experiment: suppose that taking some common everyday substance, and using it with a common appliance many people have access to, would destroy the world.
Right now, a very small handful of people have the ability to existentially threaten humanity. Fortunately, those people seem moderately unlikely to do so, and the process for becoming one of those people selects at least somewhat against the type of craziness that would hit the button just to see what happens, or because they genuinely want the world to end.
Out of seven billion people, based on existing examples of human behavior, it seems exceedingly likely that there exist people who would intentionally choose to to destroy the world.
[1] I certainly think it will become possible, but the timeframe is indefinite. If we get really lucky and breakthrough after breakthrough is achieved, it could be within 10 years. But it could be 20 years, it could be 100 years.
"I think we should be very careful about artificial intelligence. If I were to guess like what our biggest existential threat is, it's probably that. So we need to be very careful with the artificial intelligence. Increasingly scientists think there should be some regulatory oversight maybe at the national and international level, just to make sure that we don't do something very foolish. With artificial intelligence we are summoning the demon. In all those stories where there's the guy with the pentagram and the holy water, it's like yeah he's sure he can control the demon. Didn't work out."
The classes of algorithms that are meant to directly interact with people in a way that appears authentically human must obviously be highly regulated, and I certainly agree that these kinds of regulations should be on par with international nuclear oversight bodies.
It is always important to give end users the option to figure out for themselves how the algorithms that they interact with actually function. In order to encourage this kind of thing, I have been working on an online, distributed operating system concept for the past several years, and one of the apps is a simple, "Hello World" kind of an AI that goes by the name, Bertie.
I am working on making the underlying system code (which is mostly JavaScript) completely editable by end users. They will be able to test out their edits in an application window inside of the web page, and will be able to share their changes with each other over the distributed, web-based filesystem that I am actively developing.
If you are running Chrome, you can try out the OS by going to https://nacl-pg.appspot.com/. To see the AI app, just click on the Applications folder, and then click on Bertie's face. Alternatively, if you are feeling lazy, just click on the following link and the Bertie app will automatically open: https://nacl-pg.appspot.com/desk?open=Bertie.
1. Introduction
2. Desiderata for an intelligent machine
2.1 Ability to communicate
2.2 Ability to learn
3. A simulated ecosystem to educate communication-based intelligent machines
3.1 High-level description of the ecosystem (Agents, Interface channels, Reward, Incremental structure, Time off for exploration, Evaluation)
3.2 Examples from early stages of the simulation (Preliminaries and notation, The Learner learns to issue Environment commands, Associating language to actions, Learning to generalize, Understanding higher-level orders, Interactive communication, Algorithmic knowledge)
3.3 Interacting with the trained intelligent machine
4. Towards the development of intelligent machines
4.1 Types of learning
4.2 Long-term memory and compositional learning skills
4.3 Computational properties of intelligent machines
5. Related ideas
6. Conclusion
I'm thinking the winner might not be the company who makes huge progress towards MI, it could be the one who provides the ecosystem. For example, in the trend of Siri-type chatbots, Slack is very well positioned to reap most of the benefits even without doing much research in AI, because they could get a commission on the platform usage.
Wonder what the other button does...
On the bright side, they bucked the trend and cited Terry Winograd's research from the 1970s instead of pretending they made this idea all up by themselves.