Neural networks modify their behaviour by changing their data. Any non-trivial program does that. Some GOFAI programs (e.g. Eurisko) could modify their instructions, not just their data.
Searle's argument is confusing, but how the program in the Chinese Room is implemented doesn't matter. His argument is solely against strong AI. He claims that the Chinese Room (or a suitably programmed computer) cannot be conscious of understanding Chinese in the same way that people can. He doesn't deny that a suitably programmed computer could, in principle, behave as if it understood Chinese, even if it wasn't conscious of anything at all.
However, the machine translation program mentioned in the article behaves as if it understands Chinese only within the limited context of the translation. It wouldn't be able to answer wider questions about things mentioned in an article it had just translated.
Previously it was thought that machine translation systems would have to understand the text they were translating in the way a person does, to produce a useful translation, but that's now shown not to be true. Without hindsight, it's a surprising result, but less surprising when you think of translation as pattern recognition, and think of how a person might go about translating text on a highly technical subject they don't understand.
It's a completely meaningless and plain stupid argument though. There's no reason to believe human consciousness is special and that "understanding" Chinese is at all related to it. One can speculate that the perception of consciousness is simply the product of some form of introspective sensory system and internally-directed actions, of which the former ironically clearly doesn't quite work when it comes to language (or it wouldn't be as much of a reverse-engineering exercise). Nothing really stops you from throwing that into your system and having it consciously understand chinese, assuming it already maintains state.
You can however make a fairly solid argument that a CNN alone (as used in image/object recognition) is fundamentally incapable of dealing with images (but maybe not language), on the assumption that it can be faithfully described as Satan's boolean satisfiability problem, then by virtue of complexity theory it can only be solved in constant time with a sufficiently massive lookup table (which there wouldn't be enough atoms in the universe to store). Microsoft are actually dealing with this in their system by repeatedly applying the network and revisioning the text.
Regardless though, accurate NLP is going to come down to managing to codify how humans deals with objects, concepts and actions, because that's what the languages encode; GOFAI wasn't really too off (and the original effort was doomed from the start by the state of hardware and linguistics). Consider how distinguishing objects as masculine-feminine-neuter and animate-inanimate(-human) is universal (but doesn't necessarily affect the grammar), and that the latter is based purely on how complex/incomprehensible the behaviour of something is (unlike grammatical gender which seems to be fairly arbitrary). Of course that's arguable, but you can see animacy appear in english word choices (unrelated to anthromorphic metaphors) and in how "animate" objects tend to be referred to as having intent. You could try and figure all this out the wrong way around using statistical brute force and copious amounts of text, but that's pretty roundabout isn't it?
(Also, the assumption that an objects animacy is determined by predictability offers a pretty concise explanation of why the idea of human consciousness being produced by simpl(er) interacting systems often fails to compute so spectacularily, why most programmers appear to be immune to that, and also why the illusion that image recognition CNNs perform their intended function is so strong (regardless of how useful they are, the failures make it blatant that they're only looking at texture and low-level features, and are extremely sensitive to noise, which is the opposite of what anyone intended))
I agree, the argument seems to come down to saying that human consciousness can't be replicated because human consciousness stems from a "soul" (a non-physical and undetectable element of someone that's at the root of their consciousness).
The amount of attention this argument has received has made me wonder whether the "rigor" used by philosophy departments is mostly just a way to obfuscate bad arguments.
That's not his argument at all. His argument is that just because you can do some task doesn't mean you "understand" it.
You don't need some fancy philosophy and complex thought experiments to see what he means. Just look at how people learn math. You can do calculations by memorizing algebraic rules, but that's not the same as understanding why those rules exist and what they mean. Even though you will calculate answers correctly in both cases, we all know there is a qualitative difference between them.
Back to Searle. His argument is that everything computers do is analogous to rote memorization and that transition to understanding requires something computers don't have.
Whether you buy his argument, two things are clear. First, there is a difference between just producing results and understanding the process. We all experienced this difference. It's all theoretical as long as you stick to simple tests (like multiple-choice exams), but becomes relevant when you suddenly expand the context (like requiring the student to prove some theorem instead of doing a calculation). Second, we also know that for humans this difference isn't just quantitative. Memorizing more algebraic rules and training in their application will not automatically result in students gaining understanding of mathematical principles.
Thanks for rebutting Chathamization's gross misrepresentation of Searle's argument.
> It's all theoretical as long as you stick to simple tests (like multiple-choice exams), but becomes relevant when you suddenly expand the context (like requiring the student to prove some theorem instead of doing a calculation).
Not even expanding the context changes the situation. The proof of a theorem can be memorized without any understanding just as easily as algebraic rules.
> Second, we also know that for humans this difference isn't just quantitative. Memorizing more algebraic rules and training in their application will not automatically result in students gaining understanding of mathematical principles.
This is correct and the same principle applies not just to humans but to computers too (which was the point of Searle's argument). No amount of computation is going to make a computer aware or understand the meaning of the symbols. Ultimately "meaning" is our perceptual awareness of existence but that is a long proof for another day.
Any finite computational system can be implemented as a lookup table in the manner that Searle suggests. But that's not essential to the argument. You can imagine that the man in the room is following instructions for simulating a (finite approximation of) a Turing machine, or any other computational device that you like.
This is what I have found. I started indie game dev a back in 2009, and I'm finally to the point where I'm making a very comfortable living, but by no means a millionaire. However, having a small company with some fellow devs is now in the realm of possibility, which is a long-time dream of mine.
Edit:
My games are mostly mobile. I am really excited about the figures he posted for Steam. I just got one of my games greenlit on Steam (SimpleRockets) and I hope I can sustain further development on it.
You might like the book "Nothing to Envy: Ordinary Lives in North Korea." There's quite a few jaw dropping stories from people who defected from NK. It's such a mysterious country, I am completely fascinated by it.
Thanks for the suggestion. I will definitely check it out. Although, I have trouble reading those types of books (and articles) because they tend to be a bittersweet experience. On the one hand I feel like it is sort of like a sin to be willfully ignorant of the terrible things happening in places like NK, but it is also incredibly depressing learning about these things and being so powerless. For some reason the brutality women face in these places seems to upset me the most. A few weeks ago I read a very descriptive article on witch hunting in Papua New Guinea and thinking about it still keeps me up at night.
Did you learn of the PNG situation from the article that was submitted to HN?
Did you know that since that article was shared here, the PNG govt is trying to push forward very tough laws to clamp down on the nastiness that goes on there. They're bringing back the death penalty, and it will now also apply to rape, violent robbery, etc.
> The prime minister also announced that the government would repeal the controversial 1971 Sorcery Act, which acknowledges the accusation of sorcery as a plausible defence in murder cases
> Prime Minister Peter O'Neill said violent crimes were becoming too frequent and that "draconian" measures were required.
> "There will be maximum penalties that have never been seen before in this country"
> Parliament last week resurrected the long-dormant death penalty and approved five methods of execution: hanging, firing squad, electrocution, lethal injection and asphyxiation.
I'm reading this right now, and I'll second the vote. One of the more Orwellian/absurd fun-facts I've come across: The two biggest department stores in the DPRK are called Department Store No. 1 and Department Store No. 2. (I'm sure there's some clever joke about marketing/branding in there) Like the OP said - it's mysterious and completely fascinating.
That book's good - but it's about people fleeing the northern part of the country, one of the industrial centers, neither at the border or near the capital in the south. It's quite a different situation there and probably far more representative of the country as a whole.
Another good book on North Korea is B.R. Myers' "The Cleanest Race." While it's not focused on history or defectors specifically, it does offer unique insight on the formation of the North Korean state and the rationale behind its actions.
I like the question. Until and unless the person who chose it wishes to answer, here's my attempt at a more-than-complete answer.
I guess orange may be chosen as a rather eye-catching color. A reddish orange may be chosen to be a bit more tasteful or distinctive.
The choice of RGB component values may originate in an older practice in web design called web-safe colors (http://en.wikipedia.org/wiki/Web_colors#Web-safe_colors). It uses the observation that 33 hexadecimal (let's write 0x33) evenly divides the range of an HTML red-green-blue color component: 0x00, 0x33, 0x66, 0x99, 0xCC, 0xFF. Choosing each of the three color components from among these six values yielded 6^3 = 216 colors, a palette that would fit into a low-end graphics adapter's table of 256 colors with room left over for system-defined colors.
Those who have studied Mersenne primes may recall that it is sufficient to observe that 8 is a composite number in order to prove that 0xFF = 0x100 - 1 = 2^8 - 1 is a composite number. And we compute that 2^8 - 1 = 255 which ends in 5, so it's obviously divisible by 5, the quotient being 51 = 0x33.
It wasn't covered in the blog post, but it is also interesting how slowly WordPress performed compared to DotNetNuke. I never felt there was a performance problem with my web site until I moved from DNN to WP. I suppose it could also be GoDaddy's MySQL servers vs their SQL Server servers. Maybe their MySQL servers are bogged down.
I've used it on a few projects. I have never used NHibernate, so I can't really compare them, but I really like EF. I don't have a great deal of SQL experience, so I'm much better at writing queries with LINQ methods and prefer it over SQL. It's great having strongly typed entities and the intellisense is awesome, but that's probably true with any ORM.
