Talk:Moravec's paradox

message: Why is this called a "paradox?"  Wikipedia defines paradox as: "an apparently true statement or group of statements that leads to a contradiction or a situation which defies intuition."  Where's the contradiction or nonintuitiveness?  Moravec's statement strikes me as simply an empirical claim, which may be true or false.  How is this any different from saying, "Men are at their worst trying to do the things most natural to women," or similar for birds / fish, cops / robbers, Cowboys / Indians, etc.?  Are those paradoxes too?
Also -- does this term "Moravec's paradox" exist anywhere other than on wikipedia?  Google shows only 12 links. —Preceding unsigned comment added by 128.30.31.167 (talk • contribs) 18:28, 20 August 2007
:It's paradoxical by the second part of the definition you posted; it defies intuition. Simply, things we find hard, computers find easy, and vice versa. It's too general to be an empirical truth. I get 7,750 Google hits, and have seen/studied a handful of papers by Rodney Brooks which mention the subject. It's definitely encyclopaedic and meets WP:NOT. --BlueNovember (talk • contribs) 18:33, 12 June 2009 (UTC)
thread_title: Why?

message: This article should not be categorized as philosophy and is not in the scope of Wikiproject:Philosophy.  This is, as it states, a principle in robotics and artificial intelligence. It should be categorized only as artificial intelligence or robotics. (It's only relation to philosophy would be as an example in embodied philosophy or embodiment. This merits a "See Also", not a category.)  ---- CharlesGillingham 07:24, 31 August 2007 (UTC)
replies: text: Well that's a pretty narrow view there. I think it qualifies on several counts Philosophy of mind, Philosophy of science, and logic. I think at least one applies. Fortunately, the field options we have mean we don't have to choose. Greg Bard 13:23, 12 September 2007 (UTC)
thread_title:  Not a philosophical article 

message: Most classes in robotics or artificial intelligence mention some version of this principle (at least the ones I took). It is part of the motivation for "Nouvelle AI" (a school of AI research named by Rodney Brooks and also practiced by Hans Moravec and most people on the robotics side of things). More research will show this. ---- CharlesGillingham 07:24, 31 August 2007 (UTC)
replies: text: I've found a few: Minsky, McCorduck, etc. ---- CharlesGillingham (talk) 14:54, 4 June 2008 (UTC)
thread_title:  More references needed 

message: I think the theory of evolution can be the explanation of everything by this standard. I don't think it is relevant, but hey, I'm a creationist, so I'll just shut my mouth and know my place in Wikipedia.  —Preceding unsigned comment added by 203.97.104.99 (talk) 07:09, 2 November 2008 (UTC)
replies: text: I'd actually be very interested to hear a creationist explanation. I edited the section so it reads "one explanation of the paradox is...", rather than "the explanation of the paradox is...". The paradox itself is an empirical fact, a discovery made by researchers. However, the explanation of it is not an empirical fact. Absolute proof would require more evidence.---- CharlesGillingham (talk) 23:27, 2 November 2008 (UTC)
thread_title:  The explanation of the paradox is the theory of evolution? 

message: For those who are so old that they cannot remember, or so young that it was before their time: Minsky is an exponent of the AI hype. AI means "artificial intelligence", and it was a hype similar than .com or the credit crunch. The AI hype has wasted lots of money and generations of computer scientists by trying to build intelligent computers. From the very beginning of computer science in the 1950ies, AI was a very high priority. And it has never worked.
I've read Minsky's book "The Society of Mind".  The whole book is a loose collection of ideas that have proven not to work in real life. In this respect, Minsky's book is similar to Hofstadter's "Fluid Concepts and Creative Analogies". These are the kind of book of which you make your kids a present for the winter holidays because of the nice pictures in it. 
In this book, Minsky is trying to make the case in favor of AI. This notion of "paradox" is quite far fetched from the spirit of this book, IMHO. (Maybe paradox to indicate a lack of insight?)
A more credible discussion of this phenomenon can be found in Roger Penrose's "The emporor's new mind" and later books. In this context, it might be called a physical phenomenon rather than a (mathematical) paradox.  —Preceding unsigned comment added by 85.181.130.151 (talk) 21:58, 2 November 2008 (UTC)
thread_title:  Penrose 

message: Current definition stating that "uniquely human faculty of reason (conscious, intelligent, rational thought) requires very little computation" IS a complete bullshit. How something like this could be in Wikipedia? Currently we even don't know if reason is at all computable. 83.26.84.105 (talk) 22:16, 19 May 2010 (UTC)
replies: text: "Reason" in this context means step-by-step problem solving of the kind that people use when doing algebra, playing chess, or proving mathematical theorems. While not necessarily "computable" in a Godelian sense, this is still something computers can do when the problem is tractable. ---- CharlesGillingham (talk) 15:09, 18 October 2021 (UTC)
thread_title:  Wrong definition 

message: Deleted text:
:Linguist and cognitive scientist Steven Pinker considers this the most significant discovery uncovered by AI researchers. In his book The Language Instinct, he writes:
:
I think that this a valuable contribution, given Pinker's standing as one of the world's leading scientists and add more weight to the article. I agree that his quote is just restating the principle, but I don't think this minor redundancy is a problem. Plus Pinker says "the main lesson" (i.e., that this is really really important). The lede as it stands doesn't mention the importance of the idea without Pinker. 
I'd like to put it back if no one disagrees. ---- CharlesGillingham (talk) 01:37, 10 September 2015 (UTC)
thread_title:  Deleted text saved on Talk 

message: This is also known in the formulation "What's easy [for humans] is hard [for computers], and what's hard [for humans] is easy [for computers]".  For example, tasks such as adding up endless columns of long numbers are extremely tedious and error-prone for humans, but almost trivially easy for computers, while things that humans usually don't even really think much about, such as walking, language understanding, vision etc. have been extremely difficult to implement with computer programming. AnonMoos (talk) 21:18, 30 January 2020 (UTC)
replies: text: Hardly surprising when computers developed as tools to supplement humans in their work. What would be required for something to duplicate human profiencies, rather than compensate for deficiencies, probably requires going back to near first principles.  A modern Charles Babbage who is also a neuroscientist and subconscious psychologist. 185.13.50.177 (talk) 14:33, 3 March 2020 (UTC)
thread_title:  "What's easy is hard, and what's hard is easy" 

message: The article described modern computers as "trillions of times faster" than 1970s computers; this is an exaggeration. A CRAY-1, 1976-era, ran at 2 MFLOPS. A modern NVIDIA A40 card can manage a peak 32-bit throughput of about 40 TFLOPS. The ratio is only 20 million or so. Even a v3 Google Cloud TPU only reaches about 400 TFLOPs; while extremely impressive, this is still only about 200 million times faster than a CRAY-1; so even a billion times faster would be an exaggeration. -- The Anome (talk) 11:15, 18 October 2021 (UTC)
replies: text: I don't think there's even a point to putting specific values there. There's no single way to measure computer speed (to put it mildly). As far as estimating goes, it looks like CRAY-1 had 160 MFLOPS, and if anything it should be compared per analogy with the fastest machine - Fugaku with over 400 PFLOPS. Mithoron (talk) 13:40, 18 October 2021 (UTC)
replies: text:  Thanks for fixing this. ---- CharlesGillingham (talk) 15:07, 18 October 2021 (UTC)
thread_title:  Trillions vs. hundreds of millions