Open main menu
Home
Random
Recent changes
Special pages
Community portal
Preferences
About Wikipedia
Disclaimers
Incubator escapee wiki
Search
User menu
Talk
Dark mode
Contributions
Create account
Log in
Editing
Artificial general intelligence
(section)
Warning:
You are not logged in. Your IP address will be publicly visible if you make any edits. If you
log in
or
create an account
, your edits will be attributed to your username, along with other benefits.
Anti-spam check. Do
not
fill this in!
===AI-complete problems=== {{Main|AI-complete}} A problem is informally called "AI-complete" or "AI-hard" if it is believed that in order to solve it, one would need to implement AGI, because the solution is beyond the capabilities of a purpose-specific algorithm.<ref name="Shapiro92">{{Cite book |last=Shapiro |first=Stuart C. |title=Encyclopedia of Artificial Intelligence |publisher=John Wiley |date=1992 |editor-last=Stuart C. Shapiro |edition=Second |location=New York |pages=54β57 |chapter=Artificial Intelligence |chapter-url=http://www.cse.buffalo.edu/~shapiro/Papers/ai.pdf |archive-url=https://web.archive.org/web/20160201014644/http://www.cse.buffalo.edu/~shapiro/Papers/ai.pdf |archive-date=1 February 2016 |url-status=live}} (Section 4 is on "AI-Complete Tasks".)</ref> There are many problems that have been conjectured to require general intelligence to solve as well as humans. Examples include [[computer vision]], [[natural-language understanding|natural language understanding]], and dealing with unexpected circumstances while solving any real-world problem.<ref>{{Cite journal |last=Yampolskiy |first=Roman V. |date=2012 |title=Turing Test as a Defining Feature of AI-Completeness |url=http://cecs.louisville.edu/ry/TuringTestasaDefiningFeature04270003.pdf |url-status=live |journal=Artificial Intelligence, Evolutionary Computation and Metaheuristics |pages=3β17 |archive-url=https://web.archive.org/web/20130522094547/http://cecs.louisville.edu/ry/TuringTestasaDefiningFeature04270003.pdf |archive-date=22 May 2013 |editor=Xin-She Yang}}</ref> Even a specific task like [[machine translation|translation]] requires a machine to read and write in both languages, follow the author's argument (reason), understand the context (knowledge), and faithfully reproduce the author's original intent ([[social intelligence]]). All of these problems need to be solved simultaneously in order to reach human-level machine performance. However, many of these tasks can now be performed by modern large language models. According to [[Stanford University]]'s 2024 AI index, AI has reached human-level performance on many [[Benchmarks for artificial intelligence|benchmarks]] for reading comprehension and visual reasoning.<ref>{{Cite web |date=2024-04-15 |title=AI Index: State of AI in 13 Charts |url=https://hai.stanford.edu/news/ai-index-state-ai-13-charts |access-date=2024-05-27 |website=Stanford University Human-Centered Artificial Intelligence |language=en}}</ref>
Edit summary
(Briefly describe your changes)
By publishing changes, you agree to the
Terms of Use
, and you irrevocably agree to release your contribution under the
CC BY-SA 4.0 License
and the
GFDL
. You agree that a hyperlink or URL is sufficient attribution under the Creative Commons license.
Cancel
Editing help
(opens in new window)