Μετάφραση και ανάλυση λέξεων από την τεχνητή νοημοσύνη ChatGPT
Σε αυτήν τη σελίδα μπορείτε να λάβετε μια λεπτομερή ανάλυση μιας λέξης ή μιας φράσης, η οποία δημιουργήθηκε χρησιμοποιώντας το ChatGPT, την καλύτερη τεχνολογία τεχνητής νοημοσύνης μέχρι σήμερα:
- πώς χρησιμοποιείται η λέξη
- συχνότητα χρήσης
- χρησιμοποιείται πιο συχνά στον προφορικό ή γραπτό λόγο
- επιλογές μετάφρασης λέξεων
- παραδείγματα χρήσης (πολλές φράσεις με μετάφραση)
- ετυμολογία
NP problem - translation to ρωσικά
![quadratic fit]] suggests that the algorithmic complexity of the problem is O((log(''n''))<sup>2</sup>).<ref name=Pisinger2003>Pisinger, D. 2003. "Where are the hard knapsack problems?" Technical Report 2003/08, Department of Computer Science, University of Copenhagen, Copenhagen, Denmark</ref>](https://commons.wikimedia.org/wiki/Special:FilePath/KnapsackEmpComplexity.GIF?width=200 "quadratic fit]] suggests that the algorithmic complexity of the problem is O((log(''n''))<sup>2</sup>).<ref name=Pisinger2003>Pisinger, D. 2003. \"Where are the hard knapsack problems?\" Technical Report 2003/08, Department of Computer Science, University of Copenhagen, Copenhagen, Denmark</ref>")
![NP]], NP-complete, and NP-hard set of problems (excluding the empty language and its complement, which belong to P but are not NP-complete)](https://commons.wikimedia.org/wiki/Special:FilePath/P np np-complete np-hard.svg?width=200 "NP]], NP-complete, and NP-hard set of problems (excluding the empty language and its complement, which belong to P but are not NP-complete)")
Ορισμός
Βικιπαίδεια
The P versus NP problem is a major unsolved problem in theoretical computer science. In informal terms, it asks whether every problem whose solution can be quickly verified can also be quickly solved.
The informal term quickly, used above, means the existence of an algorithm solving the task that runs in polynomial time, such that the time to complete the task varies as a polynomial function on the size of the input to the algorithm (as opposed to, say, exponential time). The general class of questions for which some algorithm can provide an answer in polynomial time is "P" or "class P". For some questions, there is no known way to find an answer quickly, but if one is provided with information showing what the answer is, it is possible to verify the answer quickly. The class of questions for which an answer can be verified in polynomial time is NP, which stands for "nondeterministic polynomial time".
An answer to the P versus NP question would determine whether problems that can be verified in polynomial time can also be solved in polynomial time. If it turns out that P ≠ NP, which is widely believed, it would mean that there are problems in NP that are harder to compute than to verify: they could not be solved in polynomial time, but the answer could be verified in polynomial time.
The problem has been called the most important open problem in computer science. Aside from being an important problem in computational theory, a proof either way would have profound implications for mathematics, cryptography, algorithm research, artificial intelligence, game theory, multimedia processing, philosophy, economics and many other fields.
It is one of the seven Millennium Prize Problems selected by the Clay Mathematics Institute, each of which carries a US$1,000,000 prize for the first correct solution.
