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Lietojuma gadījumiMeklēšana
Izprotiet mākslīgā intelekta novērtēšanas metodes
Izmantojiet Padziļināta izpēte, lai atšifrētu LLM etalonus — kā tie darbojas, kur tie kļūdās un kurām metrikām uzticēties modeļu novērtēšanā
- Meklēšana
- Padziļināta izpēte
- Tehnoloģijas
Pārskats
MI pētnieki, inženieri un produktu vadītāji var izmantot Perplexity, lai izprastu strauji mainīgo LLM novērtēšanas ainavu. Padziļināta izpēte izmanto akadēmiskos rakstus, kritēriju testu dokumentāciju un nozares analīzi, lai izskaidrotu ne tikai to, kā darbojas kritēriju testi, bet arī to, kur tie ir nepilnīgi, palīdzot komandām pieņemt labākus lēmumus par to, kuriem metrikām uzticēties, novērtējot modeļus.
Padoms
- Dalieties ar savu konkrēto ražošanas kontekstu (piemēram, RAG konveijers, kodēšanas palīgs, atbalsta asistents), lai Perplexity varētu saskaņot šos kritēriju testus ar novērtēšanas komplektu, kuru jūs patiesībā vēlētos izveidot.
- Uzziniet par jaunākajām novērtēšanas pieejām, kas tiek izstrādātas, lai risinātu šos strukturālos ierobežojumus nākotnes kontekstā.