De flesta använder ChatGPT för snabba svar. Men enligt dataanalytikern James Wilkins, som skriver i magasinet Data Science Collective, går det att få betydligt mer ut av verktyget. I artikeln You’re using ChatGPT wrong – here’s how to prompt like a pro förklarar han hur forskningsbaserade metoder kan göra svaren både mer korrekta och mer användbara.
Elva forskningsbaserade verktyg som gör dig bättre på ChatGPT
Digitalisering & AI De flesta använder ChatGPT för snabba svar. Men enligt dataanalytikern James Wilkins kan genomtänkta prompts ge betydligt bättre resultat. Här är hela listan.

Foto: Adobe Stock
Någonting är fel
Du är inloggad som prenumerant hos förlaget Pauser Media, men nånting är fel. På din profilsida ser du vilka av våra produkter som du har tillgång till. Skulle uppgifterna inte stämma på din profilsida – vänligen kontakta vår kundtjänst.
VD-tidningen premium
Läs vidare – starta din prenumeration
Redan prenumerant? Logga in och läs vidare.
Språkmodeller som ChatGPT är i grunden mönsterigenkännare. De förutser vilket ord som sannolikt kommer härnäst, men de ”vet” ingenting. De är tränade på enorma textmängder där vissa ord och begrepp ofta förekommer tillsammans. Som James Wilkins påpekar: att frasen The Great Fire of London ofta följs av 1666 handlar inte om kunskap – utan om sannolikhet.
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


