AI

Artificial intelligence system dealing with (human) natural language rely on language models, predictions of which words occur together. To better understand how such models work -- and where they fail -- when applied to Swedish texts we need Swedish test data. A collection of test data addressing various aspects of understanding and generating text allows us to evaluate and compare models.

I en värld där AI tar en allt större plats har datadriven forskning blivit orden på allas läppar. I det här blogginlägget tänkte jag prata lite om vad det innebär att forska med hjälp av stora mängder textdata, primärt inom humaniora. Detta inlägg är det första i en serie om de olika delarna av en data-intensiv forskningsmetodologi.

Recently, we have seen a surge of methods that claim to embed meaning from textual corpora. But is that possible? Can text really reveal meaning, and if so, can current NLP methods detect it? Can our methods, as they some times claim, understand? Perhaps the larger question is the following: can we bring meaning to words using only the information stored in text? This question is essential for any Artificial Intelligence (AI) system that uses text as a basis.