The rise of generative AI and large-scale language fashions (LLMs) has captivated the world and revolutionized many fields. Whereas the first focus of one of these expertise has been on textual content sequences, there may be now extra consideration being paid to extending its capabilities to course of and course of knowledge codecs past simply textual content enter.
Like most AI fields, time sequence forecasting shouldn’t be resistant to the emergence of LLMs, however this can be an excellent factor for all. Time sequence modeling is thought to be one thing of an artwork, the place the outcomes rely closely on prior area data and correct tuning. Conversely, LLMs are acclaimed for being task-independent, and have nice potential to make use of their data to resolve numerous duties from totally different domains. From the union of those two fields, new frontiers for time sequence forecasting fashions emerge, enabling us to realize beforehand unthinkable outcomes sooner or later.
