that is expanding to 40 more languages.
launched this , to an AI-powered of sorts. works in a multi-step , from creating a to finding relevant information. Then, based on that , performs a again to extract knowledge. that a few times, it creates a .
< Gemini's> include , , , , , , , , , , , , , , , , , , , , , , , and .
for is to find in a particular , and then it in without messing up .
with , , of engineering for , that trains using and , overviews in like tend to have inaccuracies in summaries.
“We generally rely on native sources of data, and we also use on back end to ground that information. Additionally, we run evaluations and fact-checks in data before rolling out ,” Choe said.
“Factuality or getting correct information is a well-known research problem for generative in general. While has a lot of information in pre-training already, we are focusing on training to use information in right way,” Choe said.
, for international markets for , that has testing programs to get quality checks from native perspectives. mentioned that generates data to train models. , local teams reviews those datasets too.
this , reported that a contracting firm working to improve by rating responses passed down guidelines from that contractors were no longer allowed to skip prompt responses, irrespective of their expertise.
that report was published, a spokersperson said that contractors not only rate answers for content but also look at style, format, and other factors.
