electronic dictionary that can
Posted: Mon Dec 23, 2024 6:56 am
He has a very famous metaphor: if aliens came to Earth, they would be able to understand and read all the languages on Earth. Because in their view, every language on Earth follows the same grammar, but everyone speaks different "dialects". If htT can switch between multiple languages with ease, has it cracked the mystery of the world's universal grammar? Low-resource languages are still underrepresented in large language models. Although large language models have the potential to be transformative, the reality is that large language models mainly cater to English and a few other high-resource languages.
A close examination of the training corpora iran telephone number used by models such as T-T found that there is a clear imbalance between the languages. English dominates. The training corpus of T-T is overwhelmingly English, accounting for . . htT is based on -. Subsequent models such as . continue this trend. Limited representation of languages in the T-corpus: only two languages make up more than 50% of the T-corpus: French and German. Other languages that fall into the 50% range include Spanish, Italian, Portuguese, Dutch, Russian, Romanian, Polish, Finnish, Danish, Swedish, Japanese, and Norwegian.
It is worth noting that languages like Chinese and Hindi, which have more than 100 million speakers combined, do not even make the corpus. Training data concentration: there is a clear head effect for the top languages in the T-training corpus: together they make up 50%. Limited word coverage: only 10 languages have more than 10 million words in the T-training corpus, of which 1 is Khmer. Although Khmer is spoken by 10 million people in Cambodia, it only has 10 million words in the T-training corpus. htT's preference for English and selected high-resource languages is not intentional by htT's parent company; because most of the corpus comes from the Internet, and the Internet reflects the wealth, openness, and activity of a country and language.
A close examination of the training corpora iran telephone number used by models such as T-T found that there is a clear imbalance between the languages. English dominates. The training corpus of T-T is overwhelmingly English, accounting for . . htT is based on -. Subsequent models such as . continue this trend. Limited representation of languages in the T-corpus: only two languages make up more than 50% of the T-corpus: French and German. Other languages that fall into the 50% range include Spanish, Italian, Portuguese, Dutch, Russian, Romanian, Polish, Finnish, Danish, Swedish, Japanese, and Norwegian.
It is worth noting that languages like Chinese and Hindi, which have more than 100 million speakers combined, do not even make the corpus. Training data concentration: there is a clear head effect for the top languages in the T-training corpus: together they make up 50%. Limited word coverage: only 10 languages have more than 10 million words in the T-training corpus, of which 1 is Khmer. Although Khmer is spoken by 10 million people in Cambodia, it only has 10 million words in the T-training corpus. htT's preference for English and selected high-resource languages is not intentional by htT's parent company; because most of the corpus comes from the Internet, and the Internet reflects the wealth, openness, and activity of a country and language.