Post by habiba123820 on Nov 4, 2024 22:48:13 GMT -6
Open AI has just released GPT-4, an improved version of its next-generation generative artificial intelligence.
According to GPT Chat itself, the difference between the models is:
In plain English, it’s bigger, better, and meaner. What does this mean in terms of translation and localization? According to Open AI’s research :
In simple terms: Imagine you’re really wordpress web design agency good at taking tests in school. You’ve always done well on English tests, but you want to see if you can do well on tests in other languages too. So you take a big test with 14,000 questions in lots of different subjects, like math, science, and history.
To make it even harder, you take the test in different languages using a special tool that translates the questions into other languages for you. You try in 26 different languages, but only 2 of them don't work well.
Surprisingly, you did even better on the test in these other languages than you did on the same test in English. You even do very well in languages that are not widely used, such as Latvian, Welsh and Swahili.
That's pretty much what happened when they tested a computer program called GPT-4. It's really good at understanding questions and answering them, even when they're in different languages. It performed better than other similar programs like GPT-3.5 and Chinchilla, even for the most difficult languages.
Let's compare some real-world examples in a few languages.
A quick analysis of this limited sample of 10 idiomatic American English sentences reveals no significant differences between the output of GPT-3 and GPT-4. This demonstrates that:
GPT-3 was already pretty impressive from the start.
It takes a lot of attention to detail to discern the differences between GPT-3 and GPT-4.
When examining the subtle differences between the two, GPT-4 was in one instance significantly better than GPT-3, but also notably worse in another instance. In most cases, it was either identical or slightly better.
The concepts that applied to GPT-3 are even more true for GPT-4. With more parameters and data, prompts become increasingly important. The slightest variation in the command suggestion can result in substantially different results. As the AI model becomes more refined, greater precision is required from the user.
As for other languages mentioned in OpenAI’s research, we will soon conduct our own investigation into their performance and report back with findings on translation quality and opportunities in the context of GPT-3 vs. GPT-4.
ChatGPT Paper
Download our 55-page study for an in-depth translation comparison between ChatGPT and the leading machine translations on the market.
According to GPT Chat itself, the difference between the models is:
In plain English, it’s bigger, better, and meaner. What does this mean in terms of translation and localization? According to Open AI’s research :
In simple terms: Imagine you’re really wordpress web design agency good at taking tests in school. You’ve always done well on English tests, but you want to see if you can do well on tests in other languages too. So you take a big test with 14,000 questions in lots of different subjects, like math, science, and history.
To make it even harder, you take the test in different languages using a special tool that translates the questions into other languages for you. You try in 26 different languages, but only 2 of them don't work well.
Surprisingly, you did even better on the test in these other languages than you did on the same test in English. You even do very well in languages that are not widely used, such as Latvian, Welsh and Swahili.
That's pretty much what happened when they tested a computer program called GPT-4. It's really good at understanding questions and answering them, even when they're in different languages. It performed better than other similar programs like GPT-3.5 and Chinchilla, even for the most difficult languages.
Let's compare some real-world examples in a few languages.
A quick analysis of this limited sample of 10 idiomatic American English sentences reveals no significant differences between the output of GPT-3 and GPT-4. This demonstrates that:
GPT-3 was already pretty impressive from the start.
It takes a lot of attention to detail to discern the differences between GPT-3 and GPT-4.
When examining the subtle differences between the two, GPT-4 was in one instance significantly better than GPT-3, but also notably worse in another instance. In most cases, it was either identical or slightly better.
The concepts that applied to GPT-3 are even more true for GPT-4. With more parameters and data, prompts become increasingly important. The slightest variation in the command suggestion can result in substantially different results. As the AI model becomes more refined, greater precision is required from the user.
As for other languages mentioned in OpenAI’s research, we will soon conduct our own investigation into their performance and report back with findings on translation quality and opportunities in the context of GPT-3 vs. GPT-4.
ChatGPT Paper
Download our 55-page study for an in-depth translation comparison between ChatGPT and the leading machine translations on the market.
I am becoming a mermaid as well 