The brand new tokenizer has 200,000 tokens in complete, and about 25% are in non-English languages, says Deedy Das, an AI investor at Menlo Ventures. He used language filters to rely the variety of tokens in numerous languages, and the highest languages, apart from English, are Russian, Arabic, and Vietnamese.
“So the tokenizer’s predominant influence, in my view, is you get the associated fee down in these languages, not that the standard in these languages goes dramatically up,” Das says. When an LLM has higher and longer tokens in non-English languages, it may well analyze the prompts sooner and cost customers much less for a similar reply. With the brand new tokenizer, “you’re virtually 4 instances price discount,” he says.
Das, who additionally speaks Hindi and Bengali, took a take a look at the longest tokens in these languages. The tokens mirror discussions taking place in these languages, in order that they embody phrases like “Narendra” or “Pakistan,” however frequent English phrases like “Prime Minister,” “college,” and “worldwide” additionally come up incessantly. Additionally they don’t exhibit the problems surrounding the Chinese language tokens.
That probably displays the coaching information in these languages, Das says: “My working concept is the web sites in Hindi and Bengali are very rudimentary. It’s like [mostly] information articles. So I’d count on this to be the case. There usually are not many spam bots and porn web sites attempting to occur in these languages. It’s principally going to be in English.”
Polluted information and an absence of cleansing
Nonetheless, issues are drastically completely different in Chinese language. In response to a number of researchers who’ve seemed into the brand new library of tokens used for GPT-4o, the longest tokens in Chinese language are virtually completely spam phrases utilized in pornography, playing, and scamming contexts. Even shorter tokens, like three-character-long Chinese language phrases, mirror these matters to a major diploma.
“The issue is evident: the corpus used to coach [the tokenizer] just isn’t clear. The English tokens appear nice, however the Chinese language ones usually are not,” says Cai from Princeton College. It isn’t uncommon for a language mannequin to crawl spam when amassing coaching information, however normally there shall be important effort taken to scrub up the information earlier than it’s used. “It’s attainable that they didn’t do correct information clearing with regards to Chinese language,” he says.
The content material of those Chinese language tokens may recommend that they’ve been polluted by a particular phenomenon: web sites hijacking unrelated content material in Chinese language or different languages to spice up spam messages.
These messages are sometimes commercials for pornography movies and playing web sites. They may very well be actual companies or merely scams. And the language is inserted into content material farm web sites or generally legit web sites to allow them to be listed by serps, circumvent the spam filters, and are available up in random searches. For instance, Google listed one search consequence web page on a US Nationwide Institutes of Well being web site, which lists a porn website in Chinese language. The identical website identify additionally appeared in not less than 5 Chinese language tokens in GPT-4o.
