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 depend the variety of tokens in numerous languages, and the highest languages, moreover English, are Russian, Arabic, and Vietnamese.
“So the tokenizer’s predominant impression, for my part, 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 analyze the prompts sooner and cost customers much less for a similar reply. With the brand new tokenizer, “you’re taking a look at nearly 4 occasions price discount,” he says.
Das, who additionally speaks Hindi and Bengali, took a have a look at the longest tokens in these languages. The tokens mirror discussions occurring in these languages, so that they embody phrases like “Narendra” or “Pakistan,” however widespread English phrases like “Prime Minister,” “college,” and “worldwide” additionally come up continuously. In addition they don’t exhibit the problems surrounding the Chinese language tokens.
That doubtless 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 might anticipate this to be the case. There aren’t many spam bots and porn web sites attempting to occur in these languages. It’s largely going to be in English.”
Polluted information and a scarcity of cleansing
Nonetheless, issues are drastically totally different in Chinese language. In accordance with 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 nearly 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 big diploma.
“The issue is obvious: the corpus used to coach [the tokenizer] is just not clear. The English tokens appear fantastic, however the Chinese language ones aren’t,” says Cai from Princeton College. It’s not uncommon for a language mannequin to crawl spam when accumulating coaching information, however often there shall be important effort taken to scrub up the info earlier than it’s used. “It’s attainable that they didn’t do correct information clearing in the case of 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 typically professional 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 outcome web page on a US Nationwide Institutes of Well being web site, which lists a porn web site in Chinese language. The identical web site title additionally appeared in a minimum of 5 Chinese language tokens in GPT-4o.
