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 several languages, and the highest languages, moreover English, are Russian, Arabic, and Vietnamese.
“So the tokenizer’s most important influence, in my view, is you get the 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 will probably analyze the prompts quicker and cost customers much less for a similar reply. With the brand new tokenizer, “you’re taking a look at nearly 4 occasions value 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 taking place in these languages, in order that they embrace 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 doubtless displays the coaching information in these languages, Das says: “My working idea 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 should 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 a scarcity of cleansing
Nevertheless, issues are drastically totally different in Chinese language. In line with a number of researchers who’ve regarded into the brand new library of tokens used for GPT-4o, the longest tokens in Chinese language are nearly solely 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] shouldn’t be clear. The English tokens appear advantageous, however the Chinese language ones should not,” says Cai from Princeton College. It isn’t uncommon for a language mannequin to crawl spam when amassing coaching information, however normally there will likely be important effort taken to wash up the information earlier than it’s used. “It’s potential that they didn’t do correct information clearing relating 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 ads for pornography movies and playing web sites. They might be actual companies or merely scams. And the language is inserted into content material farm web sites or generally authentic 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 end result 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 not less than 5 Chinese language tokens in GPT-4o.
