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 major affect, for my part, is you get the price 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 sooner 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 replicate 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 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 concept is the web sites in Hindi and Bengali are very rudimentary. It’s like [mostly] information articles. So I might count on this to be the case. There will not be many spam bots and porn web sites making an attempt to occur in these languages. It’s largely going to be in English.”
Polluted information and an absence of cleansing
Nevertheless, issues are drastically completely different in Chinese language. In keeping 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 completely spam phrases utilized in pornography, playing, and scamming contexts. Even shorter tokens, like three-character-long Chinese language phrases, replicate these matters to a major diploma.
“The issue is obvious: the corpus used to coach [the tokenizer] isn’t clear. The English tokens appear positive, however the Chinese language ones will not be,” 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 in terms of Chinese language,” he says.
The content material of those Chinese language tokens might counsel that they’ve been polluted by a selected 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 could possibly be actual companies or merely scams. And the language is inserted into content material farm web sites or generally respectable web sites to allow them to be listed by engines like google, 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 not less than 5 Chinese language tokens in GPT-4o.