SAN FRANCISCO, Jan 28 (Reuters) - - Artificial

intelligence data startup Turing, one of a growing number of

companies that provide human trainers to AI labs, said Tuesday

its revenue tripled to $300 million last year as it reached

profitability.

Palo Alto-based Turing, which says OpenAI, Google, Anthropic

and Meta are its clients, was last valued at $1.1 billion in

2021.

As AI models have become more sophisticated, it has in turn

increased demand for human trainers with specialized knowledge,

boosting the valuation of startups like Turing competitor Scale

AI, which was valued at $14 billion last year.

Based on what the AI companies want their models to get

better at, AI data companies find workers with relevant

expertise for those projects, reducing the burden of managing

hundreds of trainers by the AI companies.

Turing says it has access to over 4 million human experts

such as software developers or scientists with doctorate

degrees, who it can contract to label data for AI models.

The costs aren't cheap: one complex annotation can cost

hundreds of dollars, Turing said, and advanced AI models can

require millions of annotations. For example, Meta used over 10

million human annotations when training the Llama 3 models, Meta

executive Joe Spisak said last year.

As AI labs hit the "data wall," a term for when model

performance plateaus due to lack of more internet training data,

the labs will increasingly rely on human data companies to make

their AI models smarter, Turing CEO Jonathan Siddharth told

Reuters.

"Companies like Turing are helping the scaling laws keep

going to make up for the data deficit that we have," he said.