Google continues to heavily subsidize its DeepMind artificial intelligence startup, writing off $1.5 billion in debt as losses grew.

According to a filing with the U.K.’s Companies House, DeepMind’s revenue more than doubled from 103 million pounds ($140 million) in 2018 to 266 million pounds ($362 million) in 2019.

The company’s loss rose to 477 million pounds ($649 million) from 470 million ($640 million). But during 2019, Google waived the repayment of intercompany loans and all accrued interest. That amounted to 1.1 billion pounds ($1.5 billion).

The debt waiver “underscores Google’s commitment to its investment in DeepMind, with little indication the burgeoning startup is likely to turn a profit any time soon,” Business Insider said.

Google acquired DeepMind for around $600 million in 2014 and has so far invested roughly $2 billion in the startup, which has focused on an AI technology known as deep reinforcement learning. “The direct financial return, not counting publicity, has been modest by comparison,” according to Wired.

Revenue has come from applying deep reinforcement learning within Google to reduce power costs for cooling its servers but DeepMind has yet to find any large-scale commercial application for the technology.

“Machine learning research and application is an emerging market characterized by continuous change and intense competition,” DeepMind said in the filing. “As a result, the company will continue to face risks and uncertainties, which may have a significant impact on its ability to achieve continued success within its market.”

Google has also invested in AI through its Google Brain research team.

“I’m very happy with the pace at which our R&D on AI is progressing,” Google CEO Sundar Pichai said on a recent earnings call. “And for me, it’s important that we are state-of-the-art as a company, and we are leading. And to me, I’m excited at the pace at which our engineering and R&D teams are working both across Google and DeepMind.”

A DeepMind spokesperson said its teams are “involved in a huge range of projects, from improving the predictability of wind power to accelerating ecological research in the Serengeti.”

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