Making Sense of DeepMind’s First-Ever Profit

DeepMind has developed breaking innovations, including AlphaFold, a solution to the 50-year-old protein folding problem.
Making Sense of DeepMind’s First-Ever Profit

According to a corporate filing with the UK company registry published on Tuesday, Google-backed artificial intelligence research firm DeepMind turned a profit for the first time last year and saw a significant rise in its revenues.

As per the filings, its sales rose by £560 million last year, touching £826 million, compared to £266 million in 2019. The surge in revenue helped the company turn its first profit of £43.8 million, compared to a loss of £649 million the previous year. The research lab draws its revenue from research and development carried out for other companies under the Alphabet umbrella, including Google, YouTube and X, the moonshot division.  

Headquartered in Kings Cross, London, DeepMind was founded by Demis Hassabis in 2010. In 2014, Google parent Alphabet bought the business for around half a billion dollars. Since the acquisition, the tech giant has heavily subsidised DeepMind, which has had cumulative losses of almost £2 billion since its inception in 2014. However, its sales have accelerated rapidly in recent years as the hundreds of millions spent on research has begun to yield results.

Science Behind DeepMind’s Stellar Growth

In the last few years, DeepMind has developed breaking innovations, including AlphaFold, a solution to the 50-year-old protein folding problem. The most recent is Precipitation Nowcasting, which predicts rain within a span of one to two hours

Besides AlphaFold, some of the other research work in 2020 includes FermiNets, Agent57, and the development of advanced graph neural networks (GNN) to predict traffic, amongst others. Even though the company has not mentioned the reason for its revenue growth or disclosed details about its scale, the recent revenue growth points at DeepMind’s tech, which seems to be driving improvements in Google’s ad performance (and Maps, Android, etc.), along with its valuable research on protein structure. 

At the same time, the latest decision by Google to not allow larger autonomy to DeepMind seems to be working in its favour. The same is the case with its arch-rival OpenAI, which shifted from non-profit to ‘capped-profit’ to attract capital – nearly two years ago – alongside giving exclusive license of GPT-3 to Microsoft for commercial applications and use cases. 

What about Expenses?

While the profit of DeepMind saw a significant rise last year, so did its expenses. DeepMind’s business expenses rose by 8 per cent to £780 million, an increase of £63 million. In 2019, the company recorded expenses of £717 million. The increase in expenses is due to technical infrastructure, staff costs, and other related charges, read the filings. 

DeepMind’s technical infrastructure runs mostly on Google’s cloud services and special AI processors – the Tensor Processing Unit (TPUs). DeepMind’s focus area of research is deep reinforcement learning, which calls for very expensive computing resources, and training the AI/ML models also costs millions

However, there are no public details on how much Google charges DeepMind for using its cloud AI services, but it mostly rents its TPUs at a discounted price. In other words, without the support or backing from Google, the company’s expenses might have increased significantly. 

The staff costs saw an increase of £473 million, from £467 million in 2019, suggesting that the company is actively hiring. However, it did not specify the number of people it added to its team last year but said it employs over 1,000 people. DeepMind hires some of the world’s leading AI research scientists, who can easily command annual salaries of more than $1 million


DeepMind’s profit numbers seem to have strengthened Google’s investment in the company, where it had previously waived off its debt and accrued interest amounting to £1.1 billion, along with a written assurance from Google, stating that it would ‘continue to provide adequate financial support,’ to DeepMind for a “period of at least twelve months”. 

It is only about time that DeepMind reaches complete autonomy, and at the same time, remains profitable without financial support from Google in the coming years – a move towards developing artificial general intelligence (AGI).

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Amit Raja Naik
Amit Raja Naik is a seasoned technology journalist who covers everything from data science to machine learning and artificial intelligence for Analytics India Magazine, where he examines the trends, challenges, ideas, and transformations across the industry.

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