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Last week, news broke that famous UK-based artificial intelligence research lab DeepMind was stacking up huge losses for its parent company Alphabet Inc. According to documents filed with the UK’s Companies House registry, DeepMind’s incurred $570 million in losses in 2018, up from $341 million in 2017.

DeepMind is the AI outfit that is behind some of the most remarkable feats in the past years, including the AI that beat the human champion at Go developing a deep learning model that beat human champions at StarCraft 2. Alphabet, which also owns tech giant Google, acquired DeepMind for $650 million in 2014. Since then, it has been pouring money into the AI research lab without significant returns. DeepMind has 1.04 billion pounds in debts due this year, which includes an 883 million-pound loan from Alphabet.

DeepMind’s huge costs bring to light some of the most serious challenges the AI industry is grappling with. Here are some of the key takeaways.

AI talent scarcity is concentrating research in a powerful few

According to the released information, DeepMind paid $483 million to approx. 700 employees, which means an average of around $700,000 per employee. Of course, the pay is not evenly distributed and some of DeepMind’s AI engineers earn seven-digit salaries.

Currently, the AI talent that can lead the kind of innovative projects research labs like DeepMind work on is very scarce. This has created a race between tech giants to offer bigger salaries to AI engineers in hopes of attracting them to their research teams. Paying more than $1 million to AI researchers has become common in large tech companies like Google and well-funded AI research labs such as OpenAI.

The stellar costs of hiring AI researchers is problematic in several ways. The AI arms race between the Big Tech is making it harder for smaller companies and organizations to contribute their share to AI research. After all, not every company can afford to pay its AI researchers seven-digit salaries.

But perhaps the more damaging effect is the brain drain in academic AI. The growing interest and the deep pockets of large tech companies is attracting AI talent toward commercial entities. Universities are finding it harder and harder to hold on to their AI researchers as they can’t match the lucrative incentives Big Tech offers.

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