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Thursday, August 15, 2019

DeepMind's Losses and the Future of Artificial Intelligence | Business - WIRED

Alphabet’s DeepMind unit, conqueror of Go and other games, is losing lots of money. Continued deficits could imperil investments in AI, according to Gary Marcus, CEO and Founder at Robust.AI. 

Photo: La Tigre

Alphabet’s DeepMind lost $572 million last year. What does it mean?

DeepMind, likely the world’s largest research-focused artificial intelligence operation, is losing a lot of money fast, more than $1 billion in the past three years. DeepMind also has more than $1 billion in debt due in the next 12 months.

Does this mean that AI is falling apart?...

Deep reinforcement learning also requires a huge amount of data—e.g., millions of self-played games of Go. That’s far more than a human would require to become world class at Go, and often difficult or expensive. That brings a requirement for Google-scale computer resources, which means that, in many real-world problems, the computer time alone would be too costly for most users to consider. By one estimate, the training time for AlphaGo cost $35 million; the same estimate likened the amount of energy used to the energy consumed by 12,760 human brains running continuously for three days without sleep.

But that’s just economics. The real issue, as Ernest Davis and I argue in our forthcoming book Rebooting AI, is trust. For now, deep reinforcement learning can only be trusted in environments that are well controlled, with few surprises; that works fine for Go—neither the board nor the rules have changed in 2,000 years—but you wouldn’t want to rely on it in many real-world situations.

Recommended Reading

Rebooting AI:
Building Artificial Intelligence We Can Trust
Source: WIRED