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DeepMind's Losses and the Future of Artificial Intelligence

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.

Certainly, genuine machine intelligence (also known as artificial general intelligence), of the sort that would power a Star Trek–like computer, capable of analyzing all sorts of queries posed in ordinary English, would be worth far more than that.

That technique combines deep learning, primarily used for recognizing patterns, with reinforcement learning, geared around learning based on reward signals, such as a score in a game or victory or defeat in a game like chess.

DeepMind gave the technique its name in 2013, in an exciting paper that showed how a single neural network system could be trained to play different Atari games, such as Breakout and Space Invaders, as well as, or better than, humans.

DeepMind’s StarCraft outcomes were similarly limited, with better-than-human results when played on a single map with a single “race” of character, but poorer results on different maps and with different characters.

(DeepMind’s recent results with kidney disease have been questioned in similar ways.) Deep reinforcement learning also requires a huge amount of data—e.g., millions of self-played games of Go.

UK government to invest £250m in NHS AI lab

The UK health secretary Matt Hancock has announced £250m to

in the right direction to help the NHS become a world leader in using these

offer reliable health information from the healthcare body’s website by means

tech companies, big and small, we can ensure that the millions of users looking

for health information every day can get simple, validated advice at the

touch of a button or voice command.” Not all stakeholders appear to be happy about the recent developments, however.

A GP based in Hampshire wrote to The Register this week arguing the AI lab proposal was ‘just another sound bite.’ Interested in hearing industry leaders discuss subjects like this and their use cases?Attend the co-locatedAI &

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