Machine learning – Google Deepmind – Artificial Intelligence

Machine learning is a type of artificial intelligence that provides computers the ability to learn without being explicitly programmed.

DeepMind was established in London by Demis Hassabis , Shane Legg and Mustafa Suleyman in 2011.

Major venture capital firms Horizons Ventures and Founders Fund have invested in the company, as well as entrepreneurs Scott Banister and Elon Musk. Jaan Tallinn was an early investor and an advisor to the company. In 2014, DeepMind received the “Company of the Year” award by Cambridge Computer Laboratory. Also on 26 January 2014 Google announced that it had agreed to take over DeepMind Technologies.

Google DeepMind is now an artificial intelligence division within Google that was created after Google bought University College London spinout, DeepMind, for a reported £400 million.

The company describes its sole purpose in very simple terms: to “solve intelligence“.

The division, which employs around 140 researchers at its lab in a new building at Kings Cross, London, is on a mission to solve general intelligence and make machines capable of learning things for themselves. It plans to create a set of powerful general-purpose learning algorithms that can be combined to make an AI system or “agent”.

That’s easy enough to say, but it doesn’t really describe what DeepMind does. The company builds “powerful general‑purpose learning algorithms” by combining various techniques from machine learning and systems neuroscience.

DeepMind created an AI system that taught itself how to play 49 classic Atari video games, including Breakout, often to a level that no human player would be able to match.

But, what about Google? Google didn’t buy DeepMind for nothing. Indeed, it’s using certain DeepMind algorithms to make many of its best-known products and services smarter than they were previously.


What’s startling is that this was achieved with only minimal human input. Supercomputers have been programmed to take on chess grand-masters in the past – and sometimes successfully at that. But this has always been done by feeding in reams of data, based on strategies from real life players, rather than the computer itself figuring out the rules, reading the board, and coming up with a working strategy.

Also impressive is the diverse nature of those 49 games, which included side-scrolling shooters, one-on-one combat games, and racing games, among others. This reflects a varied set of decision-making requirements that the AI “agent” had to adapt to.

Having published its findings in science journal Nature, co-founder Hassabis called this breakthrough “the first significant rung on the ladder to proving general learning systems can work”. He also pointed out that this was “the first time that anyone has built a single general learning system that can learn directly from experience”.

This was, quite recognisably, AI in a small but true form.

Google has pledged to set up an ethics board to monitor it’s internal AI developments. Interestingly, this was one of DeepMind’s prerequisites to signing the acquisition papers, suggesting that Suleyman knows AI has potential to do harm. 

Forbes new article: Google DeepMind researchers also developing an A.I. Kill Switch, Just In Case…



Tommy Lambert Written by:

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