Google AI project apes memory, programs (sort of) like a human

Neural Turing Machines attempt to emulate the brain's short-term memory

Artificial intelligence concept illustration

An artificial intelligence concept illustration.

abstract, android, artificial, binary, blue, brain, cell, communication, computer, concept, connection, creative, cyber, cybernetic, cyberspace, cyborg, data, digit, digital, fantasy, fiction, future, futuristic, fuzzy, head, human, idea, illustration, imagination, informatics, information, dreamstime

dreamstime_29416761
Artificial intelligence concept illustration An artificial intelligence concept illustration. abstract, android, artificial, binary, blue, brain, cell, communication, computer, concept, connection, creative, cyber, cybernetic, cyberspace, cyborg, data, digit, digital, fantasy, fiction, future, futuristic, fuzzy, head, human, idea, illustration, imagination, informatics, information, dreamstime dreamstime_29416761

The mission of Google's DeepMind Technologies startup is to "solve intelligence." Now, researchers there have developed an artificial intelligence system that can mimic some of the brain's memory skills and even program like a human.

The researchers developed a kind of neural network that can use external memory, allowing it to learn and perform tasks based on stored data.

Neural networks are interconnected computational "neurons." While conventional neural networks have lacked readable and writeable memory, they have been used in machine learning and pattern-recognition applications such as computer vision and speech recognition.

The so-called Neural Turing Machine (NTM) that DeepMind researchers have been working on combines a neural network controller with a memory bank, giving it the ability to learn to store and retrieve information.

The system's name refers to computer pioneer Alan Turing's formulation of computers as machines having working memory for storage and retrieval of data.

The researchers put the NTM through a series of tests including tasks such as copying and sorting blocks of data. Compared to a conventional neural net, the NTM was able to learn faster and copy longer data sequences with fewer errors. They found that its approach to the problem was comparable to that of a human programmer working in a low-level programming language.

The NTM "can infer simple algorithms such as copying, sorting and associative recall from input and output examples," DeepMind's Alex Graves, Greg Wayne and Ivo Danihelka wrote in a research paper available on the arXiv repository.

"Our experiments demonstrate that it is capable of learning simple algorithms from example data and of using these algorithms to generalize well outside its training regime."

A spokesman for Google declined to provide more information about the project, saying only that the research is "quite a few layers down from practical applications."

In a 2013 paper, Graves and colleagues showed how they had used a technique known as deep reinforcement learning to get DeepMind software to learn to play seven classic Atari 2600 video games, some better than a human expert, with the only input being information visible on the game screen.

Google confirmed earlier this year that it had acquired London-based DeepMind Technologies, founded in 2011 as an artificial intelligence company. The move is expected to have a major role in advancing the search giant's research into robotics, self-driving cars and smart-home technologies.

More recently, DeepMind co-founder Demis Hassabis wrote in a blog post that Google is partnering with artificial intelligence researchers from Oxford University to study topics including image recognition and natural language understanding.

Join the newsletter!

Or
Error: Please check your email address.
Show Comments

Blog Posts

Social purpose: Oxygen for your brand health vitals

If trust is the new currency, then we’re in deep trouble. Here's why.

Carolyn Butler-Madden

Founder and CEO, Sunday Lunch

Customer experience disruption: Healthcare faces a bitter pill

Over the past decade, disruptors such as Amazon, Apple and Australia’s Atlassian have delivered technology enhanced customer experiences, which for the most part, have improved customers’ lives and delivered unparalleled growth. Can they do the same for healthcare?

Alex Allwood

Principal, All Work Together

How can a brand remain human in a digital world?

Some commentators estimate that by 2020, 85 per cent of buyer-seller interactions will happen online through social media and video*. That’s only two years away, and pertinent for any marketer.

James Kyd

Global head of brand strategy and marketing, Xero

https://bit.ly/2qLgzmR Transform your life a proven digital blueprint

Okitoi Steven

How this banking group tackled a digital marketing transformation

Read more

Its great to hear that companies including JCDecaux, oOh!media, Omnicom and Posterscope Australia have all partnered with Seedooh inorder...

Blue Mushroom Infozone Pvt Ltd

Out of home advertising companies strive for greater metrics and transparency

Read more

Much ado about nothingAnother fluff piece around what it could possibly do rather than what it is doing

gve

How AMP is using AI to create effortless ‘experiences’

Read more

is it true that Consumer expectations are also changing as a result. If we trust someone with our data there is also an expectation that ...

Sunita Madan

Society will decide where digital marketing takes us next: Oracle

Read more

This Blog is Very interesting to read and thank you for sharing the valuable information about Machine Learning. The information you prov...

johny blaze

What machine learning has done for the Virgin Velocity program

Read more

Latest Podcast

More podcasts

Sign in