DataTorrent
Language Flags

Translation Disclaimer

HPCwire Enterprise Tech HPCwire Japan


August 22, 2013

This is Your Brain on GPUs


By now, we were told, we’d each have an intelligent robot assistant who would perform all the boring and repetitive tasks for us, freeing us to live a life of leisure. While that Jeston-esque future never quite materialized, recent breakthroughs in machine learning and GPU performance are enhancing our lives in other ways.

The fields of machine learning and artificial intelligence have been fraught with false starts and failed projects. After all, researchers don’t yet fully understand how the human brain works, so what makes you think they could replicate its processes in a machine?

While biological scientists create increasingly refined and accurate models of the human brain, computer scientists have been hard at work developing new approaches to machine learning, the field of artificial intelligence in which machines essentially program themselves based on the data they collect.

According to a recent blog post on Nvidia.com, these approaches are already paying dividends in the real world. “Thanks to a combination of recent algorithmic breakthroughs and the high performance of GPUs,” writes Nvidia product management intern Yanning Li, “researchers have seen dramatic improvements in accuracy for machine learning problems for services that are more than just lab experiments.”

Li presents several examples of how these “artificial brains” powered by GPUs are helping human kind. Google is at the forefront of using GPUs, and the company is reported to use GPU-equipped servers to deliver a variety of services, including its Web search, Google Maps Street View, and Android’s voice-recognition app.

Earlier this year, Baidu, considered the “Chinese Google,” rolled out a new visual search service that enables users to search the Web using images alone. The service uses GPUs to train its neural networks, even though it uses traditional CPUs to actually serve the visual searches.

Nuance, the company that has been at the forefront of voice recognition, is also using GPUs to power its service. In June, the company announced that it’s working with researchers at Stanford University to build the world’s largest neural network to model how the human brain learns.

Nuance says it trains its neural network models to understand users’ speech by using terabytes of audio data. “Once the models are trained, they can then recognize the pattern of spoken words by relating them to the patterns that the model learned earlier,” the company says in a June blog post.

Microsoft also used a combination of GPUs and advanced algorithms to develop the body detection capabilities of Kinect, a controller-free interface for its Xbox 360 video game console that lets users interact with the console using a wave of a hand.

“Kinect takes a stream of images coming off the camera and quickly works out where the joints in your body are in 3-D. It can use that to animate characters and to manipulate objects on the screen,” said Jamie Shotten of Microsoft Research in a 2011 blog post. 

Related items:

GPUs Push Big Data's Need for Speed 

Fuzzy Thinking about GPUs for Big Data 

The GPU "Sweet Spot" for Big Data 

Share Options


Subscribe

» Subscribe to our weekly e-newsletter


Discussion

There are 0 discussion items posted.

 

Most Read Features

Most Read News

Most Read This Just In

Cray Supercomputer

Sponsored Whitepapers

Planning Your Dashboard Project

02/01/2014 | iDashboards

Achieve your dashboard initiative goals by paving a path for success. A strategic plan helps you focus on the right key performance indicators and ensures your dashboards are effective. Learn how your organization can excel by planning out your dashboard project with our proven step-by-step process. This informational whitepaper will outline the benefits of well-thought dashboards, simplify the dashboard planning process, help avoid implementation challenges, and assist in a establishing a post deployment strategy.

Download this Whitepaper...

Slicing the Big Data Analytics Stack

11/26/2013 | HP, Mellanox, Revolution Analytics, SAS, Teradata

This special report provides an in-depth view into a series of technical tools and capabilities that are powering the next generation of big data analytics. Used properly, these tools provide increased insight, the possibility for new discoveries, and the ability to make quantitative decisions based on actual operational intelligence.

Download this Whitepaper...

View the White Paper Library

Sponsored Multimedia

Webinar: Powering Research with Knowledge Discovery & Data Mining (KDD)

Watch this webinar and learn how to develop “future-proof” advanced computing/storage technology solutions to easily manage large, shared compute resources and very large volumes of data. Focus on the research and the application results, not system and data management.

View Multimedia

Video: Using Eureqa to Uncover Mathematical Patterns Hidden in Your Data

Eureqa is like having an army of scientists working to unravel the fundamental equations hidden deep within your data. Eureqa’s algorithms identify what’s important and what’s not, enabling you to model, predict, and optimize what you care about like never before. Watch the video and learn how Eureqa can help you discover the hidden equations in your data.

View Multimedia

More Multimedia

NVIDIA

Job Bank

Datanami Conferences Ad

Featured Events

May 5-11, 2014
Big Data Week Atlanta
Atlanta, GA
United States

May 29-30, 2014
StampedeCon
St. Louis, MO
United States

June 10-12, 2014
Big Data Expo
New York, NY
United States

June 18-18, 2014
Women in Advanced Computing Summit (WiAC ’14)
Philadelphia, PA
United States

June 22-26, 2014
ISC'14
Leipzig
Germany

» View/Search Events

» Post an Event