Nvidia introduced Titan X, a new chip that is a successor to a current chip with the same name, targeted at the high-end gaming and artificial intelligence communities. Priced at $1,200 and available beginning August 2, the new Pascal-based Titan X chip offers 12 billion transistors, compared to seven billion on a high-end Intel chip. The new Titan X will be available as an add-on card for PCs. Nvidia’s closest competitor, Advanced Micro Devices (AMD) offers a similar chip for PCs and game consoles. Continue reading Nvidia Rolls Out Titan X Chip for Games, Artificial Intelligence

Image recognition, or computer vision, is the foundation of new opportunities in everything from automotive to advertising. Its growing importance is such that the upcoming LDV Vision Summit, an annual conference on visual technology, is now in its third year. Computer vision has expanded through trends that have benefited other forms of AI, including open source, deep learning technology, easier programming tools and faster, cheaper computing, opening up opportunities for a wide range of businesses. Continue reading Image Recognition Tech Paving the Way for Future Advances

Google just indicated one of its future initiatives when Amit Singhal, who oversees the Google search engine, stepped down, and was replaced by John Giannandrea, who oversees Google’s work in artificial intelligence and, by association, what’s called “deep learning.” Google has already used deep learning to reinvent Search, via RankBrain, a deep learning system to generate responses to search inquiries. As of October of last year, RankBrain has grown to handle a “large fraction” of the queries to the search engine. Continue reading Google Sees Future in Artificial Intelligence and Deep Learning

Baidu, a Chinese company best known for its Internet search engine, has entered the competition with other Internet companies and automobile manufacturers to create an autonomous vehicle. The company has already invested heavily in artificial intelligence and developed software called the Baidu AutoBrain System, which automatically records 3D road data and recognizes objects and road lanes. This expertise may help Baidu gain an edge over Google, General Motors, Tesla and Ford. Continue reading Baidu Joins the Race to Get Self-Driving Vehicles on the Road

During the Nvidia keynote at CES 2016, CEO and co-founder Jen-Hsun Huang introduced a new computer for autonomous vehicles called the Drive PX2. Following last year’s Drive CX, the PX2 touts processing power equivalent to 150 MacBook Pros, according to Huang. The lunchbox-sized, water-cooled computer features 12 CPU cores that support eight teraflops and 24 “deep learning” tera operations per second. As a result, the PX2 can reportedly process data in real time from 12 video cameras, radar, lidar and additional sensors to enhance the self-driving car experience. Continue reading CES: Nvidia Unveils New ‘Supercomputer’ for Self-Driving Cars

When Tesla released all of its patents to the public in 2014, it jumpstarted the electric car ecosystem while continuing to succeed. Facebook made its data-center architecture available to the masses, still making a tidy $12+ billion in revenue last year. Open source code is now fueling tremendous innovation and digital capabilities. Whereas companies in the past dominated by using licensed software to create monopolies, today’s companies relying on open source code differentiate themselves by the services they offer. Continue reading Open Source Speeds Developments in Artificial Intelligence

Google is now relying on artificial intelligence, with a system dubbed RankBrain, for a small but significant part of its search business. Since Google is identified with search, keeping on the bleeding edge of search technology is critical to its dominance, and Google has been researching artificial intelligence — software that learns about the world — for over five years. Prior to launching RankBrain for search, Google has been a big corporate sponsor of AI, invested in it for videos, speech and translation. Continue reading Google Using RankBrain Artificial Intelligence Tech for Search

Internet users are typically more engaged when accessing websites and social platforms that include photos and videos. Marketing firm Shift, for example, notes that readers are five times more likely to click an embedded link if a tweet includes an image. As a result, companies are now developing software solutions for sifting through the millions of online images in an effort to help brands, advertisers and e-commerce players identify what draws viewers. EyeEm Mobile and Neon Labs are among those looking to enhance the power of online visuals. Continue reading Companies Develop Tools for Sifting Through Online Images

The latest trend in artificial intelligence involves implementing a much more efficient microprocessor rather than a whole cloud computing system to power deep learning research. These microprocessors, or graphical processing units (GPUs), are great at math-crunching skills, which makes them ideal for deep learning networks. Now, companies such as Google, Facebook, and various labs that run supercomputers, are using GPU-based computers to power their AI and deep learning operations. Continue reading AI: GPU-Based Computing is Proving Ideal for Deep Learning

Startup Clarifai has developed artificial intelligence technology based on deep learning that can identify what is in a video. This ability could be significant for search engines, which currently have to rely on textual clues around a video to guess what might be in it. Clarifai’s AI has the ability to identify objects, in addition to letting users know exactly when those objects will appear in the video. This technology could be used to help advertisers and other companies analyze their videos. Continue reading Clarifai’s Artificial Intelligence Can Recognize Video Content

Viv Labs, a startup founded by three of the people who developed Siri for Apple, is currently working on an artificial intelligence technology that will truly be able to perform tasks at the sound of a voice command. Unlike Siri, the new AI named Viv will be able to teach itself to perform almost any function, not just the ones that are programmed. The AI will also get to know its user, recognize the services that the user prefers, and eventually know what the user needs before it is stated. Continue reading Siri Creators Build a New Improved AI That Can Teach Itself

By analyzing the acoustic properties of songs on Spotify, intern and PhD student Sander Dieleman hopes to advance the streaming service’s recommendation algorithms to aid users in discovering new and lesser known music. Rather than basing recommendations on the choices people with similar tastes make, they would be based on songs the user listens to. This method, which requires deep learning, would then mix more obscure but user relevant songs into the recommendations. Continue reading Spotify Intern Creates System to Improve Recommendations

Twitter announced that it has acquired an artificial intelligence startup known as Madbits. The social network is buying into Madbits’ technology that can search an image and understand its content. This new image search engine is based on deep learning, a type of AI that relies on convolutional neural nets, much like a human’s network of neurons in the brain. Twitter is just the latest in a line of tech companies to invest in this type of technology. Continue reading Twitter Acquires AI Startup Madbits, Explores Image Search

Netflix has been experimenting with new methods of artificial intelligence to improve its products. The streaming service has plans to begin using deep learning models, and while it has yet to specify what exactly it will be improving, the service is likely to use the tech for enhancing its movie recommendations feature. Other companies have also begun putting deep learning into practice in order to train their systems to better recognize text and images, as well as their meanings. Continue reading Netflix Will Use Deep Learning to Improve Recommendations

Facebook is looking to expand its Graph Search algorithms to account for the use of slang and expressions, and translate them into searchable key words. The company adjusted its search algorithms in January, and the changes mostly worked. The new algorithms signal the beginning of new ways to search user information using natural and nuanced language, and provide more personalized ads. Other tech companies are looking into similar technologies. Continue reading Facebook Turns to Deep Learning to Grow Search Possibilities