Turbotodd

Ruminations on IT, the digital media, and some golf thrown in for good measure.

Archive for the ‘AI’ Category

IBM Brings Anaconda Open Data Science Platform To IBM Cognitive Systems

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IBM announced today that it is working with Continuum Analytics to offer Anaconda, a leading Open Data Science platform, on IBM Cognitive Systems.   Anaconda will also integrate with the PowerAI software distribution for machine learning and deep learning that makes it simple and fast to take advantage of Power performance and GPU optimization for data intensive cognitive workloads.

As one of the fastest growing fields of machine learning, deep learning makes it possible to process enormous datasets with millions or even billions of elements and extract useful predictive models. Deep learning is transforming the businesses of leading consumer Web and mobile application companies, and it is quickly being adopted by more traditional business enterprises as well.

IBM developed PowerAI to accelerate enterprise adoption of open-source machine and deep learning frameworks used to build cognitive applications.

PowerAI reduces the complexity and risk of deploying these open source frameworks for enterprises on the Power architecture and is tuned for high performance. With PowerAI, clients can realize the benefit of enterprise support on IBM Cognitive Systems HPC platforms used in the most demanding commercial, academic and hyperscale environments.

These Cognitive Systems are built with IBM’s POWER8 leveraging NVIDIA’s high-speed NVLink interface to NVIDIA’s Tesla Pascal P100 GPU accelerators. The CPU to GPU and GPU to GPU NVLink high bandwidth connections give a performance boost to deep learning and analytics applications. The CPU to GPU NVLink interface is only available on POWER8 CPUs.

“Anaconda is an important capability for developers building cognitive solutions, and now it’s available on IBM’s high performance deep learning platform,” said Bob Picciano, senior vice president of Cognitive Systems. “Anaconda on IBM Cognitive Systems empowers developers and data scientists to build and deploy deep learning applications that are ready to scale.”

The Anaconda platform brings powerful capabilities for large-scale data processing, predictive analytics, and scientific computing to simplify package management and deployment. Developers using open source ML/DL components will now be able to use Power as the deployment platform and take advantage of Power optimization & GPU differentiation for NVIDIA. 

Written by turbotodd

April 17, 2017 at 8:56 am

Posted in 2017, AI, anaconda, cognitive, power

A Chorus Of Artificial Intelligence

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It was a big weekend in music… and in artificial intelligence.

Ford Motor Company announced that it had made Detroit’s biggest investment yet in self-driving technology, acquiring a majority stake in artificial intelligence startup Argo AI for $1 billion.

Silicon Angle reported that Argo was founded by veterans of self-driving car projects at Google and Uber, and that Argo AI will become a subsidiary of Ford under the new deal.

“As Ford expands to be an auto and a mobility company, we believe that investing in Argo AI will create significant value for our shareholders by strengthening Ford’s leadership in bringing self-driving vehicles to market in the near term and by creating technology that could be licensed to others in the future,” said Ford President and Chief Executive Mark Fields.
– via SiliconANGLE

On a related AI front, Chorus.ai, a sound-centric AI firm looking to extract insights from audio, garnered a $16M Series A.

TechCrunch is reporting that Chorus will join conference calls, record and transcribe content in real-time, and then have its platform flag important action items and topics that came up over the duration of calls.

At press time, it was not yet clear what Chorus.ai would make of toilet sounds flushing in the background for those individuals who forgot to go on mute, but this blogger suspects it could lead to a whole other content types with respect to conference call actions.

Written by turbotodd

February 13, 2017 at 8:06 am

Apple Expected To Join Partnership On AI

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Apple Inc. is set to join the Partnership on AI, an artificial intelligence research group that includes Amazon.com Inc., Alphabet Inc.’s Google, Facebook Inc. IBM, and Microsoft Corp., according to Bloomberg.

Despite having initiated somewhat of a lead on the rest of the industry with the introduction of the Siri virtual assistant in 2011, poor Siri seems to have been held back in AI school.

The Partneship on AI is a tech industry body that was established to agree on best practices in the use of artificial intelligence. It was formed in September, with part of its brief to make recommendations in the areas of ethics, fairness, inclusivity, privacy and trustworthiness

Apple’s admission into the group could be announced as soon as this week, according to people familiar with the situation.

9to5 Mac suggests Apple’s reluctance to join may have been prompted by secrecy concerns. In addition to its ethics focus, the group has an emphasis on collaboration between researchers working for different companies.

Siri, fingers crossed…Siri, did you hear me?…SIRI!???!!!!

Written by turbotodd

January 26, 2017 at 8:12 am

Posted in 2017, AI, apple, siri

Machines Really Learning

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In a Wall Street Journal article published earlier today, Red Hat CEO Jim Whitehurst suggested “the incorporation of machine learning as an element of software is about to soar.”

He told the CIO Journal that currently only about 1% of software developers currently employ machine learning in their work, but that that percentage would rise to about one third of all developers over the next few years.

On a similar note, just last week the MIT Technology Review reported that the Google Brain AI research group also had software design a machine learning system used to benchmark software that processes language.

MIT wrote in its story, entitled “AI Software Learns to Make AI Software,” that:

If self-starting AI techniques become practical, they could increase the pace at which machine-learning software is implemented across the economy. Companies must currently pay a premium for machine-learning experts, who are in short supply.
– via MIT Technology Review

But don’t throw away all the humans just yet. The Google Brain researchers indicated that it took:

800 high-powered graphics processors to power software that came up with designs for image recognition systems that rivaled the best designed by humans.
– via MIT Technology Review

Paul Bunyan, meet Babe the Blue AI Ox.

Written by turbotodd

January 24, 2017 at 9:56 am

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