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CIO Applications Weekly Brief

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Editor's Pick (1 - 4 of 8)
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Robotic Refactoring the Workplace

Robotic Refactoring the Workplace
Philip D. Heermann, Senior Manager, Sandia National Laboratories

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WiFi Networks: Shifting from Providing a Service to Improving the...
Daniel J. Strojny, Interim Associate Director of Network and IT Operations, University of St. Thomas

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Breaking the Stereotypes in the Development of AI
Yves Jacquier, Executive Director, Production Studio Services, Ubisoft

Operationalize Machine Learning

Operationalize Machine Learning
Zongjie Diao, Director of Product Strategy and Management, Data Center Compute Group, CISCO

Where is AI Already Having an Impact on Business?

Where is AI Already Having an Impact on Business?
David Wirt, VP, ASEAN & Greater China, Pure Storage

Artificial Intelligence in the Biopharma and Healthcare Sector

Artificial Intelligence in the Biopharma and Healthcare Sector
Ronald Dorenbos, Associate Director Materials & Innovation, Takeda

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The Essential AI Technologies

By CIO Applications| Wednesday, May 29, 2019
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FREMONT, CA – The technological boom of the twenty-first century has rocketed artificial intelligence (AI) and machine learning (ML) to new heights, forcing organizations to clamor for best talent and skill in these fields. However, the supply of talented and qualified professionals falls short of demand.

Over the years, many tech professionals have tried to assimilate the technologies associated with AI and ML to meet the rising demand. But, having sound knowledge of learning languages is not sufficient to stand out in the world of technology. With the constant digital flux and evolution, there is no telling which technology will dominate the future.

Nonetheless, AI has facilitated the rapid transformation of the technological sphere. Several revolutionary AI technologies have cemented its position as the most trending technology of this century; for instance, Keras, Torch, Caffe, TensorFlow, Theano, and Microsoft Cognitive Toolkit, among others.

Keras, an open source software library, focuses on streamlining the design and creation of deep learning models. It is written with Python and can be deployed along with other AI technologies. The simplified and quick-prototyping platform runs on both CPUs and GPUs.

Torch is one of the first AI technologies launched in the last two decades. The ML library possesses a variety of algorithms with deep learning capabilities. The open source framework facilitates speed and flexibility, eliminating any complexities in the process.

Caffe is relatively more recent compared to the other AI technologies. The AI platform encourages innovation through its expressive architecture. Its primary benefits include speed, expressiveness, and modularity.

TensorFlow is an open source ML framework that can be deployed across different platforms. Developed by Google, it has been adopted by several tech giants such as eBay, Dropbox, Intel, and Uber. It also facilitates the use of flowgraphs to develop neural networks.

Theone, on the other hand, is an open source Python library which can be utilized to design and develop ML models. It is one of the oldest libraries and is considered an industry standard. It has assisted in streamlining the processes of optimizing, defining, and assessing mathematical expressions.

Microsoft Cognitive ToolKit is an AI solution which facilitates the enhancement of ML projects. The open source framework has the capability of training specific algorithms to work like the human brain.

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