This story was delivered to BI Intelligence Apps and Platforms Briefing subscribers. To learn more and subscribe, please click here. A team of Microsoft researchers has achieved the lowest error rate for speech recognition on record at 6.3%, overtaking prior record holder IBM Watson's 6.9%. The news brings the company one step closer to getting computers to understand speech as well as a person, and helps in its efforts to provide conversation as a service through tech like Cortana, Skype Translator, and other language-related cognitive services. Voice is going to emerge as a dominant computing interface.

Yes, the title is a precious mess. But "Big Data" was always defined as a problem statement. For some, it represented the challenge of acquiring data from new sources. For others, it meant the herculean task of building a scalable infrastructure that could manage all the data. For a brave few, it meant the arcane art (or presumptive science) of extracting value from data using advanced data analysis techniques and tools.

Additionally, we'll have our Oracle Advanced Analytics, Machine Learning and R demo pod in the Oracle Demo Campgrounds. Stop by to say "hello" and see the latest developments.

Kerry leads three important functions at Rubikloud: people, sales, and technology disruption. Rubikloud helps retailers monetize their data to power personalized campaigns through the use of advanced machine learning techniques, effectively bridging the gap between marketing automation and retail management consultants. In his role, Kerry works to manage and maintain a thriving company culture that recruits the best and brightest in the industry, while also maintaining relationships with global retailers and investors. He is passionate about machine learning and big data, and enjoys providing enterprise retailers with the tools and knowledge needed to enhance their overall business goals. If you're only using big data to target consumers based on demographics or purchase history, you're making a mistake that will cost your company a significant amount of revenue.

This introductory Machine Learning course taught by top Caltech professor Abu-Mostafa covers theory, algorithms and applications, with focus on real understanding.

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Computer programs have defeated humans in Jeopardy!, chess and Go. Now a program developed at Case Western Reserve University has outperformed physicians on a more serious matter. The program was nearly twice as accurate as two neuroradiologists in determining whether abnormal tissue seen on magnetic resonance images (MRI) were dead brain cells caused by radiation, called radiation necrosis, or if brain cancer had returned. The direct comparison is part of a feasibility study published in the American Journal of Neuroradiology today. "One of the biggest challenges with the evaluation of brain tumor treatment is distinguishing between the confounding effects of radiation and cancer recurrence," said Pallavi Tiwari, assistant professor of biomedical engineering at Case Western Reserve and leader of the study.

Applying machine learning in marketing automation is not rocket science. It has one and only one purpose: make marketers' life easier. It helps you focus only the most important data, performs the must-have, but repetitive todos. Therefore your scope of duties will move to a more strategic position as a marketer. I'm about to I show you 4 examples when machine learning in marketing automation could truly help you.

Recently, Google added Try the API boxes on the product pages of each of its Cloud Machine Learning APIs: Cloud Vision API, Speech API and Natural Language API. Now anyone can instantly experience the power of Google's machine intelligence on their own images, voice and text. Let's see how it works. Using the label detection method of the API, Cloud Vision executes image content analysis on the uploaded image. Looks like Cloud Vision's machine intelligence is smart enough to understand not just the object, but also the context ("halloween," "holiday," "carving").

At a theoretical level, the concept of artificial intelligence has fueled and sharpened the philosophical debates on the nature of the mind, intelligence, and the uniqueness of human beings. Insights from the field have proved invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language. Today, we're continuing our Q&A with Maggie Boden, Research Professor of Cognitive Science at the University of Sussex, and one of the best known figures in the field of Artificial Intelligence. ANNs are computer systems made of large number of interconnected units, each of which can compute only one (very simple) thing. They are (very broadly) inspired by the structure of brains.