Remove 2016 Remove Artificial Inteligence Remove Big Data Remove Technology
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AIMMO bags $12M Series A to advance data labeling technology  

TechCrunch

Most artificial intelligence models are trained through supervised learning, meaning that humans must label raw data. Data labeling is a critical part of automating artificial intelligence and machine learning model, but at the same time, it can be time-consuming and tedious work.

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The Future of Artificial Intelligence: How It Will Impact Your life?

Xicom

You already have special kinds of locking system been used on your phones that involve Artificial Intelligence based face recognition. Many companies are working and doing experiments on auto-car technology, i.e. Cars driving themselves. Applications of AI include speech recognition, expert systems and machine vision.

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It's time to establish big data standards

O'Reilly Media - Data

The deployment of big data tools is being held back by the lack of standards in a number of growth areas. Technologies for streaming, storing, and querying big data have matured to the point where the computer industry can usefully establish standards. Security and governance. Metadata management.

Big Data 126
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AI Chihuahua! Part I: Why Machine Learning is Dogged by Failure and Delays

d2iq

Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.

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Ocrolus lands $80M at a $500M+ valuation to automate document processing for fintechs and banks

TechCrunch

Ocrolus uses a combination of technology, including OCR (optical character recognition), machine learning/AI and big data to analyze financial documents. In a nutshell, the company aims to help lenders make “faster, data-driven decisions.” operations. We wanted to create a new way of doing this.

Fintech 243
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Real-time in-vehicle data and AI technologies provide the key to predictive maintenance

Capgemini

According to a new report by the Capgemini Research Institute, Accelerating automotive’s AI transformation: How driving AI enterprise-wide can turbo-charge organizational value , artificial intelligence (AI) technologies are key to the success of this predictive-maintenance approach.

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Supercomputing Predictions for 2016

CTOvision

Wondering where supercomputing is heading in 2016? New Processor Technologies. The leader of this technology is currently Intel, with their next generation Xeon Phi coprocessor, which is a hybrid between an accelerator and general purpose processor. This is something to keep an eye on throughout 2016. Data-Tiering.