2017 Big Data Learning Technical Review 
Paul Hobcraft
DECEMBER 2, 2016
So if there was ever a time to clear the existing innovation agenda and rework the entire space for innovating, it is about to become the pressing reality as we enter into 2017. We have seen an amazing transformation in how we socialize through the use of technology and the smartphone. The Merging Conditions and Forces.
Daniel Burrus
DECEMBER 13, 2016
These trends for 2017 highlight enormous game-changing opportunities. Artificial Intelligence (AI), Advanced Machine Learning and Cognitive Computing Applications. Big Data and the use of High Speed Data Analytics. Separating good data from bad data will also become a rapidly growing service.
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Acuvate
NOVEMBER 22, 2019
In 2017, The Economist reported that data is the oil of the digital era and has dethroned oil as the most valuable resource in the world. But unlike oil, extracting, maneuvering, filtering, refining and storing the continuous stream of data from various internal and external sources is a herculean task.
Open Innovation EU
OCTOBER 24, 2017
In his 2016 book the Fourth Industrial Revolution Klaus Schwab mentions 6 basic technologies that are based on AI and currently impacting business: 1) the Internet of Things (IoT), 2) Autonomous Vehicles, 3) Advanced Robotics, 4) 3D-printing, 5) new materials and 6) the biological revolution. From Machine Learning to Cognitive Learning.
The Inovo Group
OCTOBER 10, 2018
New software technologies and tools will make it possible to create Startup Collaboration Platforms that enable the relationships to become more automated, structured and efficient. They had recognized that many innovative initiatives fail in the early stage of development due to, among other things, a lack of secure funding.
ITONICS
MAY 14, 2018
But we have good news for all those who have not yet taken the step into the right direction: Although every innovation has something new and unique, we can learn significantly from the companies that get it right and create a first how-to-plan based on their workflows, structures, and practices. million in 2017 (23.4% The place to be.
Linda Bernardi
JULY 24, 2017
It is due to the confluence of six factors: 1. Mega Data 2. The reasons are discussed in detail in my upcoming book, The Inversion Factor (MIT Press, October 2017), but I will unpack some of them here. We are past Big Data (which occurred with the advent of mobile, apps and social media), and are in the Hyper-Data stage.
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