Google moving into "Hardware" as the Internet of things Era takes hold

Huffington Post - Tech news and opinion

Google's strategic move into selling own branded Mobile phones is another step in the merging of "Software plus Hardware" that Apple, Microsoft, Amazon and recently Facebook have realized at the making of the "Internet of Things" Era. This is the critical issue of not just providing the software and operating system but increasing the value in the devices that become the Interface to the Customer: the smart phone, the smart tablet/laptop of Microsoft Surface, the Smart Speaker of Amazon Echo and Alexa, and the Facebook Oculus Rift and Microsoft Hololens that are the new foundations of Natural Language speech recognition services and the VR Virtual Reality and AR Augmented Reality breaking now and into 2017 and onward. Google's long-term market is changing, the advertising revenue from search engines while still strong is now seeing new ways to search via speech or Virtual image recognition and virtual interaction Google has been late to realizing perhaps the shift to software hardware is where the Internet of Things may be shaping the market with the Connected Home, Connected Car and Connected Work through these devices. It's all about "market marking" beyond just the big cloud data centers and big data analytics to how to build out the edge of the cloud network with all these potentially billions of connected sensors and devices. If the Mobile phone is becoming the "remote control to this world" and platforms the "fabric of social networks and connected experiences" then Google like others is rushing to get into this space with stronger software and hardware offerings


7 ways AI will shape the future of work & higher ed - eCampus News

#artificialintelligence

With so many industries seeing the potential for artificial intelligence (AI) applications come to fruition, we will need highly trained workers to fill what is likely to be a rising demand for such skills. In fact, the number of LinkedIn members adding these skills to their profiles saw a 190 percent increase between 2015 and 2017. Software and IT services saw incredible growth in the past two years, but education, hardware and networking, finance, and manufacturing saw increases as well. In fact, AI is one of the top four specific technological advances (along with ubiquitous high-speed mobile internet, widespread adoption of big data analytics, and cloud technology) set to positively affect business in the 2018-2022 period. Machine learning and augmented and virtual reality are poised to likewise receive considerable business investment.


The #IoT and #Analytics @ThingsExpo #BigData #BI #AI #DX #MachineLearning

@machinelearnbot

The Internet of Things (IoT) promises to change everything by enabling "smart" environments (homes, cities, hospitals, schools, stores, etc.) and smart products (cars, trucks, airplanes, trains, wind turbines, lawnmowers, etc.). I recently wrote about the importance of moving beyond "connected" to "smart" in a blog titled "Internet of Things: Connected Does Not Equal Smart". The article discusses the importance of moving beyond just collecting the data, to transitioning to leveraging this new wealth of IoT data to improve the decisions that these smart environments and products need to make: to help these environments and products to self-monitor, self-diagnose and eventually, self-direct. But one of the key concepts in enabling this transition from connected to smart is the ability to perform "analytics at the edge." Shawn Rogers, Chief Research Officer at Dell Statistica, had the following quote in an article in Information Management titled "Will the Citizen Data Scientist Inherit the World?": "Organizations are fast coming to the realization that IoT implementations are only going to become more vast and more pervasive, and that as that happens, the traditional analytic model of pulling all data in to a centralized source such as a data warehouse or analytic sandbox is going to make less and less sense.


The #IoT and #Analytics @ThingsExpo #BigData #BI #AI #DX #MachineLearning

@machinelearnbot

The Internet of Things (IoT) promises to change everything by enabling "smart" environments (homes, cities, hospitals, schools, stores, etc.) and smart products (cars, trucks, airplanes, trains, wind turbines, lawnmowers, etc.). I recently wrote about the importance of moving beyond "connected" to "smart" in a blog titled "Internet of Things: Connected Does Not Equal Smart". The article discusses the importance of moving beyond just collecting the data, to transitioning to leveraging this new wealth of IoT data to improve the decisions that these smart environments and products need to make: to help these environments and products to self-monitor, self-diagnose and eventually, self-direct. But one of the key concepts in enabling this transition from connected to smart is the ability to perform "analytics at the edge." Shawn Rogers, Chief Research Officer at Dell Statistica, had the following quote in an article in Information Management titled "Will the Citizen Data Scientist Inherit the World?": "Organizations are fast coming to the realization that IoT implementations are only going to become more vast and more pervasive, and that as that happens, the traditional analytic model of pulling all data in to a centralized source such as a data warehouse or analytic sandbox is going to make less and less sense.


Way Bigger Data Means Big Disruption -- Time To Plan For The Internet Of Things

Forbes - Tech

Even in its nascent form today, IoT is changing the way we interact with our physical environment and how we learn from it too. Besides bringing us Internet-enabled light bulbs and self-driving cars, the IoT will bring to the physical world the kind of behavioral modeling and analytics that have been embedded in the digital world for years. Businesses are already able to apply lessons from the data they gather from IoT-enabled sensors to their own operations, and early adopters stand to reap rewards from this data approach, using it to guide development of next-generation consumer devices and even open up entirely new market segments. Analysts predict there will be somewhere between 20 billion and 30 billion digitally connected devices by 2020, equating to a multi-trillion-dollar economic impact. Fueling much of that growth will be data--so much, in fact, that the torrent of data generated by the IoT will make big data look like a trickle in comparison.