In the right architecture, machine-learning functionality takes data analytics to the next level of value. Editor's note: This guest post (translated from Italian and originally published in late 2016) by Lorenzo Ridi, of Google Cloud Platform partner Noovle of Italy, describes a POC for building an end-to-end analytic pipeline on GCP that includes machine-learning functionality. "Black Friday" is traditionally the biggest shopping day of the year in the United States. Black Friday can be a great opportunity to promote products, raise brand awareness and kick-off the holiday shopping season with a bang. During that period, whatever the type of retail involved, it's also becoming increasingly important to monitor and respond to consumer sentiment and feedback across social media channels.
The modern world seems really fast and dynamic with a multitude of new products being launched. Marketing agencies are making fortune by monitoring the markets and delivering reports on consumers' opinions. For today, the feedback analysis is a separate area, let's say a growing industry with an array of products and services. And the prices for those services are pretty exorbitant. So, do vendors have a chance to cut down expenses?
Even taking into consideration the latest smartwatch models introduced recently by Apple and Samsung, it has to be admitted that these gadgets haven't been doing as well as vendors hoped. It could be that the size and weight are still off-putting to many users -- or it could be that many don't want to pay several hundred dollars for what can be viewed as a glorified Fitbit. However, that hasn't put off a number of vendors who are still hoping to make a name for themselves in the Dick Tracy sweepstakes. One that made a bit of a splash on crowdfunding site Indiegogo has just made its appearance in the market: the CoWatch, with hardware from a tech startup called iMCO, software from a company called Chronologics, and the ability to access Amazon's Alexa voice controller. I had a chance to try out the CoWatch and found it to be a highly interesting project -- one that feels not quite complete but that may have a good deal of potential.
The last decade was dedicated to building a'mobile-first' world where smartphones took control over the advancements in technology and lifestyle. Lately there has been a dramatic change in the course of action. The big shots of technology have set their sail to build an'AI First' world to unlock capabilities that were unthinkable a few years ago and build a future twice as good. Google Assistant, Amazon Echo, Facebook Spaces and Tesla's self-driving cars stands testimony to this technology shake-up. This technology'Renovation' has already begun and will be in its full swing in the next 3-4 years.
"Everything is true…everything anybody has ever thought," Philip K. Dick – Do Androids Dream of Electric Sheep. It is impossible to escape from the fact that technology, and increasingly artificial intelligence (AI), has transformed everyday life. It all started with how we play our music, but Apple's Siri and Amazon's Alexa (along with other similar "virtual assistants") now have a daily interface with many of us. We are also, increasingly, now daily users of the Internet of Things (IoT) – connecting up smart fridges, boilers and alarm systems, each controllable from a smartphone. The "everyday" form of AI is almost unavoidable in the modern home, but, while not necessarily as obvious to you and me, there is also an ongoing, yet unseen growth in AI in the manufacturing sector.