In 2018, rising enterprise demand for hybrid cloud solutions will fuel new and expanded partnerships between traditional infrastructure vendors and hyperscale public cloud providers.
Vendor initiatives will target the challenge of managing workloads across hybrid and increasingly distributed IT environments, along with ways of simplifying the procurement, deployment and consumption of IT.
2017 saw a growing recognition that private cloud technology is both a realistic and desirable way to manage enterprise workloads, and can be used more efficiently through effective integration in conjunction with public cloud services. A common theme during the year’s industry events was envisaging and enabling multi- and hybrid cloud futures. At the same time, in 2017, data center infrastructure vendors from Cisco and Dell EMC to IBM and HPE continued to transform their solutions and services businesses. These transformations were a response to enterprise digitalization initiatives and recognition that in the future, IT will be hybrid, and must be able to span the full spectrum of enterprise locales from the cloud to core data centers to the network edge. In 2017, individual vendors went through quite different transformation processes: in addition to launching new solutions, technology companies acquired and integrated new businesses, and forged alliances with one another and with hyperscale cloud providers in order to fill out their portfolios. These developments were all driven by a competitive push to help enterprises modernize their traditional data center environments, capitalize on the benefits of hybrid cloud, and expand their ability to handle growing volumes of data at the edge of their networks. Continue reading “In 2018, Data Center Technology Will Become Smarter, Hybrid, More Distributed, and Easier to Consume”→
• How did a computer algorithm like Google’s AlphaZero manage to learn, master and then dominate the game of chess in just four hours?
• AlphaZero’s mastery of chess stemmed from the sheer, brute force of Google’s AI-specific Tensorflow processing units (TPUs) – 5,000 of them to be exact.
“How about a nice game of chess?” With that iconic line of dialog from what is one of my favorite films, the 1983 cold war sci-fi thriller WarGames, nuclear war was narrowly averted by a machine (named Joshua) capable of teaching itself how to play a game. This week another machine, one of Google’s DeepMind AI offspring, AlphaZero, did something similar in that it took four hours to teach itself how to play chess and then proceeded to demolish the best, highest rated chess computer, Stockfish. After 100 games, AlphaZero racked up 28 wins and zero losses. So much for more than a millenium of human effort in teaching a computer how to play chess. But how was this possible? Was this a fair match? How did a computer algorithm like AlphaZero manage to learn, master and then dominate the game of chess in just four hours? Continue reading “The Chess Dominance of Google’s AlphaZero Teaches Us More About Chips Than About Brains”→
At its annual user conference, customer experience management player Genesys introduced Kate, a personified artificial intelligence (AI) platform tailored to augment and automate multimodal customer interactions.
Genesys Kate, however, is not meant to compete with AI platforms such as IBM Watson or Salesforce.com Einstein. Instead Kate seeks to blend its own capabilities with those offerings, serving as an open platform.
Personified AI platforms – suddenly every technology vendor seems to have an AI persona that’s eager to strike up a one-on-one conversation. There’s of course IBM Watson, Amazon Alexa, Apple Siri, Google Assistant, Salesforce.com Einstein, and Adobe Sensei, but that somewhat lengthy list doesn’t even scratch the surface of what’s available when you bring AI bots like Mitsuku, Poncho, Melody, Rose, and my personal favorite, Dr. AI. And now we have Kate, a personified AI platform introduced by customer experience manager Genesys this week during its annual user conference. Continue reading “Genesys Jumps on the AI Bandwagon, Invites Others Along for the Ride”→
• Google wants to democratize AI and operationalize machine learning (ML) with the release of Google Cloud Machine Learning Engine, a platform that includes developer-friendly APIs and pre-trained data models.
• But what the company really needs isn’t just data, algorithms or even data scientists but instead a new breed of developers, who can build software that can anticipate outcomes.
It’s always the same at the end of a company’s keynote address. After all of the important messages have been conveyed and all of the product announcements have been made, a mid-level corporate mouthpiece will take the stage and provide the audience with some positive reinforcement of what went before. It’s like the closing credits of a film, something that may contain a nugget of interest to the cinephile. More often, it serves as filler, a thematic soundtrack to accompany attendees as they make for the exits.