When living and operating in a market largely dominated by a vendor that isn't you, the strategy you must deploy is one of focus. In the early days of Power, IBM tried to take on Intel head to head and that just wasn't working. You can understand why IBM thought it could do this; it was once the most powerful company in the world. But, like Microsoft, Intel's strength largely came from providing technology to firms like IBM, and IBM's decline in the late 1980s and early 1990s not only weakened it substantially, it collectively strengthened other firms. Much like AMD, which has always been weaker than Intel, IBM needed to pick its battles, and given that the company still pretty much owns the market for enterprise-class AI with Watson, and that this segment is slated to become the most lucrative in the industry for servers over the next decade, it chose wisely to make this one of its critical areas of focus.
Companies across industries are experimenting with and using machine learning, but the actual adoption rates are lower than it might be seem. According to a 2017 SAP Digital Transformation Study, fewer than 10% of 3,100 executives from small, medium and large companies said their organizations were investing in machine learning. That will change dramatically in the coming years, according to a new Deloitte report, because researchers and vendors are making progress in five key areas that may make machine learning more practical for businesses of all sizes. There is a lot of debate about whether data scientists will or won't be automated out of a job. It turns out that machines are far better at doing rote tasks faster and more reliably than humans, such as data wrangling.
What do tomorrow's automakers have to do with net-zero buildings? Why it's important: This will transform the design and technology requirements for buildings in order to accommodate personal EVs and even electric fleets What It Is: Drillinginfo, a SaaS provider for the energy industry, has acquired Pattern Recognition Technologies (PRT), an energy forecasting software player. Why It Matters: Adding PRT's machine learning capabilities to predict energy consumption will allow Drillinginfo to enter horizontal markets in energy data analytics. This maneuver also bolsters Drillinginfo's North American customer base, particularly in clean energy data analytics. Why It Matters: Incumbents are reacting to the transition towards smart products by picking up smart home specialists.
Companies say the new tools make them more efficient and give employees more opportunities to do new kinds of work. But the software also is starting to take on management tasks that humans have long handled, such as scheduling and shepherding strategic projects. Researchers say the shift could lead to narrower roles for some managers and displace others. When Shell wanted help evaluating digital business models in the car-maintenance sector, executives plugged the project into an algorithm that scanned for available Shell staffers with the right expertise--and assigned the job with a click. Shell uses machine-learning software designed by Boston-based Catalant Inc. to match workers and projects.
Technological advances like artificial intelligence, machine learning and big data are impacting the power sector as well, making it imperative for producers to re-skill resources, a senior official of Tata Power said. "With technological disruptions like artificial intelligence, machine learning, big data, augmented reality etc. that are impacting the power sector as well, it has become imperative to re-train and re-skill resources for emerging careers where the demand is more than the supply," Tata Power Chief Human Resource Officer Jayant Kumar said. Addressing the seventh Power HR Round Table organised by the University of Petroleum & Energy Studies (UPES), Kumar said, "Curiosity, courage and comfort with technology are the traits of a future digital worker." CEOs and HR heads of leading Indian companies in the power sector such as Tata Power, Power Grid, GMR Energy, Adani Green Energy, and DB Power deliberated on various challenges faced by the sector today and possible solutions, UPES said in a statement. "Power distribution companies (Discoms), due to their nature of work, have access to huge consumer data and they can use this data to foray into other allied businesses just the way cab aggregators are delivering food or e-commerce companies providing video-on-demand services," Ashis Basu, CEO (Corporate), GMR Energy, suggested.
Artificial intelligence is not new but, suddenly, everyone seems to be talking about it. We have hit an inflection point with computing power and data that is finally allowing for commercial applications of this technology, and that's what all the excitement is about. It's only going to get faster and better from here on out. Along with talk about the new possibilities, there is also a lot of fear about people possibly losing their job to a robot, or even becoming irrelevant. Despite the wow factor of being able to shout a command at Siri or Alexa and have a task performed, when you get right down to it the tasks they are performing are rudimentary.
On the two-year anniversary of the Paris climate accord, the world's government, civic and business leaders are coming together in Paris to discuss one of the most important issues and opportunities of our time, climate change. I'm excited to lead the Microsoft delegation at these meetings. While the experts' warnings are dire, at Microsoft we believe technology advances can help us better understand and address the environmental issues facing our planet. That's why we're announcing in Paris that we are broadening our AI for Earth program with an expanded strategic plan and committing $50 million over the next five years to put artificial intelligence technology in the hands of individuals and organizations around the world who are working to protect our planet. At Microsoft, we believe artificial intelligence is a game changer.
To further enhance its research capabilities Eco Marine Power announced today that it will begin using the Neural Network Console provided by Sony Network Communications Inc., as part of a strategy to incorporate Artificial Intelligence (AI) into various ongoing ship related technology projects including the further development of the patented Aquarius MRE (Marine Renewable Energy) and EnergySail. The Neural Network Console is an integrated development environment using deep learning for AI creation and has been used in deep learning applied technology development within Sony since 2015. Various functions are included such as recognition technology and a full-fledged GUI (graphical user interface) and these allow for deep learning programs to be developed. Deep learning refers to a form of machine learning that uses neural networks modelled after the human brain and is notable for its high versatility with applications in a wide variety of fields including signal processing, and robotics. An initial area of focus will be on studying how the Neural Network Console and AI can assist with the development of the automated control system for EMP's EnergySail.
In a guest blogpost, Peter Pugh-Jones, head of technology at SAS UK & Ireland, reflects on how the analytics industry is evolving and what organisations need in a data-driven economy. Check out the latest findings on how the hype around artificial intelligence could be sowing damaging confusion. Also, read a number of case studies on how enterprises are using AI to help reach business goals around the world. You forgot to provide an Email Address. This email address doesn't appear to be valid.