If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
In the consumer report, we are number one once again and just like the Q7, in the consumer report it also occupies the first position as the best luxury SUV. And I think this power of the brand makes it possible for us to grow significantly. There are couple of models which have not even be launched yet in this market, models which we already know here, for instance the S4, the A5, and the entirely new A5 Sportback. They are now being launched in the United States. All new models for this market, and I assume that this year once again we are going to experience very solid growth in the United States. And the question so whether we spend more money for this? I can tell you we even spend less money in form of sales discounts because of the powerful brand and the relatively young product portfolio. So you would take the second part?
Over the past four years, the role of chief marketing officers has changed. Once, CMOs led small silos that focused on growing business impact across paid media channels. Now, CMOs are increasingly being asked to manage company impact and growth across an array of owned digital media and customer relationship channels -- with robust budgets to match. While the breadth of technology continues to grow, separate tools themselves do not necessarily equate success. Budgets for marketers are slowly climbing, and responsibilities are broadening, according to Gartner's 2016-2017 CMO Spend Survey.
The potential of AI is often praised by academics, technologists and the press, but there is little information about how to adapt to this new technology and its influence on modern-day jobs. How should managers prepare themselves to ensure that they will excel in this new world of artificial intelligence? Accenture recently conducted a research, surveying 1,770 managers from 14 countries and 37 interviewed executives responsible for the digital transformation of their company. By identifying this data, the researchers established five practices that is essential for a manager to master, to be successful. The survey, conducted by Vegard Kolbjornsrud, Richard Amico and Robert J. Thomas, found that managers spend more than half their time on administrative coordination and control tasks, despite what levels they are managing.
Robotic cars are great at monitoring other cars, and they're getting better at noticing pedestrians, squirrels, and birds. The main challenge, though, is posed by the lightest, quietest, swerviest vehicles on the road. "Bicycles are probably the most difficult detection problem that autonomous vehicle systems face," says UC Berkeley research engineer Steven Shladover. Nuno Vasconcelos, a visual computing expert at the University of California, San Diego, says bikes pose a complex detection problem because they are relatively small, fast and heterogenous. "A car is basically a big block of stuff.
And so the insurrection is beginning. Last week Japanese insurance Fukoku Mutual Life Insurance announced that it was going to be replacing 30 staff with an artificial intelligence that would be calculating payouts (although, it noted, with human oversight still making final approvals). The technology would improve productivity by 30% and the firm expected to save some 140m Yen a year (around £1m) after the 200m Yen investment. Now I'm sure that this implementation of IBM's Watson technology (remember: Watson was the man who predicted in 1943 a global market for maybe five computers) will be very whizzy. But excuse me whilst I contend that Fukoku's PR make this AI sound like every IT business case I've ever seen: cost savings through headcount reduction blah blah, productivity gains blah blah.
For a project to succeed, "You must get on the ground and listen to your people," says Travis Perkins CIO Neil Pearce. Neil Pearce, CIO at Travis Perkins, is running a major transformation programme for the timber and builders merchant. The initiative involves a shift from legacy systems to digital services. The transformation will feature technology from big data to natural language processing, to improve the quality of service for customers. Pearce says the potential business benefits will be great for the firm's major retail brands, which include Tile Giant, Toolstation, and City Plumbing Suppliers.
Unless a "neutral" third party publishes them, we tend to view benchmarks as self-serving exercises that vendors typically stack in their own favor. But recent benchmarks issued by Cloudera and Hortonworks for their SQL on Hadoop engines point to something serious going on. In an era of Spark hype, SQL remains table stakes for Hadoop platforms. Yes, you can perform machine learning, model customer ecosystems as social graphs, run streaming, and conduct sentiment analysis, but for most organizations, the first question they often ask is how fast is the interactive SQL. Using Hadoop only for SQL query might seem like a waste, given its appeal to R or Python developers.
We're experiencing artificial intelligence every day of our lives, even if we don't know it or just take it for granted. Whether it's Spotify using machine learning to give us a better music playlist, or Apple using natural language processing to make Siri our digital assistant, AI is truly everywhere. As the leader of Salesforce's Marketing and Analytics Clouds, I want to outline what exactly intelligence means for marketing and analytics professionals. Starting from the top, we all know and can understand that customers expect faster, smarter, more personalized engagement. But delivering on these expectations is challenging.
Apple CEO Tim Cook unveils the new iPhone 7 at the company's event in San Francisco Sept. 7. (Photo: Marco della Cava, USA TODAY) SAN FRANCISCO - Apple may be thinking twice about getting into the car business. The Cupertino iPhone-maker, which has never publicly acknowledged it is working on an automobile, has reportedly laid off employees associated with its so-called Project Titan, according to anonymous sources quoted by The New York Times late Friday. The report cites three employees as saying Apple had fired "dozens of employees" off the automotive team, which just two months ago was taken over by Bob Mansfield, a top executive in the Steve Jobs era who had been coaxed to rejoin the company. Apple declined to comment on the report. The company's shares (AAPL) didn't move much after-hours on the news, but fell during trading 2% to 103.13.
This week saw the eruption of a vendor spat when NVIDIA, developer of GPUs widely used in the AI/machine learning market, alleged foul play against Intel in recent comparative benchmark results involving Intel's Xeon Phi processors. While NVIDIA makes some fair points about the methodology employed by its rival, Intel announced impressive news of its own on the AI/Xeon Phi front. First, let's look at NVIDIA's criticism of Intel that came in the form of a blog post by Ian Buck, vice president of accelerated computing, who declared that Intel compared Xeon Phi to out-of-date NVIDIA benchmarking data. "Intel used Caffe AlexNet (benchmarking) data that is 18 months old, comparing a system with four (NVIDIA) Maxwell GPUs to four Xeon Phi servers," Buck wrote. "With the more recent implementation of Caffe AlexNet, publicly available here, Intel would have discovered that the same system with four Maxwell GPUs delivers 30 percent faster training time than four Xeon Phi servers.