For the connected consumer, machine learning is now a key enabler, from on-demand translation services, to weather forecasting, to guessing what users want based on where they are and what they've been doing. But only a third of companies IDC surveyed in 2017 said they had plans to use machine learning inside the enterprise. Lack of familiarity and a talent gap are some of the reasons enterprises have been reluctant to embrace this set of techniques. As with any essential technology, companies can get started with a clearer sense of the fundamentals. What is machine learning, and how does it differ from traditional programming?

John Fremont is the Go to Market lead for Artificial Intelligence at Accenture in North America. Previously the Chief Revenue Officer and a managing partner at Chaotic Moon (acquired by Accenture in mid-2015) and the Global head of Digital Product Creation for Accenture, Fremont has been in the AI space for years, driving clients and partners to understand the impact and complexity of the impending transformation. He contributed to a recent Salesforce panel on Artificial Intelligence, and we took some time with him to discuss his take on the impact of AI on business. I think the fundamentals of business strategy will stay quite consistent - in the sense that the overarching goals will still be to create more efficiency, drive more profitability and the like. However, there is a major shift underway - in which a company's operations and their interactions with customers are taking place increasingly in the digital world. This digitalization allows for a lot more data collection.

Suppose we have coins with the following denominations: 5 cents, 4 cents, 3 cents, and 1 cent, and that we need to determine the minimum number of coins to create the amount of 7 cents. In order to solve this problem we can use a technique called "Heuristics". Webster1 defines the term Heuristic as "involving or serving as an aid to learning, discovery, or problem-solving by experimental and especially trial and error methods". In practice, this means that whenever problems get too complex to find the guaranteed best possible solution using exact methods, Heuristics serves to employ a practical method for finding a solution that is not guaranteed to be optimal, but one that is sufficient for the immediate goals. For some problems, tailored heuristics can be designed that exploits the structure within the problem.

Accelerating trends in artificial intelligence (AI) and robotics point to significant economic disruption in the years ahead. Together, machine learning, natural-language recognition, biometrics, and decision management are converging toward what the World Economic Forum has described as the Fourth Industrial Revolution. To this point, technology has consistently generated more jobs than it destroys--but many now wonder if "this time is different." According to McKinsey & Company, half of all existing work activities could be automated by currently existing technologies, saving some $16 trillion in wages. Forecasts indicate that revenues from AI will expand from the current $8 billion to more than $47 billion by 2020.

Hey Accenture, are you aware that your PR firm is pitching your latest corporate beta for a creepy face and emotion-monitoring algorithm as a party trick? Do you know what a party is? Have you read the definition? Would you call requiring people to download an app before they can get into an event a party-time kind of thing to do? Would you say that demanding that people scan their faces so they can be recognized by an algorithm fun times? Does having that same algorithm watch and record every interaction that happens in the Austin bar or event space you've filled with some light snacks and a bunch of free liquor count as rockin like Dokken? Do good hosts require people to become lab rats in the latest attempt to develop HAL?

Whenever there's a need to draft a job description, Expedia Inc.'s 3,000-plus recruiters and hiring managers have the option to call on a writing coach. The online travel-booking company's writing companion is Textio Inc., an artificial intelligence application that runs in the cloud and analyzes each typewritten word in milliseconds to spot gender bias or other language that might turn off good candidates. The software generates an effectiveness score and suggests alternative phrasing, in effect teaching the recruiter how to write a job description more effectively. We are in the age of "the Facebook generation"-- millennials. They'll make up the majority of the workforce.

Ernst and Young (EY), the leading global professional services organisation, on Friday announced its plans to enhance its suite of automation and artificial intelligence offerings with the opening of its first Artificial Intelligence (AI) Center in India. The AI Center resonates with EY?s purpose of?building a better working world?, by helping businesses to accelerate innovation and leverage on emerging technologies to operate more efficiently, manage risk and inspire confidence. Advisory Services and Technology Sector Leader, EY India, said:?The current wave of digital innovation is disrupting sectors and businesses in unprecedented ways. The Center will help organizations find new ways to deploy new technologies across a range of functions in their business environment and build a more digital workforce of the future.? EY?s AI Center will bring together teams of multi-disciplinary practitioners, combining expertise in AI, robotics etc. along with domain experience in sectors.

The pervasive fear that artificial intelligence (AI) will take over human economic livelihood has been felt in places like the manufacturing sector, as large swaths of the industry automate labor formerly done by humans. However, proponents of machine learning say ultimately AI and robotics will improve the way we do virtually everything, and ultimately create new jobs. Still, nearly 40 percent of U.S. jobs were slated as a "high risk" for automation by the early 2030s in a March 2017 report by PricewaterhouseCoopers (PwC). While the PwC report acknowledges it's unlikely all those jobs will be automated for "a variety of economic, legal, and regulatory reasons," PwC also acknowledges that new tech typically means the creation of new jobs for human workers as well, conceding "the net impact of automation on total employment is therefore unclear." Many technologists purport that the new job creation will offset some of the pain of displacement; retraining programs and continuing education opportunities are key to bringing in displaced workers into the new high-tech fold.

Enjoy it while it lasts. US Treasury Secretary Steven Mnuchin may think artificial intelligence (AI) isn't going to start taking humans' jobs for 50 to 100 years, but most experts believe a revolution in automation is coming far sooner, promising massive increases in efficiency -- and job losses on a huge scale. A recent study put out by PwC estimated that as many as 30% of UK jobs could be "susceptible to automation by robots and AI" by the early 2030s -- with 38% in the US at risk, 35% in Germany, and 21% in Japan -- although it believes jobs will be created elsewhere in the economy to help offset this. Are we doing enough to prepare? Absolutely not, says Bob Moritz, global chairman of consultancy firm PwC.

Twitter Inc's chief executive, Jack Dorsey, continued to forego direct compensation and Peter Fenton, a board member since 2009, will leave after the company's annual meet in May, a regulatory filing showed on Friday.