How do you explain quantum computing? Think of that vintage telephone at the General Store on Petticoat Junction. Put it next to your iPhone. Every day, it seems like there is news of yet another breakthrough in computing. Technology experts debate exactly when we will all have quantum computers instead of Echo Dots, but the day is coming.

Anywhere, at any time, the capabilities and competence of Artificial Intelligence (AI) has the potential to threaten an employee's role and an employer's style of working. Recent statistics surrounding the correlation between AI and employment in the Capgemini survey reveal that an increasing number of employers are turning to AI devices to heighten their company's impact. For instance, when discussing conversational AI chat bots, 76 percent of the organisations interviewed have seen quantifiable benefits from their voice and chat initiatives, while 58 percent claimed that these benefits met or exceeded their expectations. Compared to last year, the number of consumers using voice has shown a meaningful increase and the report emphasises that customers are increasingly preferring to use voice assistants throughout the consumer journey. To leverage their grasp of consumer appetites, the organisations appear to be trying to find the right balance between human and robotic interactions, but this still threatens the existence of human-based roles in their companies.

Automaker Ford has for the first time introduced a team of collaborative robots that works alongside engineers in Cologne, Germany, to ensure every Ford Fiesta has a perfect finish. The six cobots complete a choreographed sequence to sand the entire body surface in just 35 seconds. The initiative does not replace employees but allows operators to use their time on more complex tasks and avoid suffering the strains associated with performing repetitive tasks. Dennis Kuhn, senior manufacturing engineer, paint shop, Ford of Europe, says: "The cobots can feel when more force needs to be applied, just like we can, and they can more easily get to hard-to-reach places, like the centre of the roof." Each cobot is a UR10, the world's best-selling cobot, from Universal Robots, the kind that is also used in the audio equipment industry to polish high‑performance loudspeakers and subwoofers.

Machine Learning in Pharmaceutical Market Research Report has been studied and presents an actionable idea to key contributors working in it. A thorough study of the competitive landscape of the global Machine Learning in Pharmaceutical Market has been given, presenting insights into the company profiles, financial status, recent developments, mergers and acquisitions, and the SWOT analysis. This report has published stating that the Global Machine Learning in Pharmaceutical Market is anticipated to expand significantly at Million US$ in 2019 and is projected to reach Million US$ by 2026, at a CAGR of during the forecast period. The global Machine Learning in Pharmaceutical market can be segmented based on product type, application, end-user, and region. This report gives an in depth and broad understanding of market with accurate data covering all key features of the prevailing market, this report offers prevailing data of leading companies.

Mark Lilly, president and CEO of software developer LillyWorks, says his company is onto something. "What we have here could be as big as the invention of MRP (materials resource planning) or the creation of finite scheduling," he says. Managing workflow is just one function of the LillyWorks's cloud-based enterprise resource planning (ERP) software. However, leadership sees enough promise in the roughly two-year-old Production Flow Manufacturing (PFM) scheduling system to offer it as a standalone module that integrates with any other ERP software. As the user base expands, the company has been investigating how machine learning might expand that promise by making the system's predictive analytics capability more precise, more automated and broader in scope.

Fledgling gal-bots are the latest hires in the virtual assistant landscape. Meet Mia and Marge: two virtual assistants in the banking world – each brought into existence by women, both of whom carry deep institutional knowledge, subject matter expertise and long-standing credibility. UBank's Lee Hatton (Mia) and The Royal Bank of Scotland's (RBS) MaryAnn Fleming (Marge) are among 40 women who have been recognized as 2019's women leaders in A.I. by IBM. These leaders have succeeded in garnering acceptance of A.I. in the workplace, elevating their customers' experience and their companies' brands. It seems mortgage consumer complaints consistently surface around the loan application process according to UBank CEO, Lee Hatton.

Irish health insurer Laya Healthcare Ltd. needs to clean up thousands of accounts each month that carry balances that are too small to bother collecting. "A customer may have a balance of $150.12 and pay $150 because they can't remember the correct amount," said Information Technology Director Ian Brennan. "We're not going to chase them for 12 cents, so we apply a credit to zero them out." With 586,000 customers, the company has thousands of such tasks to address each month. "Our financial system didn't have the functionality we needed, and the vendor wanted a king's ransom to build it," Brennan remembered. Instead, Laya assigned the job to software robots developed by Blue Prism Ltd. For the past 21 months, Blue Prism bots have been logging into the debt ledger, identifying small-debt accounts and zeroing them out. "The ledger is much cleaner and our debtors' team can focus on real outstanding debts without bothering with the shrapnel of the job," Brennan said. Laya Healthcare has now automated more than 100 tasks this way, jobs that used to the take anywhere from five minutes to six hours per day for humans to process.

Digital Universe is expanding and how! Each day marks a new entry in the burgeoning list of technologies that augment and innovate the way we interact with information. This rising digital consumption brings with it, untapped opportunities for a digital marketer to reach clients. We have compiled a list of three emerging opportunities that cannot be ignored anymore. Artificial Intelligence (AI) is a two-pronged tool to automate and augment your sales and boost lead conversion.

CHIBA – A compact driverless bus on Tuesday slowly shuttled a dozen passengers on public roads near the Makuhari Messe convention center in the city of Chiba to give them a sense of the steering wheel- and pedal-free future of transport. One of the passengers, Noriyuki Sakayanagi, was amazed at the distance the bus traveled without a human driver. "It wasn't scary" to ride the bus on a public road, said Sakayanagi, who was attending the first day of CEATEC 2019, one of Japan's biggest international digital trade shows that this year marks its 20th anniversary. Sakayanagi, a 39-year-old company worker, added, "I thought more improvement in detecting traffic lights may be needed and the brakes were not so smooth." CEATEC organizers said this year's four-day event has brought together 787 exhibitors from a broad spectrum of sectors -- not only information technology and electronics but also finance, housing, travel and health care -- with a vision toward a supersmart society designed to further economic growth and solve social problems.

Artificial Intelligence and Machine Learning (AI & ML) and Sentiment Analysis are said to "predict the future through analysing the past" – the Holy Grail of the finance sector. They can replicate cognitive decisions made by humans yet avoid the behavioural biases inherent in humans. Processing news data and social media data and classifying (market) sentiment and how it impacts Financial Markets is a growing area of research. The field has recently progressed further with many new "alternative" data sources, such as email receipts, credit/debit card transactions, weather, geo-location, satellite data, Twitter, Micro-blogs and search engine results. AI & ML are gaining adoption in the financial services industry especially in the context of compliance, investment decisions and risk management.