The industry is worth billions (circa 60bn in 2013) and around 150,000 VAT registered UK companies are dependent on road transport to trade effectively. As transport costs are typically between 3-10 per cent of a company's turnover, they are an important factor for both individual organisations and the economy as a whole. One of the long held aims of the industry has been to reduce the number of freight vehicles on the road. As such a significant part of the GDP in both the UK and the rest of Europe, the prospect of being able to remove 30-40 per cent of freight vehicles from the roads has massive environmental and economic implications for all of us. So what is the best way of achieving this ambitious target?

Life and stories are so closely intertwined that, at times, it's hard to know where one ends and the other begins. On Flipboard, stories flow from one to the next, weaving a rich tapestry that does an amazing job of showcasing all that life has to offer. The Galaxy Note 7 was the best phone available when it was released in August. A culmination of all of the company's strongest technologies to date, coupled with some fascinating new arrivals, Samsung somehow made the whole thing work in harmony, fit into a beautifully crafted 5.7-inch design. Even a war as pitiless as Syria's can have a low point.

He's a lightning-fast learner, he speaks eight languages and he's considered an expert in multiple fields. He's got an exemplary work ethic, is a speed reader and finds insights no one else can. On a personal note, he's a mean chef and even offers good dating advice. Named after IBM's first CEO, Watson was born back in 2007 as part of an effort by IBM Research to develop a question-answering system that could compete on the American quiz show "Jeopardy." Since trouncing its human opponents on the show in 2011, it has expanded considerably.

Yvonne Baur is the head of predictive analytics at SAP SuccessFactors. We've been hearing a lot about diversity and inclusion recently, and one of the areas that a lot of people are particularly interested in and excited about is applying machine learning to eliminate bias. Done right, this can be a huge boost supporting our efforts to go beyond bias across all areas of the organization. But there are potential pitfalls, as well; if not done right, machine learning can actually make your business more biased. Let's look at Google's word2vec, for example. Using a millions-large set of Google News data, Google researchers extracted patterns of words that are related to each other.

Microsoft (NSDQ:MSFT) CEO Satya Nadella and president Brad Smith embarked on a four-day European tour to meet with business and government leaders, and promote the company's cloud computing services in Europe. Microsoft, which has invested over 3 billion in Europe to date, announced that it has more than doubled its cloud capacity in Europe in the past year, and intends to deliver Microsoft Cloud to European customers from data centers in France, starting in 2017. "We continue to invest heavily in cloud infrastructure to meet the growing demand from European customers and partners," said Nadella. "Building a global, trusted, intelligent cloud platform is core to our mission to empower every person and organization on the planet to achieve more. There's never been a better time for organizations across Europe to seize new growth and opportunity with the Microsoft Cloud."

Dynamics 365, a new cloud service from Microsoft that combines components of its CRM and ERP offerings, will become available on Nov. 1, the company announced Tuesday. First unveiled in July, Dynamics 365 is a set of apps for seven CRM and ERP functions: financials, operations, marketing, sales, customer service, project service automation and field service management. Organizations can purchase each Dynamics 365 app separately, adding more as their needs change. They also have the option to purchase a set of apps as a subscription bundle. Microsoft announced one such app on Tuesday called "Dynamics 365 for Customer Insights."

Results of preclinical studies by investigators at the Medical University of South Carolina (MUSC) reported in the August 2016 issue of Arthritis & Rheumatology demonstrate for the first time that including novel biomarkers in lupus nephritis (LN) prognostic models significantly increases their power to predict therapeutic efficacy. Identifying biomarker models with sufficient predictive power is a critical step toward developing clinical decision-making tools that can rapidly identify patients who require a change in therapy and potentially reduce onset of renal fibrosis during induction therapy. Approximately half of all patients with systemic lupus erythematosus (SLE) develop LN, an immune complex-mediated glomerulonephritis. Lupus nephritis, in turn, leads to renal failure in up to 50% of patients within five years. American College of Rheumatology guidelines recommend changing LN treatment after six months of induction therapy if response to therapy is not achieved.

Free app Duolingo is a great way to learn the basics of a new language, with small daily lessons that gradually increase your skills, with rewards for progressing. Now the service has added a new feature that's a little different from the back-and-forth translation -- text-based chatbots. These are aimed at helping you improve your conversational skills and skills you might use in real life, such as ordering food, visiting a tourist attraction, shopping for clothing or catching a cab. A variety of scenarios will see you learning how to follow a set of directions, or talk with a doctor. According to the Duolingo chatbot Web page, these bots are programmed to react to thousands of different responses.

All you hear these days is how machine learning and artificial intelligence are the next big things. Your fellow executives, managers, vice presidents and directors are all talking about the need to think about an AI strategy to build business intelligence and create a competitive advantage. Unless you are among a handful of sophisticated technology companies, machine learning and artificial intelligence are way beyond the level of your core competence. You don't have a neural network and wouldn't know what to do with one even if you did. Your IT department just finished (finally) setting up your cloud platform and migrating all of the old company resources to a fancy new public/private hybrid cloud that the executive team spent three years talking about. The new DevOps team is finally in place … and may be obsolete before it even starts work.

Nearly 140 private companies working to advance artificial intelligence technologies have been acquired since 2011, with over 40 acquisitions taking place in 2016 alone (as of 10/7/2016). Corporate giants like Google, IBM, Yahoo, Intel, Apple and Salesforce, are competing in the race to acquire private AI companies, with Samsung emerging as a new entrant this month with its acquisition of startup Viv Labs, which is developing a Siri-like AI assistant. Google has been the most prominent global player, with 11 acquisitions in the category under its belt (follow all of Google's M&A activity here through our real-time Google acquisitions tracker). In 2013, the corporate giant picked up deep learning and neural network startup DNNresearch from the computer science department at the University of Toronto. This acquisition reportedly helped Google make major upgrades to its image search feature.