Omar Abdelwahed, Head of Studio at SoftBank Robotics America, demos the capabilities of a humanoid robot, called Pepper, which is supposed to help customers shop in stores. "We designed Pepper to create empathy," says Steve Carlin, SoftBank Robotics America vice president in charge of sales and development. Steve Carlin, VP of Marketing and Business Development at SoftBank, discusses Pepper's new ability to help consumers shop at stores. "We've given Pepper a number of cues that will help people understand what it's doing," says SoftBank's Omar Abdelwahed, head of the company's robotics studio.

Maintaining the highest level of user safety will be non-negotiable when it comes to the deployment of autonomous vehicles whether they are used for personal or mass transport, or logistics in industrial environments. However, for reasons of sheer volume, it will be road vehicles where the biggest changes will be felt. Vehicle efficiency and road safety will be improved and congestion will come down and the technology and legislation is in development to make it a reality. It is generally agreed that the transition to autonomous driving will be gradual. In the US, the National Highway Traffic Safety Administration (NHTSA) has defined five levels of automation, from 0 to 4, which it refers to as the automation continuum.

Pindrop's software will be integrated into Lloyd's customer service offices. Representatives will see a traffic light system that will alert them if the call is fraudulent. From there, they can pass the call onto fraud specialists. "Every time we mark a phone call as fraudulent, we tell the system it did well and the machine learns. When we get it wrong, Lloyds lets us know, the machine learning system is constantly learning," Vijay Balasubramaniyan, chief executive of Pindrop, told CNBC by phone.

In Australia last week, the banking industry was focussed on a parliamentary inquiry into the industry's culture and response to a range of issues from customer complaints to pricing to market behaviour. Meanwhile, in the United States, technology services giant IBM bought Promontory Financial Group, a specialist risk-management consultancy. Promontory had been mentioned back in Australia, not because of IBM, but because it has been overseeing the remediation program Commonwealth Bank of Australia is running to compensate customers given inappropriate financial advice. Founded by a former US regulator, Promontory is recognised as one of the world's leading firms in regulatory compliance, risk management and risk culture. While Promontory has a significant role in Australia and globally (particularly with the ongoing fallout from the financial crisis and the cultural challenges facing banks) the IBM deal is potentially vastly more significant.

Samsung Electronics has announced that it has agreed to acquire Viv Labs, "the intelligent interface to everything." Viv has developed an open artificial intelligence (AI) platform that gives third-party developers the power to use and build conversational assistants and integrate a natural language-based interface into applications and services. It claims to be well advanced over other language interfaces like Siri or Google Now where accuracy cannot be relied on. Viv's creator, Dag Kittlaus should know as he co-created Siri too. He said, "Viv would breathe life into the inanimate objects of our life through conversation."

Robotics and AI have "huge potential" to reshape the way people work and live, but the government needs to do more to address the issues raised by such technology, says a report. MPs on the Science and Technology Committee have called for careful scrutiny of the probable ethical, legal and societal impact. They want the government to establish a commission to look at the issues. That will include new skills for humans as artificial intelligence takes jobs. Others, such as Tesla boss Elon Musk, have gone further - declaring AI to be the biggest threat to the survival of the human race.

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.