Then a blogger spotted DoNotPay, and the chatbot went viral. To date, it has helped more than 400,000 people save a total of $11 million in fines, without charging a cent. "I think people get caught up in trying to make money," says Browder, 19. "I'm just trying to make the law free for everyone." A computer-science major at Stanford who finds class "just so boring," Browder is now out to democratize a new institution: divorce.

The International Conference on Robot Ethics and Safety Standards (ICRESS-2017) took place in Lisbon, Portugal, from 20th to 21st October 2017. Maria Isabel Aldinhas Ferreira and João Silva Sequeira coordinated the conference with the aim to create a vibrant multidisciplinary discussion around pressing safety, ethical, legal and societal issues of the rapid introduction of robotic technology in many environments. There were several fascinating keynote presentations. Mathias Scheutz' inaugural speech highlighted the need for robots to act in a way that would be perceived as using moral principles and judgement. It was refreshing to see that we could potentially have autonomous robots that arrive at appropriate decisions that would be seen as "right" or "wrong" by an external observer.

A four-year-old London startup called Echobox found traction in Europe and is poised to further expand in the U.S. with its AI-assisted social media product. Echobox, which has about 30 employees and raised $3.4 million in seed funding last year, aims to develop "AI for automating repetitive tasks" for publishers, according to CEO and founder Antoine Amann. The first product the company has brought to market is an automated social media tool that uses a publisher's internal audience analytics along with machine learning to completely run social media accounts. Le Monde in France and The Guardian in the U.K. are clients. A challenge with publishing analytics today is how to make sense of them, and Echobox isn't alone in trying to solve this.

Of the six most valuable companies in the world, five are tech firms, whose worth is embodied less in physical assets than in intellectual property and customer data. Apple and Microsoft provide the tools to connect people, and to collect and process data. Google, Facebook and Amazon provide services, and in return accumulate more data about each customer than has ever been possible before. In seventh place trails Exxon Mobil, an illustration of the well-worn assertion that data is the new oil to fuel the next industrial revolution. If data is the new oil, what is the equivalent of the internal combustion engine, that turned fossil fuels from a cleaner fluid for oil lamps to a world-changing energy source for cars, tractors and aeroplanes?

For many companies, today, the demand for data and analytics is now everywhere in the enterprise. Projects are underway to improve customer engagement, reduce risk and optimize business operations. Data sources are also growing rapidly with new data coming from both inside and outside the enterprise in many different varieties. Also although analytics are needed almost everywhere, the current approaches to developing them are slow and expensive. To support this demand, the modern analytical environment has also expanded going way beyond the traditional data warehouse to become an analytical ecosystem comprising multiple data stores and platforms optimised for different kinds of analytic workloads.

Artificial Intelligence (AI) may be out of the sci-fi closet but the adoption within MarTech industry is still very much in its nascent stage. With the advent of wireless and virtual technologies in last two decades, businesses have evolved at a breakneck pace. And now, the biggest force pushing that momentum is the refined combination of AI and Machine Learning (AI/ML). While the first half of the decade focused on leveraging Big Data, AI technology in business, especially in sales and marketing, has taken a major lead with its equitable adoption rate. The promise AI offers – intelligent software running on AI/ML algorithms would perform tasks better, faster and cheaper, is an optimistic opportunity within MarTech.

Fast-food workers, cashiers, cooks, delivery people and their supporters held a rally outside New York City Hall on May 24, 2017.Erik Mcgregor/Pacific Press/Zuma From the window of his university office in Louvain-la-Neuve, Belgium, philosophy professor Philippe Van Parijs--considered by many to be Europe's most prominent advocate for the idea that the state should provide a regular income to every citizen--can see the mailbox where he sent off invitations to the first "basic income" conference more than 30 years ago. "I'm quite amazed by the seed we threw on the ground now," he says. After decades of obscurity, the idea is suddenly in fashion. Politicians around the world are interested and a handful of governments, such as Finland and the Canadian province of Ontario, are planning or considering basic-income pilot projects. But the idea of basic income has been around for more than 200 years, rising on waves of political and economic turmoil only to disappear in calmer times.

According to a survey from SLI Systems, 54 percent of mid-size retailers are using or plan to use artificial intelligence (AI) as an online tool in the next 12 months. The most popular applications are expected to be personalized product recommendations, customer service requests and chatbots. The online survey of 234 e-commerce professionals primarily in the U.S., Europe, Australia and New Zealand showed that 56 percent are either using or planning to use AI for personalized product recommendations. That was followed by customer service requests, 41 percent; chatbots, 35 percent; and visual search, 32 percent. VR/AR, voice-activated apps and virtual buying assistants scored lower.In a note from late September, according to Barron's, R.W. Baird's Colin Sebastian indicated that the "overriding theme" at the Shop.org Noting that AI chatter had risen significantly at e-commerce conferences over the last two or three years, Mr. Sebastion said the message being relayed was that "machines will learn about and communicate with individual customers."

Octavia, a humanoid robot designed to fight fires on Navy ships, has mastered an impressive range of facial expressions. When she's turned off, she looks like a human-size doll. She has a smooth white face with a snub nose. Her plastic eyebrows sit evenly on her forehead like two little capsized canoes. When she's on, however, her eyelids fly open and she begins to display emotion.