Samsung has faced a tough slog getting Bixby to the masses, but now its voice assistant is accessible in more than 200 countries including the UK, Australia, Canada and South Africa. It's been available in South Korea and the US since July, when it launched after months of delays. Part of Bixby's appeal is its positioning beyond that of a simple voice assistant. Samsung claims it learns over time, recognizing "natural language" to make interacting with your phone easier and more intuitive. It understands cross-application commands and thanks to deep integration it can be accessed without any interruptions to what you're already doing on-screen.

Machine learning is perhaps the principal technology behind two emerging domains: data science and artificial intelligence. The rise of machine learning is coming about through the availability of data and computation, but machine learning methdologies are fundamentally dependent on models. The emergence of machine learning is closely tied to the emergence of widely available data. Large amounts of data and high interconnection bandwidth mean that we receive much of our information about the world around us through computers. Economists try to measure productivity, one of the ways we can become more productive is by becoming more efficient. For example, moving from gathering food to settled agriculture. In the modern era one approach to becoming more efficient is automation of processes like manufacturing production lines. The manufacturing process is decomposed into a series of mechanical or manual processes each of which is applied sequentially. Manufacturing processes consist of production lines and robotic automation. Logistics can also be decomposed into the supply chain processes. Whether it's manufacturing or logistics, efficiency can be improved by automating components of the processes to improve the flow of goods. An interesting challenge for modern society is the management of both the flow of goods and the flow of information. The flow of information is also highly automated. Processing of data is decomposed into stages in computer code. In these processing pipelines, manufacturing, logistics or data management, the overall pipeline normally also requires human intervention from an operator. These interventions can create bottlenecks and slow the process of automation. Machine learning is the key technology in automating these manual stages. The human interventions that were easy to replicate with technology have already been replaced. The components that still require human intervention are the knottier problems. Often they represent components that are difficult, or impossible, to decompose into stages which could then be further automated. In that sense these components are process-atoms. In manufacturing or logistics settings these atoms involve the sort of flexible manual skills that we cannot replicate with current robotic technology.

Image recognition AIs that have been trained by some of the most-used research-photo collections are developing sexist biases, according to a new study. University of Virginia computer science professor Vicente Ordóñez and colleagues tested two of the largest collections of photos and data used to train these types of AIs (including one supported by Facebook and Microsoft) and discovered that sexism was rampant. He began the research after noticing a disturbing pattern of sexism in the guesses made by the image recognition software he was building. 'It would see a picture of a kitchen and more often than not associate it with women, not men,' Ordóñez told Wired, adding it also linked women with images of shopping, washing, and even kitchen objects like forks. The AI was also associating men with stereotypically masculine activities like sports, hunting, and coaching, as well as objects sch as sporting equipment.

SUBIRATS, SPAIN – Spanish police on Monday shot dead an Islamist militant who killed 13 people with a van in Barcelona last week, ending a five-day manhunt for the perpetrator of Spain's deadliest attack in over a decade. Police said they tracked 22-year-old Younes Abouyaaqoub to a rural area near Barcelona and shot him after he held up what looked like an explosives belt and shouted "Allahu Akbar" (God is Greatest). A bomb squad then used a robot to approach his body. Abouyaaqoub had been on the run since Thursday evening, after he drove at high speed into throngs of strollers along Barcelona's most famous avenue, Las Ramblas. After fleeing the scene, he hijacked a car and fatally stabbed its driver.

German multinational software company SAP will participate in DigiTrans -- The Digital Transformation Forum -- scheduled for October 25-26, 2017, in Dubai, as a gold sponsor. The event, presented by MIT Sloan Management Review GCC, will focus on customer-centric experiences and operational efficiency. DigiTrans will offer actionable knowledge for strategy, organisational roadmap, and innovation-based opportunities. "Dubai is a global hub for showing best practices in using digital transformation to transform industry verticals, and the citizen and customer experiences. With digital transformation reaching a tipping point in the Middle East, DigiTrans 2017 Dubai provides the platform for SAP to exchange best practices in digital transformation. Topics such as artificial intelligence, blockchain, machine learning, and the Internet of Things will be vital for the next generation of chief digital officers to lead the digital economy," said Tayfun Topkoc, managing director, SAP UAE and Oman.

Leaders in the fields of AI and robotics, including Elon Musk and Google DeepMind's Mustafa Suleyman, have signed a letter calling on the United Nations to ban lethal autonomous weapons, otherwise known as "killer robots." In their petition, the group states that the development of such technology would usher in a "third revolution in warfare," that could equal the invention of gunpowder and nuclear weapons. "Once developed, [autonomous weapons] will permit armed conflict to be fought at a scale greater than ever, and at timescales faster than humans can comprehend," write the signatories. "These can be weapons of terror, weapons that despots and terrorists use against innocent populations, and weapons hacked to behave in undesirable ways." The letter is signed by the founders of 116 AI and robotics companies from 26 countries, and was published this weekend ahead of the International Joint Conference on Artificial Intelligence (IJCAI).

The world's leading artificial intelligence experts are sounding the alarm on killer robots. Tesla (TSLA) boss Elon Musk is among a group of 116 founders of robotics and artificial intelligence companies who are calling on the United Nations to ban autonomous weapons. "Lethal autonomous weapons threaten to become the third revolution in warfare. Once developed, they will permit armed conflict to be fought at a scale greater than ever, and at timescales faster than humans can comprehend," the experts warn in an open letter released Monday. "These can be weapons of terror, weapons that despots and terrorists use against innocent populations, and weapons hacked to behave in undesirable ways," the letter says.

A next revolution in warfare where killer robots, or autonomous weapons systems, are common in battlefields is about to start. Both scientists and industry are worried. The world's top artificial intelligence (AI) and robotics companies have used a conference in Melbourne to collectively urge the United Nations to ban killer robots or lethal autonomous weapons. An open letter by 116 founders of robotics and artificial intelligence companies from 26 countries was launched at the world's biggest artificial intelligence conference, the International Joint Conference on Artificial Intelligence (IJCAI), as the UN delays meeting until later this year to discuss the robot arms race. Toby Walsh, Scientia Professor of Artificial Intelligence at the University of New South Wales, released the letter at the opening of the opening of the conference, the world's pre-eminent gathering of experts in artificial intelligence and robotics.

Today, businesses need to be able to predict demand and trends to stay in line with any sudden market changes and economy swings. This is exactly where forecasting tools, powered by Data Science, come into play, enabling organizations to successfully deal with strategic and capacity planning. Smart forecasting techniques can be used to reduce any possible risks and assist in making well-informed decisions. One of our customers, an enterprise from the Middle East, needed to predict their market demand for the upcoming twelve weeks. They required a market forecast to help them set their short-term objectives, such as production strategy, as well as assist in capacity planning and price control.

The emerging technologies on the Gartner Inc. Hype Cycle for Emerging Technologies, 2017 reveal three distinct megatrends that will enable businesses to survive and thrive in the digital economy over the next five to 10 years. Artificial intelligence (AI) everywhere, transparently immersive experiences and digital platforms are the trends that will provide unrivaled intelligence, create profoundly new experiences and offer platforms that allow organizations to connect with new business ecosystems. The Hype Cycle for Emerging Technologies report is the longest-running annual Gartner Hype Cycle, providing a cross-industry perspective on the technologies and trends that business strategists, chief innovation officers, R&D leaders, entrepreneurs, global market developers and emerging-technology teams should consider in developing emerging-technology portfolios. The Emerging Technologies Hype Cycle is unique among most Gartner Hype Cycles because it garners insights from more than 2,000 technologies into a succinct set of compelling emerging technologies and trends. This Hype Cycle specifically focuses on the set of technologies that is showing promise in delivering a high degree of competitive advantage over the next five to 10 years (see Figure 1).