New drone rules are being introduced in U.K. that'll restrict all drones from flying above 400 feet and within 1 km of airport boundaries, and the changes will come into effect on July 30. The law will also be requiring the registration of drones weighing 250 grams or more with the Civil Aviation Authority (CAA), and these requirements will come into force on Nov.30, 2019. "We welcome the clarity that today's announcements provides, as it leaves no doubt that anyone flying a drone must stay well away from aircraft, airports and airfields, says Chris Woodroofe, Chief Operating Officer of London's Gatwick Airport. On the other hand, 'Drone bill' will be published to provide police officers the powers to intervene if the drones are used inappropriately. "The CAA supports the safe development of drones in the U.K., as they can bring many benefits, but to achieve those, we need everyone flying a drone now to do so safely.

There are plenty of reasons to use voice assistants, but one of the key drivers is speed. The majority (82%) of voice assistant users say that fast and accurate replies is the most compelling feature that causes them to use the voice assistant. These are among the findings in the Conversational Commerce study by Capgemini Digital Transformation Institute, which surveyed 5,000 consumers in the U.S., U.K., France and Germany. Although the study was focused on consumers making purchases via voice assistants, some other interesting insights about consumers who use voice assistants also were found. For example, more than two-thirds (69%) prefer to use their voice assistants in their living rooms and 61% in the kitchen.

The Serious Fraud Office is a specialist prosecuting authority tackling the top level of serious or complex fraud, bribery, and corruption across England, Wales and Northern Ireland. It both investigates and prosecutes its cases, which is unique but necessary because the cases are complicated, and lawyers and investigators need to work together from the outset of them. Supporting both lawyers and investigators is an IT infrastructure that is managed by chief technology officer (CTO) Ben Denison, who also looks after the technology that supports the SFO's operational activities. "That includes digital evidence, so in our cases when we're investigating someone we'll see information from phones, tablets, laptops, and email, and we have a digital forensics team that processes that material and extracts relevant data from it, and it can then be ingested into another system which our case teams use to review it from," Denison tells PublicTechnology. In essence, the SFO ensures that all of the data – whether it's digital or a hard copy – is put into one place, so that it can be reviewed together.

Marc Aguilar (Chief Data Officer at BGL BNP Paribas) officially opened the summit: "Today, it is possible to develop an algorithm in 8 weeks, but infrastructure and data sourcing strategies are needed. Also, quality data is required to work on developing an Artificial Intelligence". According to the CDO, data is the new asset which must be managed through the use of data quality management tools. It requires governance and a sourcing strategy: where does the data come from? Who do we buy it from?

This post originally appeared on the PullString blog. Unless you've been living under a rock for the last twelve months, you've heard about voice assistants. They go by the name of Alexa, Google Assistant or Siri and can give you information about your commute or the weather, turn lights on and off, book flights, and order groceries. A line of questioning we hear a lot from CMOs in North America and Europe is: should they even care about this latest technology trend, does voice deserve its own strategy, does it warrant attention at their level of the organization? We believe there are four strategic reasons why every CMO should start thinking about what voice assistant customer engagement means for their digital transformation strategy.

It's no great revelation that we live in a surveillance society. A U.S. citizen is reportedly captured on CCTV around 75 times per day. That figure is even higher elsewhere in the world. In the United Kingdom, this number is considerably greater, with your average Brit likely to be caught on surveillance cameras up to 300 times in the same period. But a lot of existing CCTV networks still rely on people to operate them.

In 2015, a worried father asked Rhema Vaithianathan a question that still weighs on her mind. A small crowd had gathered in a basement room in Pittsburgh, Pennsylvania, to hear her explain how software might tackle child abuse. Each day, the area's hotline receives dozens of calls from people who suspect that a child is in danger; some of these are then flagged by call-centre staff for investigation. But the system does not catch all cases of abuse. Vaithianathan and her colleagues had just won a half-million-dollar contract to build an algorithm to help. Vaithianathan, a health economist who co-directs the Centre for Social Data Analytics at the Auckland University of Technology in New Zealand, told the crowd how the algorithm might work. For example, a tool trained on reams of data -- including family backgrounds and criminal records -- could generate risk scores when calls come in. That could help call screeners to flag which families to investigate.

Cylance, a cybersecurity startup that leverages artificial intelligence and machine learning to combat online attacks, has raised $120 million in a series E round of funding led by Blackstone Tactical Opportunities, with participation from other unnamed investors. Founded in 2012 by Stuart McClure, an entrepreneur who sold an Internet security firm to McAfee for $86 million in 2004, Cylance is an endpoint protection platform designed to thwart malware, ransomware, and other forms of advanced threats using AI. Its suite of algorithm-based security protocols essentially inspect networks for weaknesses and shuts them down if any are detected. Cylance claims in excess of 4,000 customers, and said that it has revenues of $130 million for the 2018 fiscal year, representing a year-on-year growth of 90 percent. Prior to now, Cylance had raised around $177 million, including a $100 million tranche two years ago, and with another $120 million in the bank it said that it plans to double down on its global expansion efforts, with a particular focus on Europe, the Middle East, and Asia Pacific, and extend its product range.

Cylance, a cybersecurity startup that leverages artificial intelligence and machine learning to combat online attacks, has raised $120 million in a series E round of funding led by Blackstone Tactical Opportunities, with participation from other unnamed investors. Founded in 2012 by Stuart McClure, an entrepreneur who sold an Internet security firm to McAfee for $86 million in 2004, Cylance is an endpoint protection platform designed to thwart malware, ransomware, and other forms of advanced threats using AI. Its suite of algorithm-based security protocols essentially inspect networks for weaknesses and shuts them down if any are detected. Cylance claims in excess of 4,000 customers, and said that it has revenues of $130 million for the 2018 fiscal year, representing a year-on-year growth of 90 percent. Prior to now, Cylance had raised around $177 million, including a $100 million tranche two years ago, and with another $120 million in the bank it said that it plans to double down on its global expansion efforts, with a particular focus on Europe, the Middle East, and Asia Pacific, and extend its product range.

A deep learning neural network trained on 50,000 crystal structures of inorganic materials has acquired the ability to recognise chemical similarities and predict new materials. One way to find out whether two elements from the periodic table will form a crystalline material is the tried and trusted'shake and bake' – mix them together at a range of different stoichiometries and hope for the best. Binary materials are thus very well covered in the scientific literature, but this method can't keep up with the vastly more complex combinatorial possibilities afforded by three or more elements. Therefore, predictions of which elements will combine in which ratios to form regular solids are necessary and they hold the promise of new materials with desirable or even unprecedented properties. Current prediction methods typically use evolutionary algorithms and apply them to random starting structures.