It's a cliché to proclaim that technology is having a disruptive influence on our lives, changing our society and the way people work. And, are employees and organisations prepared for the future of work? A recent event – "The Robots are coming: The future of work"- at the South Bank Centre brought together a panel of experts on robotics and artificial intelligence to debate what awaits our working lives in the near future. I was there to explore the topic and report on the talk. Sabine Hauert (pictured right) is a lecturer in robotics and member of Bristol Robotics Laboratory, an academic centre for multi-disciplinary robotics research in the UK.

In a keynote talk, Dean outlined the history of machine learning (ML) and neural networks and various ways to programme models to take advantage of raw data coming through in the form of images or audio. He also detailed how ML has taken shape at Google, which recently announced that it will open a machine learning center in Europe. The company developed its own accelerator chips for artificial intelligence it calls tensor processing units (TPUs) after the open source TensorFlow algorithms it released last year.

To celebrate the first UK Robotics Week (25 June - 1 July 2016) Plymouth University organises an afternoon of academic presentations, followed by a public exhibition and debate on robotics and artificial intelligence. From 15:00 onwards you are welcome to a series of quick-fire academic presentations on cutting-edge robotics research by the University's research team. At 17:30 there is the opportunity to visit the robotics labs at the University and see robots in action, all while having a drink and chatting to our research team. This will be followed at 19:00 by a public debate on'Robots and Artificial Intelligence: bright future or impending gloom?'. As part of the UK Robotics week, Plymouth University invites you to attend a debate on robotics, artificial intelligence and its impact on society.

Better Together is slightly tongue-in-cheek, too, but Kershaw said it's a way to support the Remain cause, though it's probably too late. The morning after the referendum, Kershaw and his team of about six had woken up feeling "miserable." "We've got Europe in our DNA; half my family are French, we've got staff here on an EU visa, and some of us are the children of immigrants," Kershaw told me over email. "I wanted something to cheer us up."' The Android app launched Thursday morning, and Kershaw hopes an iOS app will become available next week.

Could Kevin Bacon have saved us from the 2008 financial crisis? But the network science behind six degrees of Kevin Bacon just well may have. According to the famous saying, every movie actor is separated from Kevin Bacon by six degrees of separation or less, going from co-star to co-star (actually most are separated from Bacon by only three degrees). Actors form a "small-world" network, meaning it takes a surprisingly small number of connections to get from any one member to any other. Natural and man-made small-world networks of all kinds are extremely common: The electric power grid of the western United States, the neural network of the nematode worm C. elegans, the Internet, protein and gene networks in biology, citations in scientific papers, and most social networks are small. Most of these small networks use hubs, or nodes with an especially large number of links to other nodes.

Artificial intelligence that can understand and answer any work-related question it is asked has been made available in the UK for the first time. The computer software, called Starmind, uses machine learning to understand queries, then source answers from previous staff conversations on a subject or track down experts within the company who are able to help. Its creators refer to it as "brain technology", adding its aim is to become a central knowledge bank within any company, an instant database of information that can be accessed by anyone. Starmind co-founder Pascal Kaufmann said of the technology: "Thousands of human brains connected can outsmart any machine today. "But if you can find ways for humans and AI (artificial intelligence) inspired technologies to autonomously collaborate rather than focusing on ways for them to compete, you can bring out the best in both." The algorithm within the system, which was developed in Switzerland, becomes more powerful the more it is used and is able to build a map of the people in a business and the areas in which all of them are experts, or are able to provide relevant information. "Starmind acts like an artificial hyper brain that seamlessly exists at the core of a company," Mr Kaufmann added. "The algorithm is then fuelled by the know-how stored inside the brains of everyone that engages with the system." Several major companies in Europe, including UBS and Bayer are already using the system. A new version of the software - called Starmind NOW - has also been launched which enables the software to be accessed outside of company intranet for the first time. Starmind says this makes the technology more "intuitive and seamless" to use. Former Microsoft executive Peter Waser has also joined the company as CEO. "It's a new technology that has never been available on the market in this form," he said. "Brain technology is the latest technology in the megatrend of machine learning and artificial intelligence.

These are my notes and observations after attending the Safety in Artificial Intelligence (SafArtInt) conference, which was co-hosted by the White House Office of Science and Technology Policy and Carnegie Mellon University on June 27 and 28. This isn't an organized summary of the content of the conference; rather, it's a selection of points which are relevant to the control problem. As a result, it suffers from selection bias: it looks like superintelligence and control-problem-relevant issues were discussed frequently, when in reality those issues were discussed less and I didn't write much about the more mundane parts. SafArtInt has been the third out of a planned series of four conferences. The purpose of the conference series was twofold: the OSTP wanted to get other parts of the government moving on AI issues, and they also wanted to inform public opinion. The other three conferences are about near term legal, social, and economic issues of AI. SafArtInt was about near term safety and reliability in AI systems.

Most Machine Learning (ML) methods, from clustering to classification, rely on a distance function to describe relationships between datapoints. For complex datasets it is hard to avoid making some arbitrary choices when defining a distance function. To compare images, one must choose a spatial scale, for signals, a temporal scale. The right scale is hard to pin down and it is preferable when results do not depend too tightly on the exact value one picked. Topological data analysis seeks to address this issue by focusing on the notion of neighbourhood instead of distance. It is shown that in some cases a simpler solution is available. It can be checked how strongly distance relationships depend on a hyperparameter using dimensionality reduction. A variant of dynamical multi-dimensional scaling (MDS) is formulated, which embeds datapoints as curves. The resulting algorithm is based on the Concave-Convex Procedure (CCCP) and provides a simple and efficient way of visualizing changes and invariances in distance patterns as a hyperparameter is varied. A variant to analyze the dependence on multiple hyperparameters is also presented. A cMDS algorithm that is straightforward to implement, use and extend is provided. To illustrate the possibilities of cMDS, cMDS is applied to several real-world data sets.

Chemists and mathematicians from the Skolkovo Institute of Science and Technology (Skoltech) and Moscow State Universite (MSU) have suggested checking the composition of medical plants by means of machine learning technologies, the Skoltech press service said. They have come up with automatizing computer assisted data analysis based on high-performance liquid chromatography and mass spectrometry. "Machine learning is when a computer can be taught to analyze the chemical composition of herbal medicine based on the previously known data on chemical analysis," Skoltech said. According to the researchers, the market of herbal remedies has been rapidly developing in the recent years, as it provides an alternative to synthetic drugs. But there are still no existing effective methods of plant material quality control.

In addition, the built-in artificial intelligence will be able to predict situations, producing ready-made proposals for the border protection. "The system is fully based on domestic policy decisions that ensure protection of information resources against data loss, hackers and other unauthorized interventions," the press service quoted the deputy director of OPK Sergei Skokov as saying. The developers also noted that the new system is intended not only to collect different types of information, but also contains elements of artificial intelligence which will allow for analysis and forecasting of the situation and work out proposals for the protection of borders, by calculating steps and routes that offenders may take, as well as the necessary measures to prevent malicious acts, including the assessment of possible risks. The state borders need protection due to ever rising threats. Since the beginning of this year in the Rostov region, more than 60 "wanted" persons were found and arrested.