Last year, the Defense Advanced Research Projects Agency (DARPA), which funds a range of blue-sky research efforts relevant to the US military, launched a $1.5 billion, five-year program known as the Electronics Resurgence Initiative (ERI) to support work on advances in chip technology. The agency has just unveiled the first set of research teams selected to explore unproven but potentially powerful approaches that could revolutionize US chip development and manufacturing. Hardware innovation has taken something of a back seat to software advances in recent years, and that bothers the US military for several reasons. At the top of the list is that Moore's Law, which holds that the number of transistors fitted on a chip doubles roughly every two years, is reaching its limits (see "Moore's Law is dead. That could stymie future advances in electronics that the military relies on, unless new architectures and designs can allow progress in chip performance to continue.

Project Maven, the Pentagon-backed AI imaging initiative that seeks to "result in improved safety for citizens and nations through faster identification of evils such as violent extremist activities and human right [sic] abuses," marks just the first steps along very long road for the American defense and intelligence industries. Maven uses drone footage to build its machine learning models, and drew media attention earlier this year when Google backed out of the project over the concerns of dissident employees. The employees, some 3,000 of whom signed a petition against any involvement with the US military, demanded the company not contribute to any research that would be used for wartime applications. General James Holmes of the US Air Force told reporters last month, however, that the US would need to vigorously pursue such research if it wanted to seriously deter war. A stance the Pentagon has thrown its weight behind, releasing a memo earlier this week announcing the establishment of the Joint Artificial Intelligence Center.

The work is seen as essential to test and prove vehicle safety. The Government is also calling for views from industry and others ahead of a fuller policy proposal about the potential opportunities, obstacles and dangers entailed in likely transport developments, to help Britain get ahead of the competition. The initial aim is to explore regulatory barriers to technological and service innovation, and how data can be better used to improve transport, as well as the potential disadvantages of some technologies. The possibilities the Government envisages include not only increased use of drones which cities are already pioneering to help emergency services, but the possible introduction of aerial passenger vehicles.

Hundreds of companies and thousands of individuals, many of them researchers and engineers prominent in the fields of robotics and artificial intelligence, vowed on Wednesday never to apply their skills toward the creation of autonomous killing machines. Led by the Future of Life Institute, a Boston-based nonprofit, as many as 160 AI-related companies in 36 countries, and 2,400 individuals in 90 countries, signed the pledge stating that autonomous weapons posed a "clear and present danger to the citizens of every country in the world," and that they would not participate in their development. "Artificial intelligence (AI) is poised to play an increasing role in military systems," the pledge states. "There is an urgent opportunity and necessity for citizens, policymakers, and leaders to distinguish between acceptable and unacceptable uses of AI." The signatories, who join 26 United Nations countries that have explicitly called for a ban on lethal autonomous weapons, include DeepMind, Google's top AI research team; the European Association for AI; ClearPath Robotics/OTTO Motors; the XPRIZE Foundation, the Swedish AI Society; and University College of London, among others. Leading AI researchers Demis Hassabis, Stuart Russell, Yoshua Bengio, Anca Dragan, Toby Walsh, and Tesla and SpaceX founder Elon Musk are among the individuals who also signed the pledge.

In order to mitigate the displacement effect on this large portion of the workforce, as well as to help members of the UK's labour pool who have already found themselves out of work, PwC issued a number of recommendations to accompany its report. Most importantly, the firm suggests that the UK Government should invest more in'STEAM' skills that will be most useful to people in this increasingly automated world. While this does mean pushing for schools to focus more on STEM subjects (science, technology, engineering and mathematics), it also means Britain should explore how art and design – the'A' in'STEAM' – can feature at the heart of innovation. It is not solely about educating new labour, though, and PwC also states that governments have a responsibility to encourage workers to continually update and adapt their skills so as to complement what new machines and AI can do. Meanwhile, the UK Government should strengthen the state's safety net for those who find it hard to adjust to technological changes.

In recent times, the beltway of America is growing upset with many things in the country. This isn't to say that other parts of the country are not dissatisfied, but change is more likely to occur where the collective is more together. As David Stockman likes to call it, "Flyover America is not happy with the robbery that has impacted so many aspects of daily life. Whether that is the central banking cartel rigging wheat futures or lean hogs, people are not happy with their purchasing power over the last several decades. Purchasing power affects their kids' futures, along with their generational livelihoods.

Humans should get'out of the loop' of artificial intelligence systems, UTS roboticist Professor Mary-Anne Williams argued last week at an Australian Human Rights Commission technology conference in Sydney. AI needn't consult a flesh and blood individual even when making life or death decisions, said Williams, director of The Magic Lab at the university's Centre of Artificial Intelligence. The rise of autonomous weapons systems which operate without human control is being campaigned against around the world. "States must draw the line now against unchecked autonomy in weapon systems by ensuring that the decision to take human life is never delegated to a machine," the Campaign to Stop Killer Robots states. In Australia, 122 AI experts last year signed a letter to Prime Minister Malcolm Turnbull urging him to "take a firm global stand" against weapons systems that remove "meaningful human control" when selecting targets and deploying lethal force.

You will soon be working with, or competing against, a new type of robot with the potential to change the game of international politics forever. Diplomacy is similar to a strategic board game. A country makes a move, the other(s) respond. Artificial intelligence is good at board games. To get the game started, the system analyses previous play, learns lessons from defeats or even repeatedly plays against itself to devise a strategy that can be never thought of before by humans.

This speech was given by Dr Larry Marshall at the AFR Innovation Summit on Monday 30 July 2018. I would like to begin by acknowledging the Gadigal people of the Eora nation as the Traditional Owners of the land that we are on today, and pay my respect to their Elders past and present. It's great to be back at the AFR Innovation Summit, and thank you to our morning speakers for setting a strong focus on the power of innovation to shape our future. Before I was the Chief Executive of Australia's national science agency, I was an inventor, an entrepreneur, a venture capitalist and of course a kid. I grew up in a time where people were obsessed with the power of the computer and its ability to replace humans, our parents told us to study computer programing.

In scientific disciplines where research findings have a strong impact on society, reducing the amount of time it takes to understand, synthesize and exploit the research is invaluable. Topic modeling is an effective technique for summarizing a collection of documents to find the main themes among them and to classify other documents that have a similar mixture of co-occurring words. We show how grounding a topic model with an ontology, extracted from a glossary of important domain phrases, improves the topics generated and makes them easier to understand. We apply and evaluate this method to the climate science domain. The result improves the topics generated and supports faster research understanding, discovery of social networks among researchers, and automatic ontology generation.