Valentino Zocca graduated with a PhD in mathematics from the University of Maryland, USA, with a dissertation in symplectic geometry, after having graduated with a laurea in mathematics from the University of Rome. He spent a semester at the University of Warwick. After a post-doc in Paris, Valentino started working on hightech projects in the Washington, D.C. area and played a central role in the design, development, and realization of an advanced stereo 3D Earth visualization software with head tracking at Autometric, a company later bought by Boeing. At Boeing, he developed many mathematical algorithms and predictive models, and using Hadoop, he has also automated several satellite-imagery visualization programs. He has since become an expert on machine learning and deep learning and has worked at the U.S. Census Bureau and as an independent consultant both in the US and in Italy.

When Microsoft co-founder (now billionaire philanthropist) Bill Gates spoke about a robot tax, San Francisco city supervisor Jane Kim heard him -- or, at least, she read about it. Now, Kim has been pushing for a robot tax in the home state of Silicon Valley, and she's been up and about talking to the leaders of the tech industry, various labor groups throughout the state, and to public policy makers figuring out how best to implement a robot tax. But what does it mean to tax robots? For the ordinary worker, the tax one pays the government gets spent on various programs that (ideally) ends up servicing the tax-paying individual -- be it as an infrastructural project, through social services, or even as salary for public servants. Instead, it would benefit the ordinary human worker whose job was taken over by an intelligent machine.

First, Symantec revealed that hackers--probably based in Russia, although the security firm didn't go so far as to name names--had hacked more than 20 power companies in North America and Europe, and in a handful of cases, had direct access to their control systems. And then Equifax confessed it had been the target of a breach that stole 143 million Americans' data, one of the worst data spills ever, and one that raises questions about data centralization, particularly for Social Security Numbers. Megabreaches aside, Facebook admitted that a Russian troll farm had spent $100,000 on influence ads during last year's election. Google patched a flaw in Android that would allow a nasty "toast overlay" attack to take control of devices. WIRED dug into the long-running series of scams and theft plaguing new currencies in the cryptocoin economy.

The legislation contains rules such as saving humans before animals and property, saving lives without discrimination and that self-driving software should contain safeguards against malicious hacking. Germany has taken a novel approach, rather than concentrating on self-driven cars, it concentrates on self-driving software -- most self-driving legislation concentrates on self-driven cars and consequences of putting them on roads and literally in charge of human lives. The German legislation concentrates on the root of self-driving, the computers, and software used to run self-driven cars. This makes it essential that decisions be taken when programming the software of conditionally and highly automated driving systems."

Recently we wrote about the development of AI and neural nets beyond the second generation Convolutional and Recurrent Neural Nets (CNNs / RNNs) which have come on so strong and dominate the current conversation about deep learning. The original charge by DARPA's SyNAPSE program has spread the work among many of these labs including Sandia, Oak Ridge, and Lawrence Livermore. "Neuromorphic computing is still in its beginning stages," says Dr. Catherine Schuman, a researcher working on such architectures at Oak Ridge National Laboratory. State of the art on the hardware side appears to still belong to IBM which recently delivered a supercomputing platform based on TrueNorth to Lawrence Livermore Lab with the equivalent of 16 million neurons and 4 billion synapses.

AI's next frontier requires ethics built through policy. With one foot in its science fiction past and the other in the new frontier of science and tech innovations, AI occupies a unique place in our cultural imagination. Will we live into a future where machines are as intelligent -- or frighteningly, more so -- than humans? We have already witnessed AI predict the outcome of the latest U.S. presidential election when many policy wonks failed. Perhaps we are further along than we thought.

Artificial intelligence can accurately guess whether people are gay or straight based on photos of their faces, according to new research that suggests machines can have significantly better "gaydar" than humans. The study from Stanford University – which found that a computer algorithm could correctly distinguish between gay and straight men 81% of the time, and 74% for women – has raised questions about the biological origins of sexual orientation, the ethics of facial-detection technology, and the potential for this kind of software to violate people's privacy or be abused for anti-LGBT purposes. The research found that gay men and women tended to have "gender-atypical" features, expressions and "grooming styles", essentially meaning gay men appeared more feminine and vice versa. The data also identified certain trends, including that gay men had narrower jaws, longer noses and larger foreheads than straight men, and that gay women had larger jaws and smaller foreheads compared to straight women.

To register or not to register? This question has been haunting aviation authorities about drones for long – the United Nations' aviation authority the International Civil Aviation Organization (ICAO) has called for a global drone registry, Reuters reported Friday. According to the report, the effort is a part of a larger plan to create a common framework of rules to fly and track unmanned aerial vehicles. Many countries including the U.S. have tried to create a drone registry before and failed. The Federal Aviation Administration called for registration of all drones in the U.S. in March, but the 2015 Department of Transportation backing was stuck down by a Washington D.C. court in May, prompting the aviation authority to rescind its order.

For many Russian students, the academic year started last Friday with tips on planetary domination from President Vladimir Putin. "Artificial intelligence is the future, not only for Russia but for all humankind," he said, via live video beamed to 16,000 selected schools. "Whoever becomes the leader in this sphere will become the ruler of the world." Putin's advice is the latest sign of an intensifying race among Russia, China, and the US to accumulate military power based on artificial intelligence. All three countries have proclaimed intelligent machines as vital to the future of their national security.

Dawn Meyerriecks, the Central Intelligence Agency's deputy director for technology development, said this week the CIA currently has 137 different AI projects, many of them with developers in Silicon Valley. These range from trying to predict significant future events, by finding correlations in data shifts and other evidence, to having computers tag objects or individuals in video that can draw the attention of intelligence analysts. Officials of other key spy agencies at the Intelligence and National Security Summit in Washington this week, including military intelligence, also said they were seeking AI-based solutions for turning terabytes of digital data coming in daily into trustworthy intelligence that can be used for policy and battlefield action. "If we were to attempt to manually exploit the commercial satellite imagery we expect to have over the next 20 years, we would need eight million imagery analysts," Robert Cardillo, director of the National Geospatial-Intelligence Agency, said in a speech in June.