Everybody knows that artificial intelligence is an exceptionally weaponizable technology. So it's no mystery why militaries everywhere are racing to exploit AI to its maximum potential. Autonomous vehicles, for example, will become the most formidable weapon systems humanity has ever developed. AI gives them the ability to see, hear, sense, and adjust real-time strategies far better and faster than most humans. It will almost certainly produce casualty counts in future battles that are staggering and lopsided, especially when one side is almost entirely composed of AI-powered intelligent weapons systems equipped with phalanxes of 3-D camera, millimeter-wave radar, biochemical detectors and other ambient sensors.
Deep ocean robotics is not generally an area where we expect to see much in the way of significant innovation. When we do write about submersible robots, they're usually confined to very near-surface operations. This isn't a total surprise: It seems like the only people who really worry about what's going on in the deep ocean (meaning hundreds or thousands of meters beneath the surface) are the military, the occasional scientist, and the oil and gas industry. Robots are important to these folks, even critical in some cases, but the technology has been more or less stagnant for decades, which is why we don't write about it very frequently. To be fair, there are some very good reasons why it's hard to innovate when it comes to submersible robotics.
With 400 hours of video being uploaded to YouTube every minute and fleets of self-driving cars mapping high definition 3D maps of roads all over the world, data is being created, stored and processed at a rate never seen before. Ninety percent of the world's data has been created in the last two years, according to IBM and other industry sources, and with new data hungry applications on the rise (autonomous driving, the Internet of Things, artificial intelligence), there's no sign of this trend abating. Organizing, storing and processing all that data comes with not only business, but also environmental challenges. In fact, networking and telecom equipment maker Huawei has estimated that global computing power could consume as much as 20% of global electricity in 2025 and account for 3.5% of global emissions. All this data processing also requires large amounts of water to keep servers from overheating - roughly 1.8 liters for every kWh consumed - according to the U.S. Department of Energy (DOE).
When Emmanuel Macron announced his bid for the French presidency in November 2016 from Seine-Saint-Denis, the poorest suburb in France, the message was clear: improving the social situation in the French banlieues, or suburbs, was one of his priorities. Seine-Saint-Denis, located just northeast of Paris, had long been synonymous with the conditions that blight France's banlieues - about 10 percent of France's population live in deprived areas with high unemployment and poverty rates, crime and substandard education. Recently, the Macron government announced plans to attempt what three of the preceding governments have tried to do since these banlieues came into existence: tackle what it calls "the discrimination and deprivation" faced by people living in poor suburban areas. One of the previous plans was introduced by the French politician Jean-Louis Borloo in 2004 under the presidency of Jacques Chirac. But Borloo's "social cohesion plan", which sought to improve employment and housing opportunities, did not go far.
Last week, things began stirring inside the truck-size box that sat among melting piles of snow at the airport in Fairbanks, Alaska. Before long, the roof of the box yawned open and a weather balloon took off into the sunny afternoon, instruments dangling. The entire launch was triggered with the touch of a button, 5 kilometers away at an office of the National Weather Service (NWS). The flight was smooth, just one of hundreds of twice-daily balloon launches around the world that radio back crucial data for weather forecasts. But most of those balloons are launched by people; the robotic launchers, which are rolling out across Alaska, are proving to be controversial.
The Department for Digital, Culture, Media and Sport (DCMS) announced the multi-million-pound deal today, which aims to put the UK at the forefront of AI. The deal includes almost £300m of private sector investment and newly allocated government funding for AI research. The announcement follows on from the government's recent Industrial Strategy, in which AI was highlighted as one of the country's four'grand challenges'. The EC strategy paper, released today, focuses heavily on skills, including funding for the training of 8,000 computer science teachers, 1,000 government funded AI PhDs by 2025. Furthermore, the government has committed to developing a global Turing Fellowship programme to attract and retain AI research talent to the UK.
The Commission is proposing a three-pronged approach to increase public and private investment in AI, prepare for socio-economic changes, and ensure an appropriate ethical and legal framework. This follows European leaders' call for a European approach on AI. The EU (public and private sectors) should increase investments in AI research and innovation by at least EUR 20 billion between 2018 and the end of 2020, according to the Commission's official press release. To support these efforts, the Commission is increasing its investment to EUR 1.5 billion for the period 2018-2020 under the Horizon 2020 research and innovation programme. This investment is expected to trigger an additional EUR 2.5 billion of funding from existing public-private partnerships, for example on big data and robotics.
Business Secretary Greg Clark and Culture, Media and Sport Secretary Matt Hancock (second left) talk with Alistair Cohen (left) and Brent Hoberman, Chairman of the Founders Factory (right), as they meet with artificial intelligence companies at Northcliffe House in Kensington, London as part of the launch for the Artificial Intelligence Sector Deal. Britain wants you to know that even as it stumbles towards Brexit, it's racing ahead on one of the most important technological innovations of our time - artificial intelligence. The U.K. government announced Thursday that it had put together "an AI deal worth more than £1 billion" that includes public and private funding. The money is going towards research and grants, with around £145 million from two foreign venture capital firms going into British, emerging-tech startups. It comes a couple of weeks after France announced its own commitment to AI.
The National Institutes for Health (NIH) are on an ambitious effort to harness advances in data science, machine learning, and artificial intelligence (AI) to support programs like the Precision Medicine, Cancer Moonshot, and Brain Initiatives. To accelerate progress, the NIH made a call to the public for a Request for Information (RFI)on the proposed Strategic Plan on Data Science. I submitted my letter and a number of people asked me to make my letter public. Since, as soon as it is submitted, it becomes part of the public record and the submission has now closed, I'm put the full text below. While this letter is specific to the NIH, there are many parts that are salient to the broader questions of ethics, security, and how we need to think about data going forward.
As a young person aged 16, I have come to a clear realisation that artificial intelligence will have a profound impact on myself, my family and everyone around me. Only recently have we really seen the impact of AI on the world, some examples of these include our phones (we interact with virtual personal assistants such as Siri, Alexa, Cortana and Google Assistant), banking (AI analyses large amounts of data and pattern searching) medicine (AI is able to predict and diagnose lung cancer, heart disease and more). However, although some people understand the concept of AI and its use in our day to day life, the majority of people are scared of what life will be with these so called "fake humans" running our lives. In my opinion, the first step that needs to take place, having the greatest effect, are the laws that will be put in place before the mass realisation of AI. Although some laws now stand, more discussion needs to take place around ethics and use of data, as well as guidance for those developing AI systems and algorithms.