The Defense Advanced Research Projects Agency wants warfighters to better trust artificial intelligence, so it's putting it to work in dogfights. DARPA's Air Combat Evolution program, currently out with a presolicitation notice, is working to deploy AI in "within-visual-range maneuvering," more commonly known in the air combat space as dogfighting. The ultimate goal is to not only to get AI into the cockpit -- the Defense Department doesn't foresee dogfights being the fighting style of the future -- but to train warfighters to trust computers the way they trust other humans. DARPA is seeking proposals for AI that can be gradually implemented into high-tempo, highly dynamic environments through simulation and eventual deployment, according to the notice. The Air Combat Evolution program is a part of a broader push for AI working alongside warfighters called Mosaic Warfare.

The research revealed that while over half of organisations use artificial intelligence (AI) or machine learning in their security stack, nearly 60 percent are still more confident in cyberthreat findings verified by humans over AI. The survey responses, along with the theme of "Human Element" at RSA Conference 2020, reflect the need for security organisations to incorporate both AI- and human-centric offerings, especially in the application security space. Three-quarters of respondents use an application security tool, and more than 40 percent of those application security solutions use both AI-based and human-based verification. AI and machine learning have provided several advantages for cybersecurity professionals overall the past several years, especially in the face of the technology talent gap, which has left 45 percent of respondents' companies lacking a sufficiently staffed cybersecurity team. More than 70 percent of respondents agree that AI-based tools made their cybersecurity teams more efficient by eliminating over 55 percent of mundane tasks.

Increased Integration of Different Solutions to Provide Improved Performance 5.2.3.3 Rapid Industrial Growth in Emerging Economies 5.2.4 Challenges 5.2.4.1 Threats Related to Cybersecurity 5.2.4.2 Complexity in Implementation of Smart Manufacturing Technology Systems 5.2.4.3 Lack of Awareness About Benefits of Adopting Information and Enabling Technologies 5.2.4.4 Lack of Skilled Workforce 5.3 Industrial Wearable Devices Trends in Smart Manufacturing 5.3.1 By Device 5.3.1.1

Researchers from Google Brain, Intel, OpenAI, and top research labs in the U.S. and Europe joined forces this week to release what the group calls a toolbox for turning AI ethics principles into practice. The kit for organizations creating AI models includes the idea of paying developers for finding bias in AI, akin to the bug bounties offered in security software. This recommendation and other ideas for ensuring AI is made with public trust and societal well-being in mind were detailed in a preprint paper published this week. The bug bounty hunting community might be too small to create strong assurances, but developers could still unearth more bias than is revealed by measures in place today, the authors say. "Bias and safety bounties would extend the bug bounty concept to AI and could complement existing efforts to better document data sets and models for their performance limitations and other properties," the paper reads.

Microsoft chief technology officer Kevin Scott grew up fascinated by the 1960s Apollo space program and then-President John F. Kennedy's vision of a moon shot. Now, he envisions just as ambitious a project taking shape as a consequence of the coronavirus pandemic. Just as the U.S. government significantly invested to put Neil Armstrong and others on the moon by 1969 – $200 billion in today's dollars by his estimate – Scott said similar funding in artificial intelligence technology could be a difference-maker for our nation's battered health care system. Scott, 48, whose new book about AI will be released Tuesday, said using the technology to detect underlying health conditions could not only help treat patients and prevent the spread of future pandemics, but also reduce care costs for Americans, tens of millions of which are uninsured. "Instead of a'moon shot,' our moon shot should be something like radically transforming health care for the public good,'' Scott said. "We all know the cost of delivering ubiquitous, high-quality health care is very high and growing faster than [gross domestic product].

A U.S. Department of Energy initiative could refurbish existing supercomputers, turning them into high-performance artificial intelligence machines. WASHINGTON, D.C.--The U.S. Department of Energy (DOE) is planning a major initiative to use artificial intelligence (AI) to speed up scientific discoveries. At a meeting here last week, DOE officials said they will likely ask Congress for between $3 billion and $4 billion over 10 years, roughly the amount the agency is spending to build next-generation "exascale" supercomputers. "That's a good starting point," says Earl Joseph, CEO of Hyperion Research, a high-performance computing analysis firm in St. Paul that tracks AI research funding. He notes, though, that DOE's planned spending is modest compared with the feverish investment in AI by China and industry.

Artificial Intelligence (AI) will have a massive impact on the global economy and Romania has huge potential in this field, fuelled by its talent pool in fields like robotics, technology, and IT. We've been hearing it constantly over the last few years, but what does the beginning of the year look like for AI in Romania? Artificial Intelligence represents an opportunity that Romania cannot afford to miss in terms of its economic development. As a general context, the European Union is pursuing a digital strategy that builds on technology, innovation, and ingenuity, projecting European values onto the international stage. The recently presented White Paper on Artificial Intelligence (AI) and the European data strategy show that Europe can set global standards on technological development while putting people first.

Compared to other countries, the USA has been relatively slow to develop a national strategy pertaining specifically to Artificial Intelligence. However that has not slowed down the rate of progress in American academia and industry that has led to many noteworthy AI technical advances over the past several years, both in fundamental algorithms and in practical applications. This high rate of AI-related technological progress shows no sign of slowing down. Meanwhile, the federal government has recently become more proactive in its organization of a national strategy and providing guidance and possibly new resources for AI development. Artificial Intelligence (AI) is changing rapidly in all ways.

The close of the first decade of the 21st century marked the final end of the dream of deregulated global capitalism as a historical horizon of peace and prosperity. From 2008, the so-called Great Recession established new political coordinates characterised by the normalisation of precariousness and the rise of illiberal movements. Similarly, the close of the second decade of the 21st century has been marked by the end of the hopes placed on digital technology as a means of extra-political solution--analogous and complementary to the commercial--to our economic, cultural and social problems. For at least three decades--from the 1980s to the outbreak of the crisis--the vertigo of social weakening and the vital risk associated with global financialisation, labour flexibility and the loss of political sovereignty were somehow curbed by expectations of economic growth and, above all, technological progress. It is difficult to call into question the decomposition of this social programme.

It can no longer be denied that Artificial Intelligence is having a growing impact in many areas of human activity. It is helping humans communicate with each other--even beyond linguistic boundaries--, finding relevant information in the vast information resources available on the web, solving challenging problems that go beyond the competence of a single expert, enabling the deployment of autonomous systems, such as self-driving cars or other devices that handle complex interactions with the real world with little or no human intervention, and many other useful things. These applications are perhaps not like the fully autonomous, conscious and intelligent robots that science fiction stories have been predicting, but they are nevertheless important and useful, and most importantly they are real and here today. The growing impact of AI has triggered a kind of'gold rush': we see new research laboratories springing up, new AI start-up companies, and very significant investments, particularly by big digital tech companies, but also by transportation, manufacturing, financial, and many other industries. Management consulting companies are competing in their predictions on how big the economic impact of AI is going to be and governments are responding with strategic planning to see how their countries can avoid staying behind. Although all of this is good news, it cannot be denied that the application of AI comes with certain risks. Several initiatives have been taken in recent years to better understand the risks of AI deployment and came up with legal frameworks, codes of conduct, and value-based design methodologies.