In the final report of the Committee on Artificial Intelligence (AIDA), set to be adopted by the European Parliament today, Renew Europe calls for a regulatory framework to make the EU an AI-leader setting the global standards for an ethically responsible AI infrastructure that respects fundamental rights and supports innovation. "Our aim is to build human-centric AI, which will serve our people while respecting their privacy. The report encourages to use more solutions based on AI and is carried out by the sense of urgency. The European Union must significantly increase its investments in AI so we would have competitive solutions. I hope this report will lead the way in the development of AI in Europe", said Andrus Ansip, Renew Europe's shadow rapporteur on the'Artificial Intelligence in a Digital Age' report.

With wildfires becoming bigger and more destructive as the West dries out and heats up, agencies and officials tasked with preventing and battling the blazes could soon have a new tool to add to their arsenal of prescribed burns, pick axes, chain saws and aircraft. The high-tech help could come way of an area not normally associated with fighting wildfires: artificial intelligence. Lockheed Martin Space, based in Jefferson County, Colo., is tapping decades of experience of managing satellites, exploring space and providing information for the U.S. military to offer more accurate data quicker to ground crews. They are talking to the U.S. Forest Service, university researchers and a Colorado state agency about how their their technology could help. By generating more timely information about on-the-ground conditions and running computer programs to process massive amounts of data, Lockheed Martin representatives say they can map fire perimeters in minutes rather than the hours it can take now.

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In a live interview with the Washington Post last week, New York-based Clearview AI's co-founder and CEO Hoan Ton-That addressed questions about the ethical and legal implications of his software, which became first known to many Americans when a billionaire used it to identify his daughter's dinner date, and for the involvement of far-right individuals in the creation of the company. Pressed on questions about the legal and ethical choices his firm has made while creating a searchable database of 20 billion facial images, Ton-That repeatedly brought up examples where the use cases of Clearview AI's technology would look better in the public eye, mentioning its use in helping catch criminals in child pornography and child abuse cases. Ton-That also pointed to the use of Clearview AI's technology by the Ukrainian government to identify dead Russian soldiers, for notifying their families of their passing.

A joint research collaboration between US universities and IBM has formulated a proof-of-concept adversarial attack that's theoretically capable of causing stock market losses, simply by changing one word in a retweet of a Twitter post. In one experiment, the researchers were able to hobble the Stocknet prediction model with two methods: a manipulation attack and a concatenation attack. The attack surface for an adversarial attack on automated and machine learning stock prediction systems is that a growing number of them are relying on organic social media as predictors of performance; and that manipulating this'in-the-wild' data is a process that can, potentially, be reliably formulated. Besides Twitter, systems of this nature ingest data from Reddit, StockTwits, and Yahoo News, among others. The difference between Twitter and the other sources is that retweets are editable, even if the original tweets are not.

"Artificial Intelligence and machine learning … [are] foundational to the future of cybersecurity. We have got to work our way through how we're going to deal with this. It is not the if, it's only the when to me," Adm. Mike Rogers, former chief of the National Security Agency and U.S. Cyber Command, remarked in an interview. During his presidency, Barack Obama shared his concerns about an attacker using artificial intelligence (AI) to access launch codes for nuclear weapons. "If that's its only job, if it's self-teaching and it's just a really effective algorithm, then you've got problems," Obama said.

Artificial intelligence in cybersecurity is a must-have combination for organizations nowadays. Artificial intelligence (AI) assists under-resourced security operations analysts in keeping pace with attacks, and this technology will have a greater role as cyberattacks increase in volume and complexity. AI technologies, such as machine learning and natural language processing that analyze millions of research papers, blogs, and news stories, provide rapid insights to cut through the noise of daily alerts. AI provides analysts with a method to connect the dots between threats. The enterprise attack surface continues to expand and get more complex.

In March, a largely overlooked, 90-page Government Accountability Office study revealed something interesting: This summer, the Pentagon is getting a new AI Strategy. Between shaping ethical norms for AI and establishing a new Chief Data and AI Officer, it's clear top brass have big plans for the technology, though the report is light on the details. Released in 2018, the last AI Strategy laid the scaffolding for the U.S. military's high-tech competition with China. But over the past four years one thing has become apparent: The United States needs a balanced approach to AI investment -- one that doesn't simply guard against threats, but also imposes costs on a Chinese force that sees AI as the key to victory. Undoubtedly, a military conflict between the United States and China would be catastrophic, and every effort must be taken to avoid such an outcome through diplomatic means.

In the world of computer science and artificial intelligence, few topics are generating as much interest as the rise of so-called "foundation models." These models can be thought of as meta-AI--but not Meta-AI, if you see what I mean--systems that incorporate vast neural networks with even bigger datasets. They are able to process a lot but, more importantly, they are easily adaptable across information domain areas, shortening and simplifying what has previously been a laborious process of training AI systems. If foundation models fulfill their promise, it could bring AI into much broader commercial use. To give a sense of the scale of these algorithms, GPT-3, a foundation model for natural language processing released two years ago, contains upwards of 170 billion parameters, the variables that guide functions within a model.

Just when you thought modern life couldn't get any crazier, a video emerged during the run-up to the recent UK election, in which the Prime Minister Boris Johnson appeared to endorse his political opponent Jeremy Corbyn. "Appeared" is the important word here, because this was actually just one of the latest in a steady stream of deepfakes – video and audio clips in which artificial intelligence simulates real people doing unreal things. Of course, humans have been faking it for centuries. From tattoos and piercings to face paints and wigs, we love altering ourselves and indulging in a bit of make-believe. My own little secret for years was that I wore green-coloured contact lenses. I did need them for short-sightedness – the colour was purely a personal choice.