Two tech-savvy lawmakers have partnered together with two prominent think tanks to produce a report detailing guidelines for a national artificial intelligence strategy. Will Hurd, R-Texas, and Robin Kelly, D-Ill., joined with the Bipartisan Policy Center and the Center for New American Security to develop a series of white papers exploring topics in artificial intelligence.The first two reports covered national security and the workforce. The third, which was announced Thursday, called on the federal government to effectively double funding for AI research and development. The new report makes 14 recommendations, beginning with the call for increased research and development funding. The aim is to increase funding year over year to reach a goal of $25 billion per year by 2025.

Pre-departure flight plan scheduling for Urban Air Mobility (UAM) and cargo delivery drones will require on-demand scheduling of large numbers of aircraft. We examine the scalability of an algorithm known as FastMDP which was shown to perform well in deconflicting many dozens of aircraft in a dense airspace environment with terrain. We show that the algorithm can adapted to perform first-come-first-served pre-departure flight plan scheduling where conflict free flight plans are generated on demand. We demonstrate a parallelized implementation of the algorithm on a Graphics Processor Unit (GPU) which we term FastMDP-GPU and show the level of performance and scaling that can be achieved. Our results show that on commodity GPU hardware we can perform flight plan scheduling against 2000-3000 known flight plans and with server-class hardware the performance can be higher. We believe the results show promise for implementing a large scale UAM scheduler capable of performing on-demand flight scheduling that would be suitable for both a centralized or distributed flight planning system

Plus, the market size is predicted to reach USD 30.5 billion by 2025. A recent Synack Report claims that combining cybersecurity talent and AI-enabled technology results in 20x more effective attack surface coverage than traditional methods. But it's difficult to truly understand the implication of these numbers. Most content on the topic leaves the reader to do all the math, connect the dots, and try to understand the real problem behind the numbers, all by themselves – an overwhelming task. Two of the most interesting topics on the internet today are Artificial Intelligence and Cybersecurity.

The Labor Department reported Friday unemployment fell to 10.2% as the economy added 1.8 million jobs, fewer than the number added in the two preceding months likely due to an upsurges in coronavirus cases. The Bureau of Labor statistics credited an improving economy as pandemic restrictions were eased. It was the lowest level since the coronavirus pandemic induced a recession in February. The Labor Department, however, admitted data collection may be flawed because of its classification methods, and some people marked as on temporary layoff should be classified as unemployed. The misclassification for June and July was believed smaller than those for previous months.

Artificial Intelligence is most effective in cybersecurity with "a human involved", according to the CTO of internet security company ESET. Speaking at the Slovakian cybersecurity company's Virtual World event, ESET CTO Juraj Malcho explored the ways in which AI and Machine Learning are impacting the security field, but also the challenges they present. Malcho highlighted the fact that AI and machine learning can have important applications in cybersecurity, enabling researchers to find the "needle in the haystack" when using AI to analyse samples or attacks, and can be used to rapidly find common traits in different samples of malware and detect different variations of attacks. He explained how ESET was able to detect 7.7 million Emotet attacks, and identify 3 million attacks that had common traits using machine learning. It was also used to help ESET find the first UEFI rootkit "in the wild", which could then be used to built tools to protect customers from this type of attack. However, Malcho highlighted that AI and machine learning have their limitations in a cybersecurity context, and is wary of companies that "claim they have magic solutions."

Since its conception, people have worried that an artificial intelligence would turn against humanity and threaten our lives. While this may be a result to be feared several years in the future, right now the more pressing danger is AI used to oppress millions of people and facilitate the threat of a controlling regime. Homebound in the pandemic quarantine, my daughter and I have been rewatching Person of Interest on Netflix. In essence, the former network series is about a man who created a nearly omniscient artificial intelligence that watches everyone through networks of cameras, computers and smartphones. Each week, our team of heroes, assembled by the AI creator, tries to help a person whom the AI has identified as a likely soon-to-be murder victim.

Rev has you covered on political transcripts leading up to the 2020 election cycle! We transcribe debates, interviews, speeches, congressional testimonies, and more.

Every millimeter of Beijing is monitored by state-of-the-art surveillance cameras, according to the Beijing Public Safety Bureau. Facial recognition algorithms matched with images filed away in a secret database could see you in legal trouble for something you did near your front door. A semi-political post made in a private chat could lead to the loss of your job. Yet it is only the tip of the iceberg -- and the very beginning -- of the rise of technologically-advanced China and its dystopian dreams. It might be a deterrent to crime, as the Chinese Communist Party (CCP) leadership advocates, but it also means a substantial loss of privacy and saps any semblance of free expression.

As attackers constantly evolve their tactics to side-step more traditional defenses, artificial intelligence and machine learning technologies are stepping in to help organizations improve defenses. Technologies like MessageControl offer a critical extra layer of protection, especially when fully integrated into a multi-tenant platform to help inform cross-product detection. A Capgemini Research Institute study found that 69% of senior executive respondents said they would be unable to respond to a cyberattack without artificial intelligence. The same study found two-thirds of organizations plan to employ artificial intelligence by 2020, demonstrating the mandate security leaders face in implementing this technology in a focused and valuable way: at their email perimeters and inside their organizations. By constantly'learning' an organization's environment and user behaviors to get smarter over time, a baseline of normal is created, with deviations from that highlighting potential threats.

The SEC said, "Musk,/your tweets are a blight./They Musk cried, "Why?/The tweets I wrote are not mean,/I don't use all-caps/and I'm sure that my tweets are clean."/"But THE PRECEDING lines--describing Tesla and SpaceX founder Elon Musk's run-ins with the Securities and Exchange Commission, an American financial regulator--are not the product of some aspiring 21st-century Dr Seuss. They come from a poem written by a computer running a piece of software called Generative Pre-Trained Transformer 3. GPT-3, as it is more commonly known, was developed by OpenAI, an artificial-intelligence (AI) laboratory based in San Francisco, and which Mr Musk helped found. It represents the latest advance in one of the most studied areas of AI: giving computers the ability to generate sophisticated, human-like text.