Modern vehicles, including connected vehicles and autonomous vehicles, nowadays involve many electronic control units connected through intra-vehicle networks to implement various functionalities and perform actions. Modern vehicles are also connected to external networks through vehicle-to-everything technologies, enabling their communications with other vehicles, infrastructures, and smart devices. However, the improving functionality and connectivity of modern vehicles also increase their vulnerabilities to cyber-attacks targeting both intra-vehicle and external networks due to the large attack surfaces. To secure vehicular networks, many researchers have focused on developing intrusion detection systems (IDSs) that capitalize on machine learning methods to detect malicious cyber-attacks. In this paper, the vulnerabilities of intra-vehicle and external networks are discussed, and a multi-tiered hybrid IDS that incorporates a signature-based IDS and an anomaly-based IDS is proposed to detect both known and unknown attacks on vehicular networks. Experimental results illustrate that the proposed system can detect various types of known attacks with 99.99% accuracy on the CAN-intrusion-dataset representing the intra-vehicle network data and 99.88% accuracy on the CICIDS2017 dataset illustrating the external vehicular network data. For the zero-day attack detection, the proposed system achieves high F1-scores of 0.963 and 0.800 on the above two datasets, respectively. The average processing time of each data packet on a vehicle-level machine is less than 0.6 ms, which shows the feasibility of implementing the proposed system in real-time vehicle systems. This emphasizes the effectiveness and efficiency of the proposed IDS.

Scholars have recently drawn attention to a range of controversial issues posed by the use of computer vision for automatically generating descriptions of people in images. Despite these concerns, automated image description has become an important tool to ensure equitable access to information for blind and low vision people. In this paper, we investigate the ethical dilemmas faced by companies that have adopted the use of computer vision for producing alt text: textual descriptions of images for blind and low vision people, We use Facebook's automatic alt text tool as our primary case study. First, we analyze the policies that Facebook has adopted with respect to identity categories, such as race, gender, age, etc., and the company's decisions about whether to present these terms in alt text. We then describe an alternative -- and manual -- approach practiced in the museum community, focusing on how museums determine what to include in alt text descriptions of cultural artifacts. We compare these policies, using notable points of contrast to develop an analytic framework that characterizes the particular apprehensions behind these policy choices. We conclude by considering two strategies that seem to sidestep some of these concerns, finding that there are no easy ways to avoid the normative dilemmas posed by the use of computer vision to automate alt text.

Cosmological simulations are indispensable for understanding our Universe, from the creation of the cosmic web to the formation of galaxies and their central black holes.

On May 25, 1961, President John F. Kennedy delivered a 46-minute speech that included historical context of the Cold War and how the US planned to triumph over the Soviets, but what won the hearts of the American people was his plan to send humans to the moon. 'Space is open to us now; and our eagerness to share its meaning is not governed by the efforts of others. We go into space because whatever mankind must undertake, free men must fully share...,' the late president said while standing behind the lectern during a joint session of Congress. 'First, I believe that this nation should commit itself to achieving the goal, before this decade is out, of landing a man on the moon and returning him safely to the earth.' The US had not even sent a human into orbit at the time of the speech, which placed it far behind the Soviets who had sent an astronaut to space a month before Kennedy addressed the nation.

The European Commission has come up with a detailed proposal for the controlled use of Artificial Intelligence on 21st April 2021, to be followed by the states of the European Union. Tech experts are expecting these regulations to have a great impact on MNCs like Amazon, Facebook, Google, or Microsoft where Europe is in a leading position to drive the digital industry. The proposal is further accompanied by a list of regulations to be applied in the use of AI in machinery. Decades after the invention, there remains a lot of uncharted territory in the world of artificial intelligence, which makes it unpredictable and prone to be used with wrong intentions. To make AI trustworthy to people, the European Commission has come up with this harmonious set of rules that has the scope to be used universally.

ACM fellow Jack Minker passed away on April 9, 2021, at the age of 93. Minker was a leader in the development of automating logistic reasoning, including deductive databases, logic programming, and artificial intelligence, but he is perhaps best known for his efforts to promote the social responsibility of scientists and human rights. In 1972, Minker was invited to join the newly constituted Committee of Concerned Scientists. He was asked to help identify Soviet computer scientists whose human rights were under attack by their government, frequently because of their career choices or because they had requested permission to emigrate from the Soviet Union. "It was something I could not refuse to do," said Jack in 2011.

Over the last decade, deep learning systems have shown an astonishing ability to classify images, translate languages, and perform other tasks that once seemed uniquely human. However, these systems work opaquely and sometimes make elementary mistakes, and this fragility could be intentionally exploited to threaten security or safety. In 2018, for example, a group of undergraduates at the Massachusetts Institute of Technology (MIT) three-dimensionally (3D) printed a toy turtle that Google's Cloud Vision system consistently classified as a rifle, even when viewed from various directions. Other researchers have tweaked an ordinary-sounding speech segment to direct a smart speaker to a malicious website. These misclassifications sound amusing, but they could also represent a serious vulnerability as machine learning is widely deployed in medical, legal, and financial systems.

We demonstrate the potential of a novel form of encoding, race logic, in which information is represented as the delay in the arrival of a signal.

In May 1948, women were strikingly prominent in ACM. Founded just months earlier as the "Eastern Association for Computing Machinery," the new professional society boldly aimed to "advance the science, development, construction, and application of the new machinery for computing, reasoning, and other handling of information."36 No fewer than 27 women were ACM members, and many were leaders in the emerging field.a Among them were the pioneer programmers Jean Bartik, Ruth Lichterman, and Frances Snyder of ENIAC fame; the incomparable Grace Murray Hopper who soon energized programming languages; Florence Koons from the National Bureau of Standards and U.S. Census Bureau; and noted mathematician-programmer Ida Rhodes.26 During the war, Gertrude Blanch had organized a massive human computing effort (a mode of computation made visible in the 2016 film Hidden Figures47) and, for her later service to the US Air Force, became "one of the most well-known computer scientists and certainly the most visible woman in the field."24,25 Mina Rees, a mathematics Ph.D. like Hopper and Blanch, notably funded mathematics and computing through the Office of Naval Research (1946–1953), later serving as the first female president of the American Association for the Advancement of Science. In 1949, Rees was among the 33 women (including at least seven ACM women) who participated in an international conference at Harvard University, chairing a heavyweight session on "Recent Developments in Computing Machinery."29

The future is hurtling toward us, and with each passing day AI is getting smarter. We've seen AI that will play your games for you, and if you're using a 30-series Nvidia GPU, you've probably utilised the company's DLSS supersampling AI tech to upscale your game resolutions. But I bet you weren't aware AI can now not only detect sarcasm, it can also then rap about it. Even we humans have trouble with sarcasm in it's written form, especially in the case of Twitter where the majority of users refuse to use punctuation. Thankfully a study from DARPA researchers, at the University of Central Florida, has birthed an AI that can recognise the tone of an internet troll with over 80% accuracy on Reddit, and on Twitter it surpasses 90% accuracy (via Engadget).