Manifold-valued functional data analysis (FDA) recently becomes an active area of research motivated by the raising availability of trajectories or longitudinal data observed on non-linear manifolds. The challenges of analyzing such data come from many aspects, including infinite dimensionality and nonlinearity, as well as time-domain or phase variability. In this paper, we study the amplitude part of manifold-valued functions on $\mathbb{S}^2$, which is invariant to random time warping or re-parameterization. Utilizing the nice geometry of $\mathbb{S}^2$, we develop a set of efficient and accurate tools for temporal alignment of functions, geodesic computing, and sample mean calculation. At the heart of these tools, they rely on gradient descent algorithms with carefully derived gradients. We show the advantages of these newly developed tools over its competitors with extensive simulations and real data and demonstrate the importance of considering the amplitude part of functions instead of mixing it with phase variability in manifold-valued FDA.

With the increasing trend in the topic of migration in Europe, the public is now more engaged in expressing their opinions through various platforms such as Twitter. Understanding the online discourses is therefore essential to capture the public opinion. The goal of this study is the analysis of social media platform to quantify public attitudes towards migrations and the identification of different factors causing these attitudes. The tweets spanning from 2013 to Jul-2021 in the European countries which are hosts to immigrants are collected, pre-processed, and filtered using advanced topic modeling technique. BERT-based entity linking and sentiment analysis, and attention-based hate speech detection are performed to annotate the curated tweets. Moreover, the external databases are used to identify the potential social and economic factors causing negative attitudes of the people about migration. To further promote research in the interdisciplinary fields of social science and computer science, the outcomes are integrated into a Knowledge Base (KB), i.e., MigrationsKB which significantly extends the existing models to take into account the public attitudes towards migrations and the economic indicators. This KB is made public using FAIR principles, which can be queried through SPARQL endpoint. Data dumps are made available on Zenodo.

The law has been relatively slow to regulate artificial intelligence, but the rules are evolving. An important question is whether an AI company can be held liable for malfunctioning AI. Ryan E. Long writes that a company's liability for its AI depends on whether a defect was present upon the AI release and whether, in the EU at least, the application is "high-risk." Artificial intelligence (AI) use has blossomed. The AI market was valued at $27.3 billion in 2019 and is projected to grow to $266.92 billion by 2026.

A US government agency has formally opened a probe into Tesla's so-called Autopilot system following a spate of well-publicised crashes over the past few years. The investigation covers over three-quarters of a million vehicles, which has got to be a decent chunk of the US inventory shifted by Tesla since the start of the 2014 model year. It is estimated that in past three years alone, Tesla has sold a combined 430,592 units of Model X, Model S, and Model 3 in the United States. The National Highway Traffic Safety Administration's Office of Defects Investigation (ODI) said it was looking into the "level 2" Advanced Driver Assistance System (ADAS), which it said consists of lane-keeping and cruise control functions. "Most incidents took place after dark and the crash scenes encountered included scene control measures such as first responder vehicle lights, flares, an illuminated arrow board, and road cones," the agency said in a statement [PDF] today.

The U.S. government has opened a formal investigation into Tesla's Autopilot partially automated driving system after a series of collisions with parked emergency vehicles. The investigation covers 765,000 vehicles, almost everything that Tesla has sold in the U.S. since the start of the 2014 model year. Of the crashes identified by the National Highway Traffic Safety Administration as part of the probe, 17 people were injured and one was killed. NHTSA says it has identified 11 crashes since 2018 in which Teslas on Autopilot or Traffic Aware Cruise Control have hit vehicles at scenes where first responders have used flashing lights, flares, an illuminated arrow board or cones warning of hazards. The agency announced the action Monday in a posting on its website.

A trio of researchers at Purdue today published pre-print research demonstrating a novel adversarial attack against computer vision systems that can make an AI see – or not see – whatever the attacker wants. It's something that could potentially affect self-driving vehicles, such as Tesla's, that rely on cameras to navigate and identify objects. Up front: The researchers wanted to confront the problem of digital manipulation in the physical world. It's easy enough to hack a computer or fool an AI if you have physical access to it, but tricking a closed system is much harder. Here's how your business can benefit from free citizen data Adversarial attacks and defenses today are predominantly driven by studies in the digital space where the attacker manipulates a digital image on a computer.

VARANASI: A student of the Indian Institute of Technology, Banaras Hindu University (IIT-BHU) claims to have developed the first version of an artificial intelligence-based yoga platform through Multiplayer Yoga Gameplay (MPYG) that will teach how to do yoga in the right manner. Vidyabhushan, a third-year chemical engineering student, has developed the platform with mentorship, funding from NASSCOM Foundation, Cisco Thingcubator and technical support from NCL-IIT BHU Incubation Centre. "MPYG is an innovation in the field of Yoga. It is an artificial intelligence and augmented reality-based community yoga platform. It will make people choose yoga keeping in mind the health-related factors and is designed with the aim of getting people to do yoga in the right way," said Vidyabhushan.

The U.S. government has opened a formal investigation into Tesla's Autopilot partially automated driving system after a series of collisions with parked emergency vehicles. The investigation covers 765,000 vehicles, almost everything that Tesla has sold in the U.S. since the start of the 2014 model year. Of the crashes identified by the National Highway Traffic Safety Administration as part of the probe, 17 people were injured and one was killed. NHTSA says it has identified 11 crashes since 2018 in which Teslas on Autopilot or Traffic Aware Cruise Control have hit vehicles at scenes where first responders have used flashing lights, flares, an illuminated arrow board or cones warning of hazards. The agency announced the action Monday in a posting on its website.

Nuro's delivery autonomous vehicles (AVs) don't have a human driver on board. The company's founders Dave Ferguson (president) and Jiajun Zhu's (CEO) vision of a driverless delivery vehicle sought to do away with a lot of the stuff that is essential for a normal car to have, like doors and airbags and even a steering wheel. They built an AV that spared no room in the narrow chassis for a driver's seat, and had no need for an accelerator, windshield or brake pedals. So when the company petitioned the U.S. government in 2018 for a minor exemption from rules requiring a rearview mirror, backup camera and a windshield, Nuro might have assumed the process wouldn't be very arduous. In a 2019 letter to the U.S. Department of Transportation, The American Association of Motor Vehicle Administrators (AAMVA) "[wondered] about the description of pedestrian'crumple zones,' and whether this may impact the vehicle's crash-worthiness in the event of a vehicle-to-vehicle crash. Even in the absence of passengers, AAMVA has concerns about cargo ejection from the vehicle and how Nuro envisions protections from loose loads affecting the driving public."

US safety officials opened a preliminary investigation into Tesla's Autopilot after identifying 11 crashes involving the driver assistance system, officials said Monday. The incidents dating back to 2018 included one fatal crash and seven that resulted in injuries, according to the National Highway Traffic Safety Administration. Tesla founder Elon Musk has defended the Autopilot system and the electric automaker warns that it requires "active driver supervision" behind the wheel, but critics, including in Congress, say the system can be easily fooled and have called for NHTSA to take action. Testers with the magazine Consumer Reports demonstrated in a video that Autopilot could be fooled into driving with nobody behind the wheel, an exercise also shown in widely-seen videos on Tik-Tok and other social media platforms. "A preliminary evaluation starts the agency's fact-finding mission and allows additional information and data to be collected," a NHTSA spokesperson said.