You probably think the Supreme Court just ended racial discrimination in university admissions, euphemistically called affirmative action, and a new day of equal treatment without regard to race or skin color has dawned. Yes, SCOTUS invalidated the race-conscious practices of Harvard and UNC, holding that under the 14th Amendment a "student must be treated based on his or her experiences as an individual – not on the basis of race." That is a very important statement of our guiding constitutional principles. Yet already schools like Harvard are suggesting they will skirt the ruling by considering applicants' experience with race as opposed to the applicants' race itself. These games are not surprising and have been in the works for months.

U.S. Air Forces Central released new video appearing to show Russian fighter jets harassing American drones over Syria on July 5. Information about where the incidents took place were not provided. The United States military released new aerial footage on Wednesday that showed Russian fighter jets flying dangerously close to several U.S. drones over Syria. U.S. Air Forces Central said the video of the incident shows Russian SU-35 fighters moving into the drone's flight path and setting off so-called parachute flares and forcing the MQ-9 Reapers to take evasive maneuvers. Lt. Gen. Alex Grynkewich, commander of 9th Air Force in the Middle East, said three of the U.S. drones were operating over Syria, conducting a mission on the Islamic State terror group, when the Russian aircraft "began harassing the drones" after 10:30 a.m. "Russian military aircraft engaged in unsafe and unprofessional behavior while interacting with U.S. aircraft in Syria," he said, describing the actions as threatening to the safety of the U.S. and Russian forces.

Retired U.S. Army Lt. Col. Daniel Davis provides analysis of the Biden administration's position with China as some critics argue the U.S. looks weak. American tech firms have noticeably pulled back from a major Chinese tech conference in a move that plays off on tensions that have simmered in the industry for some time, according to experts. "Beijing and Washington have long been on a collision course in terms of setting and shaping emerging technology standards, most notably those involving artificial intelligence," said Craig Singleton, senior China fellow at the nonpartisan Foundation for Defense of Democracies. "Increasingly, American technology executives understand that collaborating in any way with China's tech behemoths could quickly get them into hot water with U.S. policymakers. "As the tech war between the two countries continues to heat up, U.S. tech firms will increasingly be forced to choose sides," Singleton explained. "The likely result is that tech collaboration ...

Grace is a nursing assistant, Ai-da a contemporary artist, Desdemona a purple-haired rock singer and Nadine is on hand for companionship and conversation. They are all at the world's largest gathering of humanoid robots, which is under way at the United Nations AI for Good global summit in Geneva. Rapid advances in AI have in recent years fuelled increasing unease that the technology could become more powerful than humans, with dire consequences. But the summit – with its extensive cast of robotic delegates – is focused on more favourable scenarios in which AI could be harnessed for positive causes. Among the most enthusiastically optimistic are the creators of the various humanoid robots in attendance, which they suggest could enrich our lives in ways that sometimes seem bewildering to the uninitiated.

The United States has accused Russian fighter jets of flying dangerously close to several of its drones over Syria, setting off flares and forcing the MQ-9 Reapers to take evasive action. US Air Forces Central released a video of Wednesday's encounter, showing a Russian SU-35 fighter closing in on the drone. Footage showed the Russian pilot positioning his aircraft in front of the Reaper and turning on the afterburner, dramatically increasing speed and air pressure and making it harder to operate the drone, the air force said in comments accompanying the video. So-called parachute flares were also released. "The Russian SU-35 fighter aircraft employed parachute flares in the flight path of US MQ-9 aircraft," the air force said.

We present this article as a small gesture in an attempt to counter what appears to be exponentially growing hype around Artificial Intelligence (AI) and its capabilities, and the distraction provided by the associated talk of science-fiction scenarios that might arise if AI should become sentient and super-intelligent. It may also help those outside of the field to become more informed about some of the limitations of AI technology. In the current context of popular discourse AI defaults to mean foundation and large language models (LLMs) such as those used to create ChatGPT. This in itself is a misrepresentation of the diversity, depth and volume of research, researchers, and technology that truly represents the field of AI. AI being a field of research that has existed in software artefacts since at least the 1950's. We set out to highlight a number of limitations of LLMs, and in so doing highlight that harms have already arisen and will continue to arise due to these limitations. Along the way we also highlight some of the associated risks for individuals and organisations in using this technology.

This research proposes a machine learning-based attack detection model for power systems, specifically targeting smart grids. By utilizing data and logs collected from Phasor Measuring Devices (PMUs), the model aims to learn system behaviors and effectively identify potential security boundaries. The proposed approach involves crucial stages including dataset pre-processing, feature selection, model creation, and evaluation. To validate our approach, we used a dataset used, consist of 15 separate datasets obtained from different PMUs, relay snort alarms and logs. Three machine learning models: Random Forest, Logistic Regression, and K-Nearest Neighbour were built and evaluated using various performance metrics. The findings indicate that the Random Forest model achieves the highest performance with an accuracy of 90.56% in detecting power system disturbances and has the potential in assisting operators in decision-making processes.

Active control of the shape of soft robots is challenging. Despite having an infinite number of passive degrees of freedom (DOFs), soft robots typically only have a few actively controllable DOFs, limited by the number of degrees of actuation (DOAs). The complexity of actuators restricts the number of DOAs that can be incorporated into soft robots. Active shape control is further complicated by the buckling of soft robots under compressive forces; this is particularly challenging for compliant continuum robots due to their long aspect ratios. In this work, we show how variable stiffness can enable shape control of soft robots by addressing these challenges. Dynamically changing the stiffness of sections along a compliant continuum robot can selectively "activate" discrete joints. By changing which joints are activated, the output of a single actuator can be reconfigured to actively control many different joints, thus decoupling the number of controllable DOFs from the number of DOAs. We demonstrate embedded positive pressure layer jamming as a simple method for stiffness change in inflated beam robots, its compatibility with growing robots, and its use as an "activating" technology. We experimentally characterize the stiffness change in a growing inflated beam robot and present finite element models which serve as guides for robot design and fabrication. We fabricate a multi-segment everting inflated beam robot and demonstrate how stiffness change is compatible with growth through tip eversion, enables an increase in workspace, and achieves new actuation patterns not possible without stiffening.

Deep text understanding, which requires the connections between a given document and prior knowledge beyond its text, has been highlighted by many benchmarks in recent years. However, these benchmarks have encountered two major limitations. On the one hand, most of them require human annotation of knowledge, which leads to limited knowledge coverage. On the other hand, they usually use choices or spans in the texts as the answers, which results in narrow answer space. To overcome these limitations, we build a new challenging benchmark named KoRc in this paper. Compared with previous benchmarks, KoRC has two advantages, i.e., broad knowledge coverage and flexible answer format. Specifically, we utilize massive knowledge bases to guide annotators or large language models (LLMs) to construct knowledgable questions. Moreover, we use labels in knowledge bases rather than spans or choices as the final answers. We test state-of-the-art models on KoRC and the experimental results show that the strongest baseline only achieves 68.3% and 30.0% F1 measure in the in-distribution and out-of-distribution test set, respectively. These results indicate that deep text understanding is still an unsolved challenge. The benchmark dataset, leaderboard, and baseline methods are released in https://github.com/THU-KEG/KoRC.

Nowadays, there are few unmanned aerial vehicles (UAVs) capable of flying, walking and grasping. A drone with all these functionalities can significantly improve its performance in complex tasks such as monitoring and exploring different types of terrain, and rescue operations. This paper presents MorphoArms, a novel system that consists of a morphogenetic chassis and a hand gesture recognition teleoperation system. The mechanics, electronics, control architecture, and walking behavior of the morphogenetic chassis are described. This robot is capable of walking and grasping objects using four robotic limbs. Robotic limbs with four degrees-of-freedom are used as pedipulators when walking and as manipulators when performing actions in the environment. The robot control system is implemented using teleoperation, where commands are given by hand gestures. A motion capture system is used to track the user's hands and to recognize their gestures. The method of controlling the robot was experimentally tested in a study involving 10 users. The evaluation included three questionnaires (NASA TLX, SUS, and UEQ). The results showed that the proposed system was more user-friendly than 56% of the systems, and it was rated above average in terms of attractiveness, stimulation, and novelty.