Traditionally in the domain of legal research, the retrieval of pertinent citations from intricate case descriptions has demanded manual effort and keyword-based search applications that mandate expertise in understanding legal jargon. Legal case descriptions hold pivotal information for legal professionals and researchers, necessitating more efficient and automated approaches. We propose a methodology that combines natural language processing (NLP) and machine learning techniques to enhance the organization and utilization of legal case descriptions. This approach revolves around the creation of textual embeddings with the help of state-of-art embedding models. Our methodology addresses two primary objectives: unsupervised clustering and supervised citation retrieval, both designed to automate the citation extraction process. Although the proposed methodology can be used for any dataset, we employed the Supreme Court of The United States (SCOTUS) dataset, yielding remarkable results. Our methodology achieved an impressive accuracy rate of 90.9%. By automating labor-intensive processes, we pave the way for a more efficient, time-saving, and accessible landscape in legal research, benefiting legal professionals, academics, and researchers.

As voters queued up early morning on November 30 last year to vote in legislative elections to choose the next government of the southern Indian state of Telangana, a seven-second clip started going viral on social media. Posted on X by the Congress party, which is in opposition nationally, and was in the state at the time, it showed KT Rama Rao, a leader of the Bharat Rashtra Samiti that was ruling the state, calling on people to vote in favour of the Congress. The Congress shared it widely on a range of WhatsApp groups "operated unofficially" by the party, according to a senior leader who requested anonymity. It eventually ended up on the official X account of the party, viewed more than 500,000 times. "Of course, it was AI-generated though it looks completely real," the Congress party leader told Al Jazeera.

Imagine flying a small, robotic aircraft from goal post to goal post on an American football field. Now, repeat the flight 470 more times, and you'll match the record-setting 32-mile autonomous drone flight recorded by Aakash Sinha's industry-leading startup based in New Delhi. "It's only the beginning," said Sinha, a 2003 School of Computer Science graduate with a master's degree in robotics. "I'm super excited about how drones can change things, not just here in India but globally." From delivering vaccines in hard-to-reach areas to limiting fossil fuel leaks in expansive pipelines, the possibilities for positive change are endless.

Shared autonomy refers to approaches for enabling an autonomous agent to collaborate with a human with the aim of improving human performance. However, besides improving performance, it may often also be beneficial that the agent concurrently accounts for preserving the user's experience or satisfaction of collaboration. In order to address this additional goal, we examine approaches for improving the user experience by constraining the number of interventions by the autonomous agent. We propose two model-free reinforcement learning methods that can account for both hard and soft constraints on the number of interventions. We show that not only does our method outperform the existing baseline, but also eliminates the need to manually tune a black-box hyperparameter for controlling the level of assistance. We also provide an in-depth analysis of intervention scenarios in order to further illuminate system understanding.

Amazon Web Services Inc. has commissioned its first-ever major art piece, a site-specific sculpture powered by artificial intelligence and designed by artist and architect Suchi Reddy that will be the centerpiece of the Smithsonian's "Futures" exhibit. The artwork, called "me you," was unveiled today in the 90-foot-tall central rotunda of the Smithsonian's historic Arts and Industries Building in Washinton, D.C. It's an important locale as America's first national museum and because the interactive sculpture itself is nearly two stories tall. The sculpture takes up the center of the room, with a base that appears to have large fiber-optic cables sticking out of it toward people with inviting circular interfaces that Reddy (pictured, right) called "mandalas." Rising from the center of the sculpture is a broad, segmented series of panels called a "totem" upon which colorful kinetic patterned lights flow upward, representing interactive futures spoken to the artwork by the public. The idea of the artwork is to present how humans and technology interface and evolve together, Reddy told SiliconANGLE in an interview while she demonstrated the sculpture in action.

The artificial intelligence at the heart of a new art exhibit, "me you," does not judge you necessarily, but it does analyze and interpret what you have to say. Sponsored by Amazon Web Services, the sculpture by artist Suchi Reddy listens to what you have to say about the future and renders your sentiment in a display of colored lights and patterns. The artwork is a centerpiece of a new exhibit at the Smithsonian Arts and Industries Building, which is opening to the public for the first time in 20 years. The exhibition, called Futures, opens Nov. 20. Viewers are invited to interact with the sculpture, which listens for the words "My future is …" at several circular listening posts integrated into the sculpture.

As scientists laid the foundations of artificial intelligence, Pamela McCorduck was there. McCorduck, an author who wrote some of the first novels and histories about AI and was a generous friend of CMU, died Oct. 18. McCorduck described herself as an eyewitness to the birth and growth of AI. She was possibly best known for her 1979 book, "Machines Who Think," which chronicles the history of AI from the dreams and nightmares of ancient poets and prophets to the scientific discoveries of the 20th century. The novel contains the famous quote, "Artificial intelligence began with the ancient wish to forge the gods."

Sepsis is a huge healthcare concern. "You take every single cancer and all the deaths due to every single cancer and you add them all up together. More people die from sepsis worldwide than that," said Bobby Reddy, Jr., CEO of Prenosis, in an interview with MD DI. And even if patients survive, they can have lifelong consequences. "Sepsis occurs when you have a very abnormal, unhealthy reaction to infection," Reddy said.

The Computer History Museum (CHM) in Silicon Valley has honored Raj Reddy, an Indian-American professor and researcher, as part of its 2021 Fellow Awards program to contribute to artificial intelligence and continuous voice recognition. The other three recipients for 2021 were Raymond Ozzie, Lillian F. Schwartz, and Andries van Dam. Reddy, who grew up in the Andhra Pradesh district of Chittoor, has been teaching for five decades and is the founder of The Robotics Institute at Carnegie Mellon University in Pittsburg, Pennsylvania. The AI pioneer was also a driving force behind the Rajiv Gandhi University of Knowledge Technology establishment in Nuzvid, Andhra Pradesh. "New technologies have made it easier than ever to share knowledge and information and reach new audiences in this digital world," Reddy added.

Machine learning helps develop optimal antibody drugs. Antibodies are not only produced by our immune cells to fight viruses and other pathogens in the body. For a few decades now, medicine has also been using antibodies produced by biotechnology as drugs. This is because antibodies are extremely good at binding specifically to molecular structures according to the lock-and-key principle. However, developing such antibody drugs is anything but simple.