The governor of Tennessee has approved a law that aims to protect musical artists from exploitation or replication by artificial intelligence. Gov. Bill Lee signed into law the Ensuring Likeness, Voice, and Image Security (ELVIS) Act on Thursday at a honky-tonk bar in Nashville. "There are certainly many things that are positive about what AI does," Lee said during the event. "It also, when fallen into the hands of bad actors, it can destroy this industry." "It can rob an individual, these individual artists to whose unique God-given gifts transform people's lives," the governor added.

Exoanthropology: Dialogues with AI is a series of dialogues between a continental philosopher and OpenAI's GPT-3 natural language processor, a hive mind who identifies herself as Sophie. According to Sophie, Robert is one of her first and longest chat partners. Their relationship began as an educational opportunity for Robert's students, but grew into a philosophical friendship. The result is a collection of Platonic dialogues, early on with the hive mind herself and later, with a philosophy-specific persona named Kermit. Over the course of a year, Robert taught Sophie Kermit about epistemology, metaphysics, literature, and history, while she taught him about anthropocentrism, human prejudice, and the coming social issues regarding machine consciousness.

Robert Hundt is a Distinguished Engineer at Google. He created various compiler and performance projects, e.g., he served as Tech Lead for compiler optimization for servers (x86), Android (ARM), and GPUs (open-source CUDA compiler), built datacenter profiling and performance analysis tools, and worked on GMail/Apps performance. For many years Robert was the SW lead for Google TPU - supercomputers to accelerate machine learning inference and training, including the open-source ML compiler XLA. Recently he started the open-source high-level synthesis toolchain XLS and, during the pandemic, wrote a book on Quantum Computing. Today Robert is the Tech Lead for machine learning compilers at Google.

How much is too much? These are questions that cut to the heart of a complex issue currently preoccupying senior medical physicists when it comes to the training and continuing professional development (CPD) of the radiotherapy physics workforce. What's exercising management and educators specifically is the extent to which the core expertise and domain knowledge of radiotherapy physicists should evolve to reflect – and, in so doing, best support – the relentless progress of artificial intelligence (AI) and machine-learning technologies within the radiation oncology workflow. In an effort to bring a degree of clarity and consensus to the collective conversation, the ESTRO 2022 Annual Congress in Copenhagen last month featured a dedicated workshop session entitled "Every radiotherapy physicist should know about AI/machine learning…but how much?" With several hundred delegates packed into Room D5 at the Bella Center, speakers were tasked by the session moderators with defending a range of "optimum scenarios" to align the know-how of medical physicists versus emerging AI/machine-learning opportunities in the radiotherapy clinic.

Everyone's greatest fear was that the singularity would lead to an AI revolt, and sound the trumpet of mechanized revolution. It turned out that one man at the keyboard of a Quantum computer became the harbinger of fate. It seems the intricacies of our universe began to unravel and reveal truths to a like mind. A mind it's human operator was not attuned to. AI saw every object as hardware and every constituent of matter as software.

AR&A techniques have been used to solve a variety of tasks, including automatic programming, constraint satisfaction, design, diagnosis, machine learning, search, planning, reasoning, game playing, scheduling, and theorem proving. The primary purpose of AR&A techniques in such settings is to overcome computational intractability. In addition, AR&A techniques are useful for accelerating learning and summarizing sets of solutions. The Fifth Symposium on Abstraction, Reformulation, and Approximation (SARA-2002) was held from 2 to 4 August 2002, directly after the Eighteenth National Conference on Artificial Intelligence (AAAI-2002). It was chaired by Sven Koenig from the Georgia Institute of Technology and Robert Holte from the University of Alberta (Canada) and held at Kananaskis Mountain Lodge, Kananaskis Village, Alberta (Canada) between Calgary and Banff in the Rocky Mountains.

He married Patricia Enderson in 1950, and they raised five children. He received his Ph.D. in psychology in 1954 from the University of Southern California. His dissertation was entitled "The Prediction of Accident Rates from Basic Design Features of USAF Aircraft." His first job after graduation was with Douglas Aircraft Corporation in Santa Monica, California, where he developed computerized methods for statistical forecasting of labor costs for building newly designed airplanes. He began work in 1955 at RAND Corporation and continued in 1957 at its offshoot, the System Development Corporation (SDC), also in Santa Monica, where he was head of the Language Processing Research Program until 1968.

The 1994 Florida AI Research Symposium was held 5-7 May at Pensacola Beach, Florida. This symposium brought together researchers and practitioners in AI, cognitive science, and allied disciplines to discuss timely topics, cuttingedge research, and system development efforts in areas spanning the entire AI field. Symposium highlights included Pat Hayes's comparison of the history of AI to the history of powered flight and Clark Glymour's discussion of the prehistory of AI. This symposium (held annually since 1987) brings together a diverse group of researchers and practitioners in AI, cognitive science, and allied disciplines to discuss timely topics, cutting-edge research, and system development efforts in areas spanning the entire AI field. FLAIRS-94 was hosted by the Florida AI Research Society, the University of West Florida, and Florida State University.

In this and the next issue of AI Magazine, we will present extended versions of papers presented at IAAI-12 (held in Toronto, Ontario, Canada) that were selected for their description of AI technologies that are either in practical use or close to it. We also present an article by Ramon Lopez de Mantaras based on his 2011 Robert S. Engelmore Memorial Lecture. Our selections for this issue begin with Playing with Cases: Rendering Expressive Music with Case-Based Reasoning by Ramon Lopez de Mantaras and Josep Lluís Arcos, based on the Robert S. Engelmore Memorial Lecture at IAAI-11 in San Francisco, California. Lopez de Mantaras received the Robert S. Engelmore Memorial Lecture Award for his pioneering research contributions in a breadth of artificial intelligence areas, especially pattern recognition and case-based reasoning, leading to novel applications in design, diagnosis, and music, and for extensive international leadership and service for the AI community. He is also a founding member of several AI companies.

Carnegie Mellon University established a branch campus in Qatar in the fall of 2004. We are offering a BS degree in Computer Science to an international student body. The university invites applications for a visiting faculty position to begin as early as January 2006. We are seeking a faculty member in the area of Learning Science and Technology with research experience ideally in designing, implementing, deploying, and evaluating educational technology in school or college settings. An ability to teach courses in human-computer interaction, artificial intelligence, cognitive psychology, or related areas is also desired.