Dave's Hot Chicken is the top app in the iOS App Store, ending Sora's weeks-long reign. On Friday, its reign came to an end. Your new champion is Dave's Hot Chicken. Dave's Hot Chicken now rules over the App Store, where its slack-beaked, bug-eyed mascot icon expresses appropriate surprise at its ascent. How did it break the grasp of OpenAI's golem TikTok?

In the early 2000s, Mike Sellers was working on social AI agents for DARPA. During one simulation, two AI agents named Adam and Eve were given a few basic skills. They knew how to eat, but not what to eat. When they tried to eat apples from a tree, they felt happy. When they tried to eat wood from the same tree they didn't get any reward.

AI Magazine Volume 18 Number 2 (1997) ( AAAI) Date: 4/1/2002 WASA -- World Aeronautics & Space Administration Executive Summary of Committee Report on Disaster Investigation, Incident # 362 Analysis of records downloaded from the 2001 Jupiter Orbital Black Parallelopiped Investigation Mission indicates that the basic source of failure was excessive emotional stress in the HAL computer, leading to a previously unknown condition now called Computational Paranoia. This in turn was an unforeseen side-effect of the design of the HAL-9000 series. HAL was given a genuine personality, enabling it to act as an onboard psychiatric advisor, colleague, and confidante to the human crew members. As a consequence, much of HAL's perceptual software was devoted to reading subtleties of facial expression, unconscious intonation stresses, and other emotional signals. Its performance at empathy and emotional insight was at least two orders of magnitude (as measured by the Kraft-Ebbing-Rachmaninoff method) better than that of the rest of the crew.

It was written not by a human being, but by my computer program EWI (an acronym for "experiments in writing intelligence"). EWI was fed the texts of two of Hofstadter's books--namely, Gödel, Escher, Bach (winner of the Pulitzer Prize for General Nonfiction in 1980) and Metamagical Themas--and then, following its code, EWI carefully analyzed these two books for their uniquely Hofstadterian stylistic elements and features, after which it recombined these stylistic elements in new fashions. EWI thereby came up with some 25 new and highly diverse "Hofstadter articles," one of which is given below, and the article is followed by a brief commentary about EWI and its output by Hofstadter himself. Actually, I should state up front that the wonderful sparkling dialogues of GEB, which are a substantial part of that book, were not used by EWI in generating any of the articles, because EWI is unfortunately not yet able to work with inputs that belong to different genres, such as chapters and dialogues. To combine stylistic aspects of two or more different genres of writing represents a very thorny challenge indeed.

Waltz served as Association for the Advancement of Artificial Intelligence (AAAI) president from 1997 to 1999, was a Fellow of AAAI and the Association for Computing Machinery (ACM), a senior member of the Institute for Electrical and Electronics Engineers (IEEE), and former chair of the ACM Special Interest Group on Artificial Intelligence (SIGART). Prior to joining CCLS, he was president of the NEC Research Institute in Princeton, and from 1984-1993 was director of Advanced Information Systems at Thinking Machines Corporation and a professor of computer science at Brandeis University. A celebration of his life was held in the spring of 2012, and a symposium in his honor was held September 23, 2012, at Brandeis University in Waltham, Massachusetts. That dissertation created the field of constraint propagation by showing that constraints and a rich but simple descriptive system were sufficient to recover threedimensional information from a two-dimensional projection. Besides an education, Dave picked up a passion for the highenergy atmosphere that propelled the MIT AI Lab to prominence -- an atmosphere that he spent the rest of his life recreating. In 1973, Dave Waltz with Richard P. Gabriel in tow headed west from MIT to the University of Illinois at Urbana-Champaign (UIUC) with the goals of starting a first-rate AI program and creating a lab in the image of the MIT AI Lab. All they had were an enthusiastic home in the Coordinated Science Laboratory, some friendly faculty in the Electrical Engineering department, a PDP-10, a shaky connection to the Advanced Research Projects Agency Network (ARPANET), and a small but eager coterie of misfit graduate students.

Bureaucrats don't just come in uniforms and peaked caps. They come in 1U racks, too. They'll deny you credit, charge you more for paperclips that someone in another neighbourhood, and maybe even stop you getting out of jail. Algorithms are calling the shots these days, and they may not be as impartial as you thought. To some, algorithmic bias is a growing problem.

Meet Dave: an AI dressed up in a bearsuit that's just launched to save you from the evils of expensive overdraft fees. Hand Dave access to your checking account and the app's machine learning algorithms will get busy crunching your spending data so the bear can warn you about pending transactions -- like a monthly subscription for Netflix or your typical Saturday night Uber bill -- which might push you into the red and incur an expensive bank penalty. The US-only app predicts a user's "7 Day Low", aka the lowest it thinks your bank balance will drop in the next seven days, in order to encourage and support better money management. The ultimate aim being to help people avoid having to fall back on their overdraft as "an expensive form of credit", says co-founder Jason Wilk, describing it as a sort of "weather forecast" for money management. Dave also includes a payday loan facility -- so users who face the inevitability of having to dip into a negative balance can opt to borrow up to $250 ahead of their next paycheck to see them through.

In a new automotive application, we have used convolutional neural networks (CNNs) to map the raw pixels from a front-facing camera to the steering commands for a self-driving car. This powerful end-to-end approach means that with minimum training data from humans, the system learns to steer, with or without lane markings, on both local roads and highways. The system can also operate in areas with unclear visual guidance such as parking lots or unpaved roads. We designed the end-to-end learning system using an NVIDIA DevBox running Torch 7 for training. An NVIDIA DRIVETM PX self-driving car computer, also with Torch 7, was used to determine where to drive--while operating at 30 frames per second (FPS).

On a very warm afternoon in April, the image of a bald young white man's head floated on a gray screen at the Kitchen, in Chelsea. The man spoke in a tone that shifted worryingly between aggressive and confessional, punctuating his lines with two disembodied hands. "And I could have been your haruspex, sexy," he said at one point, snarling. "I could have read omens in your extricated liver." There were pale red marks beneath his eyes, a five-o'clock shadow on his jaw.

David L. Waltz (1943-2012), was director, Center for Computational Learning Systems In 1973, Dave Waltz with Richard P. Gabriel in tow headed Dave Waltz delivers his AAAI Presidential Address at AAAI-98 in Madison, Wisconsin. While at Illinois, Dave produced system, paving the way for an engineering-style 11 Ph.D. students and many more MS students, approach to emergent AI techniques; and even mentored junior researchers and postdocs, attracted though their first attempts to create a multidisciplinary new AI faculty, and helped create the Beckman AI degree program failed, Dave was able in Institute for Advanced Science and Technology. In 1984, Marvin Minsky asked Dave to return to During the late 1970s and early 1980s, Waltz's Thinking Machines, Inc., an MIT spinoff in Cambridge group explored new ideas in natural language processing, -- with the temptation that the atmosphere cognitive science, qualitative reasoning, would be like the early days of the AI Lab all over and parallel computation in a collaborative environment again. At the same time he took a parttime including researchers in computer science, tenured position at Brandeis. Machines and Brandeis, Dave developed the ideas He chaired and brought the influential of massively parallel AI and, with Craig Stanfill, the Theoretical Issues in Natural Language Processing memory-based reasoning approach to case-based conference to Urbana in 1978.