David Gruber began his almost impossibly varied career studying bluestriped grunt fish off the coast of Belize. He was an undergraduate, and his job was to track the fish at night. He navigated by the stars and slept in a tent on the beach. "It was a dream," he recalled recently. "I didn't know what I was doing, but I was performing what I thought a marine biologist would do."

Semantic-aware communication is a novel paradigm that draws inspiration from human communication focusing on the delivery of the meaning of messages. It has attracted significant interest recently due to its potential to improve the efficiency and reliability of communication and enhance users' QoE. Most existing works focus on transmitting and delivering the explicit semantic meaning that can be directly identified from the source signal. This paper investigates the implicit semantic-aware communication in which the hidden information that cannot be directly observed from the source signal must be recognized and interpreted by the intended users. To this end, a novel implicit semantic-aware communication (iSAC) architecture is proposed for representing, communicating, and interpreting the implicit semantic meaning between source and destination users. A projection-based semantic encoder is proposed to convert the high-dimensional graphical representation of explicit semantics into a low-dimensional semantic constellation space for efficient physical channel transmission. To enable the destination user to learn and imitate the implicit semantic reasoning process of source user, a generative adversarial imitation learning-based solution, called G-RML, is proposed. Different from existing communication solutions, the source user in G-RML does not focus only on sending as much of the useful messages as possible; but, instead, it tries to guide the destination user to learn a reasoning mechanism to map any observed explicit semantics to the corresponding implicit semantics that are most relevant to the semantic meaning. Compared to the existing solutions, our proposed G-RML requires much less communication and computational resources and scales well to the scenarios involving the communication of rich semantic meanings consisting of a large number of concepts and relations.

One of the most common things that a genealogist is tasked with is the gathering of a person's initial family history, normally via in-person interviews or with the use of a platform such as ancestry.com, as this can provide a strong foundation upon which a genealogist may build. However, the ability to conduct these interviews can often be hindered by both geographical constraints and the technical proficiency of the interviewee, as the interviewee in these types of interviews is most often an elderly person with a lower than average level of technical proficiency. With this in mind, this study presents what we believe, based on prior research, to be the first chatbot geared entirely towards the gathering of family histories, and explores the viability of utilising such a chatbot by comparing the performance and usability of such a method with the aforementioned alternatives. With a chatbot-based approach, we show that, though the average time taken to conduct an interview may be longer than if the user had used ancestry.com or participated in an in-person interview, the number of mistakes made and the level of confusion from the user regarding the UI and process required is lower than the other two methods. Note that the final metric regarding the user's confusion is not applicable for the in-person interview sessions due to its lack of a UI. With refinement, we believe this use of a chatbot could be a valuable tool for genealogists, especially when dealing with interviewees who are based in other countries where it is not possible to conduct an in-person interview.

Welcome to our August 2023 monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, find out about recent events, and more. This month, we take a whistle-stop tour around some of the big conferences, popping in to IJCAI, AIES and ICML, find out about interdisciplinary methods in computational creativity, and say goodbye to a well-loved podcast. Nadia Ady and Faun Rice are working on a research project exploring where AI researchers find inspiration and ideas about human intelligence, and what approaches they use to translate ideas from the disciplines that study human intelligence (e.g. We spoke to Nadia and Faun about the project, what they've learnt so far, and how they plan to further develop the work. The 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023) took place in Macao from 19-25 August 2023. The programme included plenary talks, workshops, symposia and tutorials.

Many engineering organizations are reimplementing and extending deep neural networks from the research community. We describe this process as deep learning model reengineering. Deep learning model reengineering - reusing, reproducing, adapting, and enhancing state-of-the-art deep learning approaches - is challenging for reasons including under-documented reference models, changing requirements, and the cost of implementation and testing. In addition, individual engineers may lack expertise in software engineering, yet teams must apply knowledge of software engineering and deep learning to succeed. Prior work has examined on DL systems from a "product" view, examining defects from projects regardless of the engineers' purpose. Our study is focused on reengineering activities from a "process" view, and focuses on engineers specifically engaged in the reengineering process. Our goal is to understand the characteristics and challenges of deep learning model reengineering. We conducted a case study of this phenomenon, focusing on the context of computer vision. Our results draw from two data sources: defects reported in open-source reeengineering projects, and interviews conducted with open-source project contributors and the leaders of a reengineering team. Our results describe how deep learning-based computer vision techniques are reengineered, analyze the distribution of defects in this process, and discuss challenges and practices. Integrating our quantitative and qualitative data, we proposed a novel reengineering workflow. Our findings inform several future directions, including: measuring additional unknown aspects of model reengineering; standardizing engineering practices to facilitate reengineering; and developing tools to support model reengineering and model reuse.

Esther Jo Bethard loved playing with her siblings and going to the zoo. She died at 10 months of age after accidentally swallowing a water bead. HEARTBREAKING LOSS – Mom from Wisconsin calls for change after her 10-month-old daughter dies from swallowing a water bead. 'WATCH FOR INACCURACIES' – Here's how parents and teachers can ensure an ethical use of AI by kids during this back-to-school season. AVIATION TRAILBLAZER – Amelia Earhart becomes first woman to fly solo coast-to-coast on this day in history, 1932.

CyberGuy shows you how to save money with these apps. Welcome to the world of "Text With Jesus," where you're just a tap away from a conversation with the holy – and, for a price, the not-so-holy. CLICK TO GET KURT'S FREE CYBERGUY NEWSLETTER WITH SECURITY ALERTS, QUICK TIPS, TECH REVIEWS AND EASY HOW-TO'S TO MAKE YOU SMARTER For those longing for a more personal connection to their faith, this app might be the digital salvation they're seeking. Designed with devoted Christians in mind, "Text With Jesus" promises interaction with figures like Jesus, Mary, Joseph, Peter and Matthew. This app wears its spirituality on its screen, guiding you through its queries with responses mined from the depths of the Bible's rich text.

The IJCAI distinguished paper awards recognise some of the best papers presented at the conference each year. This year, three articles were named as distinguished papers. Abstract: Levin Tree Search (LTS) is a search algorithm that makes use of a policy (a probability distribution over actions) and comes with a theoretical guarantee on the number of expansions before reaching a goal node, depending on the quality of the policy. This guarantee can be used as a loss function, which we call the LTS loss, to optimize neural networks representing the policy (LTS NN). In this work we show that the neural network can be substituted with parameterized context models originating from the online compression literature (LTS CM). We show that the LTS loss is convex under this new model, which allows for using standard convex optimization tools, and obtain convergence guarantees to the optimal parameters in an online setting for a given set of solution trajectories -- guarantees that cannot be provided for neural networks.

AI technology is quickly creeping into every industry, prompting new questions about whether online content comes from a human or a computer. The presence of advanced technology in the classroom may require conversations with students during this new school year. As artificial intelligence finds its way into more families' day-to-day routines, parents and teachers alike should be wary of how their kids are interacting with generative AI. This is according to SmartNews' head of trust and safety Arjun Narayan, who shared concerns during an interview with Fox News Digital. "As with any new technology, when it is very new, it's important to understand how you're engaging with that tech," said Narayan, who is based in Japan.

Former Chicago 911 dispatcher Keith Thornton Jr. joined "Fox & Friends First" to discuss how the crime surge is affecting law enforcement and communities nationwide. Understaffed 911 call centers across the country field non-emergency calls about stray animals or noise complaints on top of their workload of answering serious reports of medical emergencies, crimes and even death. Officials in Charleston County, South Carolina, however, are now leveraging artificial intelligence to streamline non-emergency calls in an effort to free up 911 operators to focus on getting first responders to the scene of emergency incidents as quickly as possible. "Our job is to serve the public the best way we can. So, I am not in any way demeaning anyone from the public, but someone who has their favorite cat stuck in a tree, that's an emergency for them as compared to someone's just been shot," Jim Lake, director of the Charleston County Consolidated Emergency Communications Center, told Fox News Digital in a recent phone interview.