Ground robots navigating in complex, dynamic environments must compute collision-free trajectories to avoid obstacles safely and efficiently. Nonconvex optimization is a popular method to compute a trajectory in real-time. However, these methods often converge to locally optimal solutions and frequently switch between different local minima, leading to inefficient and unsafe robot motion. In this work, We propose a novel topology-driven trajectory optimization strategy for dynamic environments that plans multiple distinct evasive trajectories to enhance the robot's behavior and efficiency. A global planner iteratively generates trajectories in distinct homotopy classes. These trajectories are then optimized by local planners working in parallel. While each planner shares the same navigation objectives, they are locally constrained to a specific homotopy class, meaning each local planner attempts a different evasive maneuver. The robot then executes the feasible trajectory with the lowest cost in a receding horizon manner. We demonstrate, on a mobile robot navigating among pedestrians, that our approach leads to faster and safer trajectories than existing planners.

When deploying machine learning algorithms in the real world, guaranteeing safety is an essential asset. Existing safe learning approaches typically consider continuous variables, i.e., regression tasks. However, in practice, robotic systems are also subject to discrete, external environmental changes, e.g., having to carry objects of certain weights or operating on frozen, wet, or dry surfaces. Such influences can be modeled as discrete context variables. In the existing literature, such contexts are, if considered, mostly assumed to be known. In this work, we drop this assumption and show how we can perform safe learning when we cannot directly measure the context variables. To achieve this, we derive frequentist guarantees for multi-class classification, allowing us to estimate the current context from measurements. Further, we propose an approach for identifying contexts through experiments. We discuss under which conditions we can retain theoretical guarantees and demonstrate the applicability of our algorithm on a Furuta pendulum with camera measurements of different weights that serve as contexts.

Over the past few months, many have attempted to translate the uncanniness of Gov. Ron DeSantis' smile into words. After the Republican debates, it's been called "painfully weird" and said to look "like it's on his face upside down." It resembles "a Disney World animatronic" or "an A.I. trying to learn human emotions." It even inspired The Daily Show to put out a public service announcement about "Frownington's Disease," a made-up condition that causes a person's smile to resemble a wince one would make upon "sitting on his own testicles." As nice as it is that one expression has inspired such rich verbiage and creativity--Ron DeSantis, unlikely muse!--you might find yourself longing for a more technical explanation.

How to Do It is Slate's sex advice column. Send it to Stoya and Rich here. As a sexually dominant-leaning female, I get a lot of instant gratification out of gorgeous women online telling me my assertiveness is impressive and sexy. When I have sex with women in my dreams, it's perfect. While my "traditional" long-term relationships have been with male-presenting people, I slept with several women in my early 20s--though I struggled to find satisfying connections.

This article was featured in the One Story to Read Today newsletter. Every day or two for the past seven months, I've received a "personalized" email containing a bunch of recent, user-generated questions from the website Quora. "I caught my son playing his Xbox at 12:00 in the morning on a school night. As a result, I broke his console and now he won't talk to me. How can I tell him that it is his fault?"

Violet Crown City Church Pastor Jay Cooper said that using AI to conduct a service at his church did not capture the essential elements required for Christian worship. A prominent Black megachurch in New York City is being accused of discriminating against a woman who lost her bid to become its senior pastor. Yale Divinity School Professor Eboni Marshall Turman filed a lawsuit against Abyssinian Baptist Church alleging she was rejected from the final round of candidates applying to lead the church after the death of Rev. Calvin O. Butts III in 2022. Marshall Turman previously served as the late reverend's assistant and was the church's youngest female Assistant Minister from 2002-2012. In her Dec. 29 lawsuit, she accuses the church and search committee chair Valerie S. Grant of acting inappropriately by "pressing issues not broached with [Marshall Turman's] male counterparts" during the interview process, the Associated Press reported.

Artificial Intelligence is now recognized as a general-purpose technology with ample impact on human life. This work aims at understanding the evolution of AI and, in particular Machine learning, from the perspective of researchers' contributions to the field. In order to do so, we present several measures allowing the analyses of AI and machine learning researchers' impact, influence, and leadership over the last decades. This work also contributes, to a certain extent, to shed new light on the history and evolution of AI by exploring the dynamics involved in the field's evolution by looking at papers published at the flagship AI and machine learning conferences since the first International Joint Conference on Artificial Intelligence (IJCAI) held in 1969. AI development and evolution have led to increasing research output, reflected in the number of articles published over the last sixty years. We construct comprehensive citation collaboration and paper-author datasets and compute corresponding centrality measures to carry out our analyses. These analyses allow a better understanding of how AI has reached its current state of affairs in research. Throughout the process, we correlate these datasets with the work of the ACM Turing Award winners and the so-called two AI winters the field has gone through. We also look at self-citation trends and new authors' behaviors. Finally, we present a novel way to infer the country of affiliation of a paper from its organization. Therefore, this work provides a deep analysis of Artificial Intelligence history from information gathered and analysed from large technical venues datasets and suggests novel insights that can contribute to understanding and measuring AI's evolution.

Kara Frederick, tech director at the Heritage Foundation, discusses the need for regulations on artificial intelligence as lawmakers and tech titans discuss the potential risks. A Nobel Prize-winning economist is sounding the alarm about the future of science, technology, engineering and mathematics (STEM) careers amid the rapid development of artificial intelligence, arguing that many of the currently in-demand jobs could soon be obsolete. "The skills that are needed now -- to collect the data, collate it, develop it and use it to develop the next phase of AI, or more to the point, make AI more applicable for jobs -- will make the skills that are needed now obsolete because it will be doing the job," said Christopher Pissarides, a professor of economics at the London School of Economics, in a recent interview, according to a report from Time. "Despite the fact that you see growth, they're still not as numerous as might be required to have jobs for all those graduates coming out with STEM because that's what they want to do." The comments come as 2023 became a breakthrough year for AI technology, which has rapidly developed and gained increased mainstream applications.

Large language models (LLMs) such as ChatGPT and Google Bard have garnered significant attention in the academic community. Previous research has evaluated these LLMs for various applications such as generating programming exercises and solutions. However, these evaluations have predominantly been conducted by instructors and researchers, not considering the actual usage of LLMs by students. This study adopts a student-first approach to comprehensively understand how undergraduate computer science students utilize ChatGPT, a popular LLM, released by OpenAI. We employ a combination of student surveys and interviews to obtain valuable insights into the benefits, challenges, and suggested improvements related to ChatGPT. Our findings suggest that a majority of students (over 57%) have a convincingly positive outlook towards adopting ChatGPT as an aid in coursework-related tasks. However, our research also highlights various challenges that must be resolved for long-term acceptance of ChatGPT amongst students. The findings from this investigation have broader implications and may be applicable to other LLMs and their role in computing education.

A general strike has been called across the cities of the occupied West Bank in protest against the assassination of seven members of Hamas, including the deputy head of its political bureau, Saleh al-Arouri. The strike was called by Palestinian armed groups that asked people to stay home on Wednesday and only leave to march in demonstrations against the drone attack on the outskirts of Beirut. The slain men are Saleh al-Arouri, who was also the commander of the Qassam Brigades in the occupied West Bank; Samir Fendi, who commanded the Qassam Brigades in Lebanon; Azzam al-Aqraa, who commanded the Qassam Brigades in southern Lebanon; and members Mahmoud Shaheen, Mohammed al-Rayes, Mohammed Bashasha and Ahmed Hamoud. All seven will be buried in Lebanon. Funerals will be held for Hamoud and Shaheen on Wednesday in the Burj al-Barajneh camp for Palestinian refugees and Taalbaya, respectively.