This paper puts forward the concept that learning to take safe actions in unknown environments, even with probability one guarantees, can be achieved without the need for an unbounded number of exploratory trials. This is indeed possible, provided that one is willing to navigate trade-offs between optimality, level of exposure to unsafe events, and the maximum detection time of unsafe actions. We illustrate this concept in two complementary settings. We first focus on the canonical multi-armed bandit problem and study the intrinsic trade-offs of learning safety in the presence of uncertainty. Under mild assumptions on sufficient exploration, we provide an algorithm that provably detects all unsafe machines in an (expected) finite number of rounds. The analysis also unveils a trade-off between the number of rounds needed to secure the environment and the probability of discarding safe machines. We then consider the problem of finding optimal policies for a Markov Decision Process (MDP) with almost sure constraints. We show that the action-value function satisfies a barrier-based decomposition which allows for the identification of feasible policies independently of the reward process. Using this decomposition, we develop a Barrier-learning algorithm, that identifies such unsafe state-action pairs in a finite expected number of steps. Our analysis further highlights a trade-off between the time lag for the underlying MDP necessary to detect unsafe actions, and the level of exposure to unsafe events. Simulations corroborate our theoretical findings, further illustrating the aforementioned trade-offs, and suggesting that safety constraints can speed up the learning process.

Conversational AI is constantly evolving with extensive research leading to new language models due to the ever-increasing adoption of this technology within companies. We caught up with experts from Peakon, A Workday Company, Vodafone and Admiral group Plc to find out more about what they predict the conversational AI trends will be in 2023. It is difficult to zero in on a single trend as there are multiple lines of thoughts around the current state of conversational AI technology that are quite relevant given the adoption rate of the technology today and the media frenzy around this topic. Want to learn more about the top Conversational AI trends this year? All of these experts will be presenting at the Conversational AI Summit on 16-17 May in London! The summit will host a number of deep dive sessions with interactive sessions, and allow for networking opportunities with like-minded individuals.

The AAAI 2023 best paper awards were presented at the conference on Saturday 11 February. The awards comprised one outstanding paper, one outstanding student paper, and 12 distinguished papers. The AAAI outstanding paper award is given to a paper (or papers) that "exemplifies the highest standards in technical contribution and exposition". Abstract: The aim of Inverse Reinforcement Learning (IRL) is to infer a reward function R from a policy pi. To do this, we need a model of how pi relates to R. In the current literature, the most common models are optimality, Boltzmann rationality, and causal entropy maximisation.

Feeld Notes is a column about a middle-aged woman who suddenly realizes she wants to have sex again--and the beguiling app she uses to do it. Not to imply I get liked by a lot of men--ha!--but of the men who do like my profile, a significant percentage of them are substantially younger than I am. Listen, I'm not a cougar, an appellation that, by definition, suggests a certain predatory instinct. As I've explained previously, I don't have it in me. But I'd be lying if I said that that some part of me isn't delighted to think that the pictures and the words on my profile project a sort of youthful exuberance.

It's great to see you on a Saturday. As you've likely seen, artificial intelligence has been the talk of the town. Nothing's been hotter than ChatGPT -- the bot's garnered 1 billion cumulative web hits since November, and users have used it to write articles, emails, and even dating-app messages. I caught up with Shark Tank star Kevin O'Leary to get his thoughts on the burgeoning tech trend and how he plans to play the market in 2023. If this was forwarded to you, sign up here. Kevin O'Leary is the chairman of O'Leary Ventures, a media personality, and veteran investor.

Two years ago, Microsoft president Brad Smith told a US congressional hearing that tech companies like his own had not been sufficiently paying media companies for the news content that helps fuel search engines like Bing and Google. "What we're talking about here is far bigger than us," he said, testifying alongside news executives. "Let's hope that, if a century from now people are not using iPhones or laptops or anything that we have today, journalism itself is still alive and well. Because our democracy depends on it." Smith said tech companies should do more and that Microsoft was committed to continuing "healthy revenue-sharing" with news publishers, including licensing articles for Microsoft news apps.

Data scientist Sahar Nasiri originally went to college to study industrial engineering. After taking Andrew Ng's Machine Learning course on a professor's recommendation, however, she knew she wanted her future to be in AI. Now she uses AI to help Delta Airlines keep its planes in top operating condition. She spoke with us about her early interview struggles, how she landed her first job, and the value of truly understanding statistics. Can you tell me about your current role? When did you start, what is your title, and what are your primary responsibilities?

AI can be unsettling for most people. Off the top of their head, many people think about robots taking over the human population or self-destructive devices. When coupled with construction, an industry that is notable for being slow to embrace technology; then you have reached a standstill as said industry is reluctant to change. On one corner is AI; a bit of an unknown element but one that is also dynamic and capable of many things. On the other, there is the construction sector; a dwindling industry frequently faced with challenges that threaten workers' safety, productivity, and resources.

Launched in November 2022, ChatGPT is a chatbot that can not only engage in human-like conversation, but also provide accurate answers to questions in a wide range of knowledge domains. The chatbot, created by the firm OpenAI, is based on a family of "large language models" -- algorithms that can recognize, predict, and generate text based on patterns they identify in datasets containing hundreds of millions of words. In a study appearing in PLOS Digital Health this week, researchers report that ChatGPT performed at or near the passing threshold of the U.S. Medical Licensing Exam (USMLE) -- a comprehensive, three-part exam that doctors must pass before practicing medicine in the United States. In an editorial accompanying the paper, Leo Anthony Celi, a principal research scientist at MIT's Institute for Medical Engineering and Science, a practicing physician at Beth Israel Deaconess Medical Center, and an associate professor at Harvard Medical School, and his co-authors argue that ChatGPT's success on this exam should be a wake-up call for the medical community. Q: What do you think the success of ChatGPT on the USMLE reveals about the nature of the medical education and evaluation of students?

A number of prestigious awards were announced shortly before the start of AAAI 2023, and will be officially presented during the conference. Some of the winners will also be giving invited talks as part of the programme. The AAAI Award for Artificial Intelligence for the Benefit of Humanity recognises the positive impacts of artificial intelligence to protect, enhance, and improve human life in meaningful ways with long-lived effects. The winner of this year's award is Tuomas Sandholm (Carnegie Mellon University). Tuomas has been recognised for "outstanding scientific and software contributions to the design and implementation of organ exchanges, and their direct impact on both practice and policy".