The moment that tennis fans have been waiting for is almost finally here, with the Wimbledon Championships set to kick off next week. This year's tournament will see the likes of Petra Kvitova, Novak Djokovic and Carlos Alcaraz take to the grass. But in the near future, they could face stiff competition from an unlikely new contender - a robot. Scientists from Georgia Tech have developed a new robot named ESTHER (Experimental Sport Tennis Wheelchair Robot), which can zip around the court and even return human shots. The team believes the bot could serve as a training partner for professional players in the future, removing the psychological pressure of training against another human.

Conversational implicatures are pragmatic inferences that require listeners to deduce the intended meaning conveyed by a speaker from their explicit utterances. Although such inferential reasoning is fundamental to human communication, recent research indicates that large language models struggle to comprehend these implicatures as effectively as the average human. This paper demonstrates that by incorporating Grice's Four Maxims into the model through chain-of-thought prompting, we can significantly enhance its performance, surpassing even the average human performance on this task.

New AI systems such as ChatGPT, the overhauled Microsoft Bing search engine, and the reportedly soon-to-arrive GPT-4 have utterly captured the public imagination. ChatGPT is the fastest-growing online application, ever, and it's no wonder why. Type in some text, and instead of getting back web links, you get well-formed, conversational responses on whatever topic you selected--an undeniably seductive vision. But the public, and the tech giants, aren't the only ones who have become enthralled with the Big Data–driven technology known as the large language model. Bad actors have taken note of the technology as well. At the extreme end, there's Andrew Torba, the CEO of the far-right social network Gab, who said recently that his company is actively developing AI tools to "uphold a Christian worldview" and fight "the censorship tools of the Regime."

Athletics are a quintessential and universal expression of humanity. From French monks who in the 12th century invented jeu de paume, the precursor to modern lawn tennis, back to the K'iche' people who played the Maya Ballgame as a form of religious expression over three thousand years ago, humans have sought to train their minds and bodies to excel in sporting contests. Advances in robotics are opening up the possibility of robots in sports. Yet, key challenges remain, as most prior works in robotics for sports are limited to pristine sensing environments, do not require significant force generation, or are on miniaturized scales unsuited for joint human-robot play. In this paper, we propose the first open-source, autonomous robot for playing regulation wheelchair tennis. We demonstrate the performance of our full-stack system in executing ground strokes and evaluate each of the system's hardware and software components. The goal of this paper is to (1) inspire more research in human-scale robot athletics and (2) establish the first baseline for a reproducible wheelchair tennis robot for regulation singles play. Our paper contributes to the science of systems design and poses a set of key challenges for the robotics community to address in striving towards robots that can match human capabilities in sports.

Understanding of pragmatics is an essential and ubiquitous part of human communication. We show large language models (LLMs) mostly don't capture this aspect of language, hindering their applicability in the real world. Our analysis indicates where the largest room for improvement is to ultimately make this technology more useful. Recently, a large language model (LLM) called LaMDA beautifully passed (a variation of) the Turing test. In our most recent paper's title we state that LLMs are not zero-shot communicators.

In this post, we summarise the final three invited talks from the International Conference on Machine Learning (ICML). These presentations covered: how machine learning can complement randomised controlled trials, encoding and decoding speech, and molecular science. Esther's work centres on the use of randomised controlled trials (RCT) and she runs policy experiments with the aim of understanding which policies work and which don't. Her work is particularly focussed on reducing poverty. Work of this type involves many causal questions, for which there are often many competing ideas. Such is the field that there is no real guidance for theory; experiments are needed to determine successful policies.

Count to five, Noemi decides. If she's cracking up--if the terror of the past few minutes has scrambled her mind to the point where she's hallucinating--then this will all go away in a couple of seconds. If this is for real, the mech will be standing here waiting for orders when she's done. The mech remains still, expression curious and patient. Noemi takes a deep breath. She remains in her crouch, hand clutching her blaster so tightly her fingers have begun to cramp. The mech said its name was Abel. We were taught that there are twenty-five models of mech in the Mansfield Cybernetics line, alphabetical from B to Z. A was for a prototype. Abel's face and posture haven't shifted in the slightest. Would it stand here for an hour? At any rate, it hasn't made any move to get its weapon back. "My friend in the docking bay--she needs medical help, now." I'll bring her to sick bay." Abel takes off down the hallway so quickly that Noemi first thinks it's escaping--but it's apparently following her orders, just like it said it would. Shoving herself to her feet, Noemi runs after the mech, unwilling to let the thing out of her sight even though she knows she can't possibly keep up. From Darius Akide's lectures on mechs, Noemi knows the A model was an experimental model never put into mass production. Could the mech be lying about what it is? Its programming could potentially allow it to lie. But like everyone else on Genesis, she has memorized the faces of every single model of mech. According to her history books, they used to fear infiltration, in the early days of the Liberty War. What if the machines had walked among them, pretending to be human, spying on them all? While the Queens and Charlies are most familiar to her, Noemi could identify any of Mansfield's mechs on sight--and she's never seen this Abel's face before. Okay, you found a prototype. It doesn't matter how it got out here as long as you can use it. Take care of Esther and worry about the rest later. Panting, she stops in the doorway to stare at the scene in front of her. Abel leans over Esther's damaged fighter, gently scooping her into its arms. Esther's head lolls back as she murmurs, "Who--who are--" "It's a mech," Noemi calls as she ditches her nearly dead blaster, then holsters Abel's to her side. "The ship has a fully equipped sick bay.