Operating home appliances, among the most common tools in every household, is a critical capability for assistive home robots. This paper presents ApBot, a robot system that operates novel household appliances by "reading" their user manuals. ApBot faces multiple challenges: (i) infer goal-conditioned partial policies from their unstructured, textual descriptions in a user manual document, (ii) ground the policies to the appliance in the physical world, and (iii) execute the policies reliably over potentially many steps, despite compounding errors. To tackle these challenges, ApBot constructs a structured, symbolic model of an appliance from its manual, with the help of a large vision-language model (VLM). It grounds the symbolic actions visually to control panel elements. Finally, ApBot closes the loop by updating the model based on visual feedback. Our experiments show that across a wide range of simulated and real-world appliances, ApBot achieves consistent and statistically significant improvements in task success rate, compared with state-of-the-art large VLMs used directly as control policies. These results suggest that a structured internal representations plays an important role in robust robot operation of home appliances, especially, complex ones.

The pattern formation task is commonly seen in a multi-robot system. In this paper, we study the problem of forming complex shapes with functionally limited mobile robots, which have to rely on other robots to precisely locate themselves. The goal is to decide whether a given shape can be filled by a given set of robots; in case the answer is yes, to complete a shape formation process as fast as possible with a minimum amount of communication. Traditional approaches either require global coordinates for each robot or are prone to failure when attempting to form complex shapes beyond the capability of given approaches - the latter calls for a decision procedure that can tell whether a target shape can be formed before the actual shape-forming process starts. In this paper, we develop a method that does not require global coordinate information during the execution process and can effectively decide whether it is feasible to form the desired shape. The latter is achieved via a planning procedure that is capable of handling a variety of complex shapes, in particular, those with holes, and assigning a simple piece of scheduling information to each robot, facilitating subsequent distributed execution, which does not rely on the coordinates of all robots but only those of neighboring ones. The effectiveness of our shape-forming approach is vividly illustrated in several simulation case studies.

Today it is trivially easy to play games on a computer, games console or phone with your friends over the internet. But before the wide availability of high-speed internet, things were more complicated. In the 1990s and early 2000s, 3D graphics in video games were becoming more and more complex, but the low network speeds of the period meant that these games, unlike slower-paced and less graphically intensive strategy games, were nearly unplayable over an internet connection. In this moment, in which communications technology was being outpaced by graphical power, the Lan (local area network) party was born. The term itself conjures up strong sensory memories for those who were there – sweaty bodies packed into a basement or convention hall, a dozen hefty computer monitors being manoeuvred into position. For those on the outside, these were scenes of incomprehension or ridicule.

Translation Quality Evaluation (TQE) is an essential step of the modern translation production process. TQE is critical in assessing both machine translation (MT) and human translation (HT) quality without reference translations. The ability to evaluate or even simply estimate the quality of translation automatically may open significant efficiency gains through process optimisation. This work examines whether the state-of-the-art large language models (LLMs) can be used for this purpose. We take OpenAI models as the best state-of-the-art technology and approach TQE as a binary classification task. On eight language pairs including English to Italian, German, French, Japanese, Dutch, Portuguese, Turkish, and Chinese, our experimental results show that fine-tuned gpt3.5 can demonstrate good performance on translation quality prediction tasks, i.e. whether the translation needs to be edited. Another finding is that simply increasing the sizes of LLMs does not lead to apparent better performances on this task by comparing the performance of three different versions of OpenAI models: curie, davinci, and gpt3.5 with 13B, 175B, and 175B parameters, respectively.

Clockwise is a tech startup that provides an online app to help employees build the most optimal daily schedules by leveraging artificial intelligence (AI) technology. The company recently closed on a Series C funding round to further expand its customer base and grow the business. Clockwise works directly with its users to generate schedules that create time for important meetings and other responsibilities. Additionally, it optimizes the day to fit within a user's preferred work style. So, for users who find they are most productive in the morning, the startup's AI software front-loads their uninterrupted focus time and leaves meetings and group tasks for later in the day.

In a world that remains anything but normal, gaming has become a source of companionship and catharsis. The game industry has struggled to keep up as major releases like Horizon Forbidden West and God of War Ragnarök have once again been delayed by the pandemic. But you'd be hard pressed to find a year with more breadth. Over 11 thousand unique titles were released to the online marketplace Steam, thousands more than any other year. Consoles like the Xbox Series X, PS5, and Nintendo Switch each deepened their catalogs with new franchises and remasters of old classics, and independent games enjoyed heightened visibility at The Game Awards and on platforms like YouTube and Twitch.

The Minimax algorithm, also known as MinMax, is a popular algorithm for calculating the best possible move a player can player in a zero-sume game, like Tic-Tac-Toe or Chess. It makes use of an evaluation-function provided by the developer to analyze a given game board. During the execution Minimax builds a game tree that might become quite large. This causes a very long runtime for the algorithm. In this article I'd like to introduce 10 methods to improve the performance of the Minimax algorithm and to optimize its runtime.

An artist has transformed the chipped stone busts of ancient Roman emperors into photorealistic portraits with the help of historical artefacts and creative software. Daniel Voshart, from Toronto, Canada, says that his project of painstakingly colourising and shaping the faces of 54 Principate rulers was'a quarantine project that got a bit out of hand', but it has attracted attention from hobbyists to historians. And he has now released his completed work in a series of stunning portraits and posters that cover 300 years of Roman history. Though more interested in design work for VR for use in architecture and the film industry, the coronavirus pandemic brought Daniel's work to stop and left him with time to explore his hobby of colourising statues. When he came to pick a subject however, he chose to research the busts of Roman Emperors who controlled its sprawling empire during the first three-century-long Principate, despite not being particularly interested in ancient history.

I am honestly not sure whether fish have any concept of bees. I am equally unsure whether bees have any concept of fish. I am even more unsure whether bees and fish could be friends, if they knew that the other existed. But thanks to robots, it turns out that the answer is definitely yes. The video really doesn't communicate a whole lot about what's going on here, but the central question is whether robots can usefully mediate communications between groups of very different animals in such a way that long distance interspecies collective behavior becomes possible. The answer appears to be yes, which isn't a total surprise: We've known for a while that robots can communicate with both bees and zebra fish, in the sense that the actions of a robot that mimics the behavior of an animal can, in turn, predictably and interactively alter the animals' behavior.

Clockwise, from top left: Nintendo; Lenovo; Build-A-Bear's Pokémon collection; "Beasts of Balance" Clockwise, from top left: Nintendo; Lenovo; Build-A-Bear's Pokémon collection; "Beasts of Balance" (Nintendo; Lenovo; Build-A-Bear; Beasts of Balance) Though this itty-bitty retro gaming console may be relatively hard to find, it's worth the hunt, as it represents some of Nintendo's best work. "Super Mario World" expanded the universe for our favorite plumber, and games like "Earthbound" brought serious topics to the home console. Scott Pilgrim's "Precious Little Card Game" pits you -- and up to three of your friends -- against one of the dreaded evil exes from Bryan Lee O'Malley's "Scott Pilgrim" series. But don't worry -- damage will be dealt, but no hearts will be broken. "Super Mario Odyssey," Mario's first-adventure for the Nintendo Switch, looks to be one of the oddest in the series yet -- and remember, this is a game with walking mushrooms.