PongBot is an artificial intelligence-powered tennis robot. American tennis player Danielle Collins had some choice words for the cameraman during her Internationaux de Strasbourg match against Emma Raducanu on Wednesday afternoon. Collins was in the middle of a changeover when she felt the cameraman's hovering was a bit too close for comfort in the middle of the third and defining set. She got off the bench and made the point clear. Danielle Collins celebrates during her match against Madison Keys in the third round of the women's singles at the 2025 Australian Open at Melbourne Park in Melbourne, Australia, on Jan. 18, 2025.

The vision-guided system changes the cartoning game with the integration of JLS TRAK and handles a variety of packaging with on-the-fly changeover. The high-speed, flexible Peregrine utilizes a proprietary positive carton transport (PCT) system to retain full control of the carton from forming through loading, without ever letting go.PACK EXPO Connects – November 9-13. Now more than ever, packaging and processing professionals need solutions for a rapidly changing world, and the power of the PACK EXPO brand delivers the decision makers you need to reach. Attendee registration is open now. The flexible carton loading system minimizes changeover while meeting production needs for small batches.

In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Tony has worked in the same automotive plant in north-west Ohio, US, for nearly two decades. During that time, he moved from a part-time line associate on the third shift to a line supervisor, where he now oversees 35 general assembly workers. Occasionally, one of his workers will come to him with an article about a nearby Indiana plant that plans full automation, and ask Tony if robots will take their jobs as well. Fortunately, Tony knows the numbers. The International Federation of Robotics projects 250,000 industrial robots will be deployed globally every year.

The world's largest robot has been unveiled and it is a completely autonomous railway system. AutoHaul has been developed by a mining firm and is being used to transport iron ore from mines to shipping ports 500 miles away (800 km) in Western Australia. This journey can be completed in just 40 hours, including the loading and dumping of the ferrous cargo. Its deployment is the end result of a project which has so far cost $940 million (£740 million). Rio Tinto, the corporation that built the infrastructure and hardware for the locomotive, says this could be the first step in transforming the firm's 1,000-mile (1,700-kilometre) network connecting 16 iron ore mines and two ports.

The Australian wine industry is turning to artificial intelligence to streamline its manufacturing. South Australian tech firm Ailytic has developed an artificial intelligence (AI) program to significantly increase production efficiency by optimising machine use. It uses an AI technique called'prescriptive analytics' to account for all the variables that go into mass-producing wines such temperature, wine changeover and inventory. The program then creates the best possible operation schedule, allowing companies to save considerable time and money. Ailytic's list of clients includes world-renown wine companies such as Pernod Ricard, Accolade Wines and Treasury Wine Estates.