Previous work in phonologically and phonetically grounded language generation has mainly focused on domains such as puns and poetry. In this article, we present new work on the generation of tongue-twisters - a form of language that is required to be conditioned on a phoneme level to maximize sound overlap, whilst maintaining semantic consistency with an input topic and still being grammatically correct. We present TwisterLister, a pipeline for generating phonologically informed tongue-twisters from Large Language Models (LLMs) that we use to generate TwistList 2.0, the largest annotated dataset of tongue-twisters to date, consisting of 17K+ examples from a combination of human and LLM authors. Our generation pipeline involves the use of a phonologically constrained vocabulary alongside LLM prompting to generate novel, non-derivative tongue-twister examples. We additionally present the results of automatic and human evaluation of smaller models trained on our generated dataset to demonstrate the extent to which phonologically motivated language types can be generated without explicit injection of phonological knowledge. Additionally, we introduce a Phoneme-Aware Constrained Decoding module (PACD) that can be integrated into any causal language model and demonstrate that this method generates good quality tongue-twisters both with and without fine-tuning the underlying language model. We also design and implement a range of automatic metrics for the task of tongue-twister generation that is phonologically motivated and captures the unique essence of tongue-twisters based on Phonemic Edit Distance (PED).

The beverage industry is a typical food processing industry and accounts for significant energy consumption, e.g., 1 % of The grid stability and security of supply are challenged Danish energy consumption [10]. The beverage industry can due to the increasing penetration of renewable energy sources be further divided based on the beverage type, with beer in the electricity grid [1]. Furthermore, conventional balancing production being the category with the highest energy of the electricity grid through supply-side management is consumption accounting for 40 % of the beverages industry's becoming costly, and the capacity required to ensure the combined energy consumption [10]. For instance, Denmark security of supply would be inefficient [2]. Demand-side has the highest number of breweries per capita [11] among the management has seen increasing potential to mitigate the European nations. As of April 2022, there were 275 breweries impact of fluctuations in the electricity grid and aid in in Denmark. A survey based on the Danish Brewery stabilization by adjusting consumer demand subject to Associations members shows that approximately 50 % of electricity market conditions [3]. Danish beverage facilities might be permanently close or go Demand side management can be divided based on the bankrupt due to COVID-19 and the increasing energy prices load-shape objective, e.g., peak clipping, valley filling, and [12].

Dutch brewing company Heineken is one of the largest beer producers in the world with more than 70 production facilities globally. From small breweries to mega-plants, its logistics and production processes are increasingly complex and its machinery ever more advanced. The global beer giant therefore began looking for robotics solutions to make its breweries safer and more attractive for employees while enabling a more flexible organisation. The environment is constantly changing and the robot has to be able to respond immediately. Automatically adapting to the situation Dennis van der Plas, senior global lead packaging lines at Heineken, says, "We are becoming a high-tech company and attracting more and more technically trained staff. Repetitive tasks – like picking up fallen bottles from the conveyor belt will not provide them job satisfaction."

Anheuser-Busch thinks that the best games console is one that can also store a couple of cans of the cold stuff. The brewery is launching BL6, a gaming PC in the shape of a six-pack with a built-in projector and, naturally, a couple of koozies to keep your light beers cold. Never one to say no to a techy marketing stunt, it's the latest in a long series of gadgets and gizmos created by the beer brand. The brewery is putting its tongue far into its cheek with the BL6, a product it compares to some other next-generation consoles that came out recently. And while Microsoft and Sony's efforts can probably beat it spec-for-spec, neither rival machine comes with its own beer cooler, does it.

Are AI machines going to take over our brewpubs? Unlikely, but it is almost certain that breweries will continue to use AI and data to create new beer recipes and optimize existing formulations. Here are some ways AI is currently used in beer making.

In late 2017, AB InBev, the Belgian giant behind Budweiser and other beers, began adding a little artificial intelligence to its brewing recipe. Using data collected from a brewery in Newark, New Jersey, the company developed an AI algorithm to predict potential problems with the filtration process used to remove impurities from beer. Paul Silverman, who runs the New Jersey Beer Company, a small operation not far from the AB InBev brewery, says his team isn't even using computers, let alone AI. "We sit around tasting beer and thinking about what to make next," he says. The divide between the two breweries highlights the pace at which AI is being adopted by US companies. With so much hype around artificial intelligence, you might imagine that it's everywhere.

Ask any brewer and they'll admit that while beer has likely been around since the dawn of civilization, we're all still learning new ways to brew it more efficiently, creatively, and quickly. But balancing the brewer's art with modern approaches to automation, measurement, and decision making requires brewers to toe a fine line. Take the personality out of the process, and you sacrifice the "craft" in craft beer. Ignore the best tools available, and you waste precious resources that could be better spent on the creative side of the brewing equation. From their outpost on the eastern edge of the Cascades in Bend, Oregon, Deschutes Brewery has tackled this problem in a forward-thinking way, embracing their brew team's passion for tech and programming. Through their operational technology team, they're using a cutting-edge approach to brewing technology aimed at saving time and money, making higher-quality beer, and in turn freeing up company resources for an aggressive innovation program.

But while the industrial macrocosm, measured by various productivity indices, putters along, there are a growing number of success stories emerging from industrial companies embracing IIoT technologies in tandem with machine learning. The startup FogHorn, for instance, helped the Japanese industrial electronics company Daihen eliminate 1,800 hours' worth of manual data entry in a single factory. And a top beverage company saved the equivalent of 1 million cans of beer through predictive maintenance in one fell swoop. The firm installed machine monitoring technology from the firm Augury, which marries wireless vibration, ultrasonic, temperature and magnetic sensors with machine learning to detect machine problems for a range of industrial machines, including those used by breweries. "And we detected severe bearing wear on a filler -- the machine that fills cans with beer," said Saar Yoskovitz, co-founder and chief executive officer at Augury.

There are many ways artificial intelligence (AI) and machine learning can make our world more productive and effective. There are even breweries that are using AI to enhance beer production. Is this brilliant or unbelievable? While it's admittedly too soon to tell, using data to inform brewmasters' decisions and the possibility of personalised brews makes AI-brewed beer definitely intriguing. Since brewing beer is an art and a science, artificial intelligence offers a powerful helping hand in the latter.

There are many ways artificial intelligence (AI) and machine learning can make our world more productive and effective. There are even breweries that are using AI to enhance beer production. Is this brilliant or unbelievable? While it's admittedly too soon to tell, using data to inform brewmasters' decisions and the possibility of personalized brews makes AI-brewed beer definitely intriguing. Since brewing beer is an art and a science, artificial intelligence offers a powerful helping hand in the latter.