A common, yet regular, decision made by people, whether healthy or with any health condition, is to decide what to have in meals like breakfast, lunch, and dinner, consisting of a combination of foods for appetizer, main course, side dishes, desserts, and beverages. However, often this decision is seen as a trade-off between nutritious choices (e.g., low salt and sugar) or convenience (e.g., inexpensive, fast to prepare/obtain, taste better). In this preliminary work, we present a data-driven approach for the novel meal recommendation problem that can explore and balance choices for both considerations while also reasoning about a food's constituents and cooking process. Beyond the problem formulation, our contributions also include a goodness measure, a recipe conversion method from text to the recently introduced multimodal rich recipe representation (R3) format, and learning methods using contextual bandits that show promising results.

Decision-making is a fundamental capability in everyday life. Large Language Models (LLMs) provide multifaceted support in enhancing human decision-making processes. However, understanding the influencing factors of LLM-assisted decision-making is crucial for enabling individuals to utilize LLM-provided advantages and minimize associated risks in order to make more informed and better decisions. This study presents the results of a comprehensive literature analysis, providing a structural overview and detailed analysis of determinants impacting decision-making with LLM support. In particular, we explore the effects of technological aspects of LLMs, including transparency and prompt engineering, psychological factors such as emotions and decision-making styles, as well as decision-specific determinants such as task difficulty and accountability. In addition, the impact of the determinants on the decision-making process is illustrated via multiple application scenarios. Drawing from our analysis, we develop a dependency framework that systematizes possible interactions in terms of reciprocal interdependencies between these determinants. Our research reveals that, due to the multifaceted interactions with various determinants, factors such as trust in or reliance on LLMs, the user's mental model, and the characteristics of information processing are identified as significant aspects influencing LLM-assisted decision-making processes. Our findings can be seen as crucial for improving decision quality in human-AI collaboration, empowering both users and organizations, and designing more effective LLM interfaces. Additionally, our work provides a foundation for future empirical investigations on the determinants of decision-making assisted by LLMs.

Nala Robotics, the AI tech company fueling restaurant cooking automation, is now tackling one of the food industry's toughest and hardest jobs to fill with the introduction of Spotless by Nala, a robotic dishwasher that can easily be added to professional kitchens with minimal changes to existing layouts. Currently being deployed in restaurants, senior living centers and other commercial venues, Spotless uses high-performance camera systems and machine learning to provide a complete dishwashing solution, from scrubbing to storage. This highly intelligent robot will remove leftovers, rinse and clean cookware, cutlery, dishware and glassware, as well as dry, stack and store hundreds of varieties of utensils and kitchenware. "Our revolutionary patented dishwashing system allows operators to overcome staffing challenges and never miss a smudge," says Ajay Sunkara, CEO of Nala Robotics. "We've heard countless stories from managers and owners who had to pull double duty because the dish washer didn't show up for work. By installing our robot, they'll never have to worry about turnaround time and every dish will be spotless."

Smartphones and GPS have made paper maps virtually obsolete and put the power of navigation in our pockets. But now, engineers are working on a high-tech update for another directional tool that could revolutionize how we find our way around. The first street signs date back hundreds of years. They help you figure out where you are and where you're going. But what if they could be updated throughout the day, hour by hour to keep you informed about what's happening around you? "This is a fully-functioning street sign that allows you to essentially market, advertise and communicate out to the public," Michael Ottoman said, showing off a hi-tech version of the old street sign.

The Peggy Smedley Show is the most influential IoT (Internet of Things) podcasts engaging, educating, and entertaining listeners about relevant digital tech trends. Tune in to the live show Tuesday at 12 p.m. CT or listen to podcasts downloadable through iHeartRadio and iTunes. Peggy Smedley is joined by Josh Peschel, assistant professor of agriculture and Biosystems engineering, Iowa State University, who says there isn't a one-size-fits-all solution to all of the problems geographically--there are too many variables. Peggy kicks off a new month, looking at the topic of infrastructure. Peggy Smedley is joined by Juan Pablo Segura, cofounder, Babyscripts, who talks about the demand that is being fueled on the patient side in healthcare.

On the roster: The scariest stat you'll see all day -Trump tries outreach to Dems on DREAMers - Dems set demands on taxes - Flynn pushed plan that profited his client - 'You're my boy, Blue' THE SCARIEST STAT YOU'LL SEE ALL DAY When you consider the fact that a third of American adults cannot name a single branch of their federal government, you cease to wonder why things are so bad and begin to wonder why they are not already worse. In a poll conducted for the Annenberg Public Policy Center ahead of this weekend's celebration of the 229th anniversary of the ratification of the Constitution, only 26 percent of respondents could identify the executive, legislative and judicial branches, while 40 percent could name only one or two. Americans talk openly and often about the dumbing down of our culture, what we refer to as "The Big Stupid." It is a lament, but also something of a brag for people not clutched by ignorance of this magnitude. But it's easy to be an intellectual elite in a nation where not even half of the people know what kind of government they have.