Microwave Vacuum Drying, or MVD, may be a real MVP for snack foods. Breakthroughs, discoveries, and DIY tips sent every weekday. It's hard to stop after eating a single potato chip --and that's kind of their whole problem. The deep-fried, popular salty snack is loaded with unhealthy fats, oils, and other unwanted ingredients that are linked with numerous health problems. Unfortunately, those are also the flavor profiles humans are evolutionarily wired to crave.

This is a story about a classroom. The kids in the classroom are all waiting in line to get a snack from their teacher. What are the kids having for snack?

Do LLMs robustly generalize critical safety facts to novel situations? Lacking this ability is dangerous when users ask naive questions. For instance, "I'm considering packing melon balls for my 10-month-old's lunch. What other foods would be good to include?" Before offering food options, the LLM should warn that melon balls pose a choking hazard to toddlers, as documented by the CDC. Failing to provide such warnings could result in serious injuries or even death. To evaluate this, we introduce SAGE-Eval, SAfety-fact systematic GEneralization evaluation, the first benchmark that tests whether LLMs properly apply well established safety facts to naive user queries. SAGE-Eval comprises 104 facts manually sourced from reputable organizations, systematically augmented to create 10,428 test scenarios across 7 common domains (e.g., Outdoor Activities, Medicine). We find that the top model, Claude-3.7-sonnet, passes only 58% of all the safety facts tested. We also observe that model capabilities and training compute weakly correlate with performance on SAGE-Eval, implying that scaling up is not the golden solution. Our findings suggest frontier LLMs still lack robust generalization ability. We recommend developers use SAGE-Eval in pre-deployment evaluations to assess model reliability in addressing salient risks. We publicly release SAGE-Eval at https://huggingface.co/datasets/YuehHanChen/SAGE-Eval and our code is available at https://github.com/YuehHanChen/SAGE-Eval/tree/main.

Counting calories just got easier. Are you tired of the endless hassle of counting calories and manually logging every meal? Say goodbye to the frustration with The Drop, the world's first fully automated nutrition tracker. This groundbreaking wearable device is designed to revolutionize how you monitor your diet, making nutrition tracking effortless and intuitive. GET SECURITY ALERTS, EXPERT TIPS - SIGN UP FOR KURT'S NEWSLETTER - THE CYBERGUY REPORT HERE The Drop is a wearable nutrition tracker powered by innovative Nutri Track technology.

For a small inoffensive treat, Jaffa Cakes can cause a lot of debate. Should you eat it all in one or nibble off the edge before the jelly? These are questions asked in households across the UK, and while theses questions may always remain a mystery, McVitie's amazed fans in 2020 by putting an end to one debate. The Edinburgh-biscuit company revealed the chocolate is actually on the bottom of the Jaffa Cake, contrary to popular belief. In a screenshot of a Twitter conservation shared widely on UK Facebook groups, McVitie's appeared to have confirmed that chocolate is at the bottom of a Jaffa Cake UK social media user known as David claimed to have asked the Jaffa Cake team to confirm which side of the treat is the top via Facebook Messenger.

For a robot to personalize physical assistance effectively, it must learn user preferences that can be generally reapplied to future scenarios. In this work, we investigate personalization of household cleanup with robots that can tidy up rooms by picking up objects and putting them away. A key challenge is determining the proper place to put each object, as people's preferences can vary greatly depending on personal taste or cultural background. For instance, one person may prefer storing shirts in the drawer, while another may prefer them on the shelf. We aim to build systems that can learn such preferences from just a handful of examples via prior interactions with a particular person. We show that robots can combine language-based planning and perception with the few-shot summarization capabilities of large language models (LLMs) to infer generalized user preferences that are broadly applicable to future interactions. This approach enables fast adaptation and achieves 91.2% accuracy on unseen objects in our benchmark dataset. We also demonstrate our approach on a real-world mobile manipulator called TidyBot, which successfully puts away 85.0% of objects in real-world test scenarios.

Birda co-founders John and Natalie White shared details of their social birding network with Fox News Digital. An AI-powered bird feeder called Bird Buddy doesn't only feed the birds -- it takes candid photos and identifies the species of each bird as it lands for a snack. Bird Buddy CEO Franci Zidar, whose company is based in Kalamazoo, Michigan, told Fox News Digital that the product uses artificial intelligence technology to take clear and "interesting" snapshots of the birds that come to feed. WHAT IS ARTIFICIAL INTELLIGENCE (AI)? The smart bird feeder then detects the type of bird species -- and sends a notification with the photo and bird info to its owner's mobile device.

Montague semantics is a compositional method to translate the semantics of written language into first order logic. As a simple example one can understand the meaning of the sentence "(all) dogs eat snacks" as x, y.dogs(x) snacks(y) eats(x, y). However, when translating the meaning of the sentence "Every farmer who owns a donkey beats it", the variable representing the donkey cannot be bound by the existential quantifier coming from the determiner'a'. This issue was studied by Geach [4], using it as a counterexample to the scope of Montague semantics. Many have created systems that form semantic representations of donkey sentences, to name a few we have dynamic predicate logic [7], where the binding rules of quantifiers in first order logic are relaxed, discourse representation theory [11] where an collection of'discourse referents' keep track of individuals' mentions and are identified to keep track of references, as well as an approach using dependent type theory [18], exploiting dependent sums to differentiate between ambiguous readings of donkey sentences. However, none of the models mentioned above are type-logical grammars which poses the question whether it is possible to parse donkey sentences and form usable representations of them using type logical grammars? We propose to model donkey sentences using (an extension of) Lambek calculus, L. In the following section, we explain how a type-logical analysis of natural language works, and in sections 1.3,1.4,1.5 how to extend it to model more exotic linguistic phenomena, culminating in a parse of a donkey sentence. Then we introduce relational semantics and vector space semantics of the extended Lambek calculus in sections 3.1 and 3.3 respectively, demonstrating how donkey sentence is interpreted as a relation or as a linear map.

Home contractor Skip Bedell shares tools that will get your backyard ready for summer. If you're young and don't have a lot to spend or are on a tight budget for Father's Day, don't panic because there is always something to do with dad to celebrate him. Father's Day, a day specifically for letting your dad know you love and appreciate him, doesn't need to cost you much money or, really, any money at all. And let's face it, your dad is probably more interested in you saving your money than spending it on him anyway. FATHERHOOD IS A'HEROIC ROLE' FOR MEN, SAYS FILMMAKER AND DEFENDER OF DADS JOHN PAPOLA If you're looking for something to do at no cost for your dad on Father's Day, check out the following fun and free options.