Control algorithms in production environments typically require domain experts to tune their parameters and logic for specific scenarios. However, existing research predominantly focuses on algorithmic performance under ideal or default configurations, overlooking the critical aspect of Tuning Potential. To bridge this gap, we introduce Crucible, an agent that employs an LLM-driven, multi-level expert simulation to turn algorithms and defines a formalized metric to quantitatively evaluate their Tuning Potential. We demonstrate Crucible's effectiveness across a wide spectrum of case studies, from classic control tasks to complex computer systems, and validate its findings in a real-world deployment. Our experimental results reveal that Crucible systematically quantifies the tunable space across different algorithms. Furthermore, Crucible provides a new dimension for algorithm analysis and design, which ultimately leads to performance improvements. Our code is available at https://github.com/thu-media/Crucible.

We report the development of a knowledge representation and reasoning (KRR) system built on hybrid SHACL-SKOS ontologies for globally harmonized system (GHS) material Safety Data Sheets (SDS) to enhance chemical safety communication and regulatory compliance. SDS are comprehensive documents containing safety and handling information for chemical substances. Thus, they are an essential part of workplace safety and risk management. However, the vast number of Safety Data Sheets from multiple organizations, manufacturers, and suppliers that produce and distribute chemicals makes it challenging to centralize and access SDS documents through a single repository. To accomplish the underlying issues of data exchange related to chemical shipping and handling, we construct SDS related controlled vocabulary and conditions validated by SHACL, and knowledge systems of similar domains linked via SKOS. The resulting hybrid ontologies aim to provide standardized yet adaptable representations of SDS information, facilitating better data sharing, retrieval, and integration across various platforms. This paper outlines our SHACL-SKOS system architectural design and showcases our implementation for an industrial application streamlining the generation of a composite shipping cover sheet.

Cardiovascular diseases are a pervasive global health concern, contributing significantly to morbidity and mortality rates worldwide. Among these conditions, arrhythmia, characterized by irregular heart rhythms, presents formidable diagnostic challenges. This study introduces an innovative approach utilizing deep learning techniques, specifically Convolutional Neural Networks (CNNs), to address the complexities of arrhythmia classification. Leveraging multi-lead Electrocardiogram (ECG) data, our CNN model, comprising six layers with a residual block, demonstrates promising outcomes in identifying five distinct heartbeat types: Left Bundle Branch Block (LBBB), Right Bundle Branch Block (RBBB), Atrial Premature Contraction (APC), Premature Ventricular Contraction (PVC), and Normal Beat. Through rigorous experimentation, we highlight the transformative potential of our methodology in enhancing diagnostic accuracy for cardiovascular arrhythmias. Arrhythmia diagnosis remains a critical challenge in cardiovascular care, often relying on manual interpretation of ECG signals, which can be time-consuming and prone to subjectivity. To address these limitations, we propose a novel approach that leverages deep learning algorithms to automate arrhythmia classification. By employing advanced CNN architectures and multi-lead ECG data, our methodology offers a robust solution for precise and efficient arrhythmia detection. Through comprehensive evaluation, we demonstrate the effectiveness of our approach in facilitating more accurate clinical decision-making, thereby improving patient outcomes in managing cardiovascular arrhythmias.

Hartmann noted that "Crucible" was well into development when he joined the company in August 2018. The game, which was first announced in 2016, contained a battle royale mode meant to compete with the likes of "PUBG" and "Fortnite," as well as teamfighting modes inspired by elements of "League of Legends" and "Dota 2." Hartmann noted that "competition in the genre was fierce" for "Crucible," and the studio applied what it learned from the experience to its work on "New World," another Amazon Games MMO that launched in 2021, and, eventually, "Lost Ark."

Amazon Games has officially launched Crucible, one of the two titles it's been planning to release this year. The free-to-play third-person shooter is now available on Steam, and logging in before 11:59 PM PST on June 1st/2:59AM EST on June 2nd will earn players 1,000 in-game Credits for free. Crucible has 10 hunters to choose from at launch, including robotic botanist Bugg (pictured above), who's the game's obvious poster child. Each hunter has their own weapons and abilities that they must use to defeat not just opponents, but also the planet's flora and fauna. The game has also launched with three game modes.

It was conceived as an online book store, then transformed into an e-commerce giant and now Amazon has entered the world of video games. The firm released its first original big-budget game called Crucible with the hopes to take on rival titles such as Fortnite and League of Legends. The free-to-play, third-person shooter game is driven by choices of players who work with teammates to take down alien creatures. Wedbush analyst Michael Pachter told CNBC that Amazon's move into the gaming space is'the same way that they got into books and music.' Amazon has its hands in a range of products and services – it is developing artificial intelligence, provides data storage, produces movies and more.

On the surface, "Crucible" looks like an average third-person arena online shooter that mixes elements of "Overwatch," (characters with different skill sets) with those other familiar titles. "Crucible" is an attempt to fuse the chaos of a hero shooter with the pacing and strategy of a multiplayer online battle arena, like "League of Legends." And much like "Fortnite" distilled the satisfaction of loot grinds to a single match, "Crucible" allows players to level up within a game, turning matches into dynamic power plays with explosive crescendos. That process is made easier thanks to every game being filled with AI-controlled enemy aliens, meaning you don't have to best the living to increase your abilities.

The e-commerce giant has a foothold in audiobooks, fresh groceries, Netflix-style video streaming and oh-so-much-more. It's no surprise, therefore, that the company wants to widen its influence in the video game industry. The Jeff Bezos empire already owns Twitch, the biggest game live-streaming service, and supports developers with its CryEngine-based Lumberyard platform and AWS server infrastructure. But it's never been a heavyweight game publisher. Multiplayer brawler Breakaway was canceled and The Grand Tour Game was a forgettable TV show tie-in. A lot is riding on Crucible, then.

Amazon enters the crowded games industry in full force Wednesday with its release of Crucible, the first big-budget PC game to come from Amazon Game Studios. Crucible is a promising mainstream introduction for the eight-year-old studio, which until now has had a large question mark hanging over its head. Crucible is a third-person team shooter that takes place on a large junglelike planet in a sci-fi future. As one of a diverse cast of heroes called "hunters," players mine resources from reptilian monsters and go head to head to capture points in their choice of three competitive modes. In a preview session hosted by Amazon Game Studios earlier this month, WIRED spent three hours playing the game and interviewing its designers.

GREENLIGHT, Business coaching firm, launches a new Artificial Intelligence (AI) simulator product to train startup founders how to overcome obstacles to be sustainable and profitable. The product was code-named "Crucible". A team of Artificial Intelligence (AI) tech developers, gaming experts, and serial entrepreneurs brought their domain expertise into a continuous learning platform and designed crucible product. A proprietary Smart Start framework from Greenlight is ued for assessing and scoring managerial competency and further improving capability with targeted action plans and simulating successful outcomes. Crucible was tested with startups from Columbia University and several candidates competing in the IBM Watson AI XPRIZE.