This study explores real-world human interactions with large language models (LLMs) in diverse, unconstrained settings in contrast to most prior research focusing on ethically trimmed models like ChatGPT for specific tasks. We aim to understand the originator of toxicity. Our findings show that although LLMs are rightfully accused of providing toxic content, it is mostly demanded or at least provoked by humans who actively seek such content. Our manual analysis of hundreds of conversations judged as toxic by APIs commercial vendors, also raises questions with respect to current practices of what user requests are refused to answer. Furthermore, we conjecture based on multiple empirical indicators that humans exhibit a change of their mental model, switching from the mindset of interacting with a machine more towards interacting with a human.

ChatGPT, the cutting-edge chatbot from OpenAI that was released in November 2022, can solve math equations, write a history term paper, compose a sonnet and almost everything in between. So it's not surprising that many educators support banning the chatbot in schools to prevent plagiarism, cheating and just plain inaccuracy. In response to these concerns, some major districts have banned the chatbot in schools. In December, the Los Angeles Unified School District "preemptively" blocked access to ChatGPT while "a risk/benefit assessment is conducted," a district spokesperson told the Washington Post. And in January, New York City Public Schools banned access to ChatGPT from devices and networks that the school owns, per the Washington Post.

The objective of this paper is to explore how financial big data and machine learning methods can be applied to model and understand financial products. We focus on residential mortgage backed securities, resMBS, which were at the heart of the 2008 US financial crisis. These securities are contained within a prospectus and have a complex waterfall payoff structure. Multiple financial institutions form a supply chain to create prospectuses. To model this supply chain, we use unsupervised probabilistic methods, particularly dynamic topics models (DTM), to extract a set of features (topics) reflecting community formation and temporal evolution along the chain. We then provide insight into the performance of the resMBS securities and the impact of the supply chain through a series of increasingly comprehensive models. First, models at the security level directly identify salient features of resMBS securities that impact their performance. We then extend the model to include prospectus level features and demonstrate that the composition of the prospectus is significant. Our model also shows that communities along the supply chain that are associated with the generation of the prospectuses and securities have an impact on performance. We are the first to show that toxic communities that are closely linked to financial institutions that played a key role in the subprime crisis can increase the risk of failure of resMBS securities.

The European Commission provides a platform for online dispute resolution (ODR): https://ec.europa.eu/consumers/odr. Our e-mail address can be found above in the site notice. We are not willing or obliged to participate in dispute resolution proceedings before a consumer arbitration board. As service providers, we are liable for own contents of these websites according to Paragraph 7, Sect. 1 German Telemedia Act (TMG). However, according to Paragraphs 8 to 10 German Telemedia Act (TMG), service providers are not obligated to permanently monitor submitted or stored information or to search for evidences that indicate illegal activities.

Urban legend has it that some of the greatest ideas in history started with a napkin. The Gettysburg Address, the poem that gave way to the U.S. National Anthem, and the premise of the Harry Potter series--each were reportedly born into the world through the medium of sketches on scrap paper--and when app creators put pen to paper for their ideas, this is often a canvas of choice. While rapid prototyping with the napkin and the whiteboard holds its charms, less charming is the prospect of translating quick sketches into working code. Last summer, a group of Garage interns tackled this problem by creating a prototype of their own: meet Ink to Code, a Microsoft Garage project, now available in the United States and Canada. Ink to Code is a Windows app that enables developers to draw wire frame sketches and export them into Visual Studio, expediting the process of prototyping Universal Windows Platform (UWP) and Android user interfaces.

This paper presents an analysis of data from a gift-exchange-game experiment. The experiment was described in `The Impact of Social Comparisons on Reciprocity' by G\"achter et al. 2012. Since this paper uses state-of-art data science techniques, the results provide a different point of view on the problem. As already shown in relevant literature from experimental economics, human decisions deviate from rational payoff maximization. The average gift rate was $31$%. Gift rate was under no conditions zero. Further, we derive some special findings and calculate their significance.