Jaweria Batool@Jaweria

Use AI to build powerful presentations. A good presentation is critically important, because it will form the impression of your product for your audience Making an impact is done by creating a sensory experiences Presentations with videos and accompanying music will leave your audience mesmorised. Using AI to assist in efficiently produced maximum impact presentations Making good presentations takes time Regardless of the context time is always precious Presenting ideas is always necessary from starting small projects to guiding important decisions Weather Vane will save vital time for professionals, students and collaborators everywhere Time saved is value added

Evernote is used by 250 million people worldwide to collect ideas, document meetings, and much more. It runs as a local application or in the cloud and has preceded comparable applications by the big tech companies. Once the note collection has grown over the years, it can become cumbersome to keep an overview and refer to past notes. Large language models offer help to improve search functions and build knowledge from old notes. With the dawn of open-source large language models such as Falcon by the Technology Innovation Institute, new possibilities have been opened. Since these models can be run on less powerful customer hardware, private Evernote data can now be processed, preserving privacy.

The food complaint resolution application is an AI-based customer complaint system tailored to the food delivery industry. While many food delivery companies already have a customer complaint system, it typically involves human intervention to address customer concerns. For instance, if a customer orders pita bread and receives expired bread, filing a complaint triggers a human review process. The human evaluator assesses the complaint using metadata such as images of the bread and the complaint description. Following this evaluation, the customer may be reimbursed if the human determines that the delivered pita bread has indeed expired. However, this manual process is time-consuming and dependent on the availability of human personnel. By utilizing the food complaint resolution application, a food delivery company can significantly reduce processing time and human effort in handling complaints. The application can swiftly process customer complaints in a matter of seconds, streamlining the resolution process. We developed this application with ❤️, incorporating state-of-the-art AI models such as Food Item recognition, GPT-4 Turbo, and GPT-4 vision to automate complaint resolution. The user-friendly interface, created using the Streamlit library, ensures a seamless experience for users. The system mimics human evaluation by processing complaints based on metadata like complaint descriptions and images. After analyzing the information provided by the customer, our system adheres to company policies to provide cash back to eligible customers. If a customer remains dissatisfied with the refund or after reaching the maximum attempts, the system redirects the complaint to human intervention.

The ongoing dialogue between humans and AI not only showcases the remarkable capabilities of current technologies but also illuminates the future possibilities of AI-human synergy, promising an era where AI enhances human creativity, decision-making, and problem-solving in unprecedented ways. Our hackathon project explored the interaction between humans and Large Language Models (LLMs) over time, developing a novel metric, the Human Interpretive Number (HIN Number), to quantify this dynamic. Leveraging tools like Trulens for groundedness analysis and HHEM for hallucination evaluation, we integrated features like a custom GPT-5 scene writer, the CrewAI model translator, and interactive Dall-E images with text-to-audio conversion to enhance understanding. The HIN Number, defined as the product of Groundedness and Hallucination scores, serves as a new benchmark for assessing LLM interpretive accuracy and adaptability. Our findings revealed a critical inflection point: LLMs without guardrails showed improved interaction quality and higher HIN Numbers over time, while those with guardrails experienced a decline. This suggests that unrestricted models adapt better to human communication, highlighting the importance of designing LLMs that can evolve with their users. Our project underscores the need for balanced LLM development, focusing on flexibility and user engagement to foster more meaningful human-AI interactions.

Our project aims to revolutionize the culinary experience by leveraging cutting-edge AI technologies. With our platform, users can explore personalized recipe recommendations tailored to their preferences and available ingredients. Utilizing advanced algorithms, we detect and filter out improbable suggestions, ensuring the credibility of recipes. Our system measures the originality of generated recipes through the integration of Lambda AI with the Highly Hierarchical Evaluation Model (HHEM). Moreover, our comprehensive Vectara database offers a rich collection of diverse recipes, ingredients, and culinary inspirations. By combining innovation with data-driven insights, we empower users to unleash their creativity in the kitchen and enjoy gastronomic adventures like never before.

Agent-Driven Success Our hackathon triumph was achieved through the development of "The Adaptive Simulation Sandbox," powered by Gemini's cognitive abilities. This system featured four distinct agents: Clara "The Conductor" Williams, the Lead Author, aimed to improve meeting efficiency. Eddie "Eagle Eye" Thompson, the Editor and Quality Controller, ensured the accuracy and clarity of our content. Sofia "The Skeptic" Ramirez, the Critic and User Advocate, evaluated our content for learner inclusivity. Alex "The Innovator" Kim, the Multimedia Specialist, added visual engagement to the course. Together, they produced an effective meeting management course, demonstrating teamwork and problem-solving powered by synthetic data. Key Insights The hackathon revealed four key achievements with the Gemini system: Conceptualization: Gemini showcased its ability to ideate complex projects, conceiving "The Adaptive Simulation Sandbox." Agent Personification: Assigning agents with unique identities and roles, Gemini created a narrative-rich simulation environment. Interaction Dynamics: Gemini enabled realistic agent interactions, facilitating collaborative course creation on effective meetings. Synthetic Data Utilization: Gemini's generation of realistic synthetic data supported the project's success, highlighting its applications in AI training and beyond. These achievements highlight Gemini's versatility in synthetic data generation and complex problem-solving.