Piotr Zak@piotrzak292

VoiceSence is a groundbreaking AI-driven project transforming content consumption. By harnessing AI21 Lab and 11Eleven Lab APIs, it elevates how users interact with blogs. VoiceSence intelligently converts text blogs into enriching audio experiences. Users input a blog URL, and AI21 Lab's NLP generates concise, coherent summaries. This innovative solution enables quick comprehension, perfect for time efficiency. But VoiceSence goes beyond summarization. Recognizing the need for personalized experiences, it integrates the 11Eleven Lab API, offering a wide array of customizable voices based on description, age, and gender. This groundbreaking feature creates a truly immersive listening experience, catering to diverse user preferences. VoiceSence's inclusive approach extends to the visually impaired, enabling accessible content consumption through audio. Multitaskers also benefit, as they can listen to lengthy articles while being productive. Its user-friendly interface ensures accessibility for users of all ages and technical abilities. The fusion of AI21 Lab's NLP expertise and 11Eleven Lab's top-notch audio capabilities marks a new era of content consumption, setting VoiceSence as a trailblazer in AI-driven applications. The project pushes boundaries, empowering users with accessible, engaging, and personalized content experiences. In conclusion, VoiceSence's revolutionary approach to summarizing and transforming blogs into customizable audio embodies true innovation. It empowers users, making information readily available and enhancing the overall user experience. With VoiceSence leading the way, AI-driven applications revolutionize information interaction for a dynamic and immersive future.

Imagine a day when you're feeling adventurous – the system agent detects the zest in your conversation and suggests vibrant and exotic recipes that align with your mood. On days when comfort is sought, the agent provides heartwarming comfort food ideas. The intersection of AI and emotion in this culinary sphere is a feat of innovation that creates a holistic cooking experience.What sets "Cognispace Recipe Mate" apart is its ability to tap into the unspoken language of emotions and translate it into flavorful creations. The personalized recipe recommendations not only cater to your taste preferences but also resonate with your emotional state, creating a profound connection between your feelings and your plate.This project's innovation extends beyond its technological prowess; it bridges the gap between human emotion and the culinary arts. It encourages users to explore their emotions, fostering a deeper connection with the food they prepare and consume. "Cognispace Recipe Mate" isn't just a recipe generator; it's a culinary companion that enhances your cooking adventure by adding an emotional layer to every dish.In conclusion, "Cognispace Recipe Mate" is a true testament to innovation in the culinary domain. By integrating AI, emotion analysis, and personalized recipe suggestions, it transforms the act of cooking into a multisensory experience that speaks to both the heart and the palate. Through its blend of cutting-edge technology and emotional resonance, this project elevates cooking from a mere task to a delightful journey of self-expression and discovery.

Forecasting algorithms for network prediction via simulated data, to integrate modern solutions (Satelitte ISPs) - for most people in the world. The solution is in python + using some google colabs. Github repository is available in : https://github.com/Synthapse/Network and Google Colab in https://colab.research.google.com/drive/1MGkMvDWOphm4Iyn8Kwq-_I2LyH07Khv9?usp=sharing#scrollTo=pSjoPXIHn2P7. There are a lot of potential cases for improving solutions - and feed it with real data. Cause the real network may contains more nodes- the solution contains only 217 nodes, that the separating via different kafka brokers and kubernetes will be supportive

Space Mission Hub: Revolutionizing Space Exploration with AI-Powered Mission Management Introduction: The Space Agent is a groundbreaking, comprehensive AI-powered platform designed to revolutionize the planning, execution, and management of space missions. In an era where space exploration is becoming increasingly complex and ambitious, there is a critical need for advanced tools that can integrate various aspects of mission management while leveraging the power of artificial intelligence. The Space Mission Hub addresses this need by providing a unified interface that combines mission planning, data access, automation, resource management, and efficiency optimization into a single, powerful solution. Core Components: The Space Mission Hub consists of five primary modules, each designed to address crucial aspects of space mission management: 1. Mission Planner: The Mission Planner module serves as the cornerstone of the Space Mission Hub, providing a sophisticated environment for conceptualizing and detailing space missions. This module allows users to input mission objectives and constraints, forming the foundation upon which all other aspects of the mission are built. Key Features: a) Objective Definition: Users can articulate clear, concise mission objectives, which the AI system uses to guide all subsequent planning and decision-making processes.

We focused on London for PoC - cause it’s the most developed smart city with the network infrastracture. And from that point for development is great for One Replication Strategy The London Smart City Optimization project enhances urban infrastructure using AI, IoT, and cybersecurity. The focus areas include This initiative ensures London remains a sustainable, secure, and efficient smart city. Network.AI - 3 LLM Agents (which communicate to each other for gathering spec and automate documentation process (cyb1, net1, ene1) Network.Data - Algorithms for data science analysis, mostly free databases + kaggle (London, 2014y, 2021y) Network.Frontend - Promotional react app, which integrate agents + provide basic auth (firebase) Network.Backend - Analyse of different protocols, and communicating with frontend due to rapport generating