Ali Husnain@Hxnyn

The Decentralized AI Model Marketplace is a platform hosted on the Qubic blockchain, designed to facilitate a peer-to-peer ecosystem for artificial intelligence services. It utilizes Qubic's high-performance, decentralized compute layer to run AI models without relying on centralized data centers. Model creators register their AI algorithms (like image recognition or sentiment analysis) via smart contracts. Users then submit data to these models and pay a micro-transaction fee in Qubic tokens. This system efficiently connects those needing AI capabilities with those providing computational resources, ensuring transparency, censorship resistance, and fair compensation for all network participants, thus democratizing access to AI power.

Engineering teams work with large volumes of documents such as FEED reports, maintenance logs, design notes, safety reviews, and technical assessments. Manually analyzing these documents requires engineers to spend hours reading, identifying issues, summarizing findings, preparing checklists, and drafting email updates. These tasks are repetitive, time-consuming, and often delay critical project decisions. To address this challenge, the Smart Task Automation Agent leverages the capabilities of IBM watsonx Orchestrate to automate the entire engineering review workflow. The agent intelligently reads engineering documents uploaded by the user, detects key issues, extracts essential technical information, and generates actionable engineering checklists. It also prepares a polished email summary that can be directly shared with supervisors or team members. This automation significantly reduces manual effort and enhances both speed and accuracy in engineering tasks. Instead of spending hours reviewing content, engineers can obtain structured insights within seconds. The agent ensures more consistent reporting, faster communication, and improved decision-making. By combining AI-driven document understanding with automated workflow execution, this project demonstrates how agentic AI can transform engineering operations. It is particularly useful for industries like petrochemicals, manufacturing, construction, energy, and utilities where documentation and reporting are critical. The Smart Task Automation Agent ultimately streamlines engineering processes, boosts productivity, and enables teams to focus on high-value design and problem-solving activities while the AI handles routine work efficiently.

This project explores the use of artificial intelligence for load frequency control (LFC) in a single-area power system. Keeping system frequency stable is vital for reliable electricity supply, as sudden load changes can cause deviations that threaten grid stability. Traditional controllers like PID (Proportional-Integral-Derivative) can correct frequency deviations, but they often struggle with nonlinearities and complex system dynamics. Here, a feedforward Artificial Neural Network (ANN) is trained to predict the next frequency deviation using recent historical data of frequency and load. The ANN controller adjusts the mechanical power input in real time to minimize these deviations. Training data is generated from numerous random load profiles to simulate realistic disturbances. The performance of the ANN controller is compared with both open-loop (no control) and classical PID control. Results show that the ANN achieves better frequency regulation, with lower root mean square (RMS) deviations and smoother responses. Graphs of frequency, mechanical power, and load clearly demonstrate the ANN’s ability to handle disturbances more effectively than PID. This work highlights the potential of machine learning in modern power system control, offering an adaptive and robust approach to frequency regulation. Future work could extend this to multi-area systems, use recurrent neural networks for better temporal modeling, and explore reinforcement learning for optimal control strategies.

⏱️ You’ve got 48 hours - create, build, and launch! 🌟 Get direct access to Qubic, mentors, and ecosystem support. 💰 Compete for your share of $44,550 in prizes across two tracks. 🤝 Work solo or team up to design the next wave of blockchain innovation. 🧑‍💻 Sign up and start building on one of the world’s fastest decentralized networks..

Leverage Orchestrate’s digital skills to design solutions that automate repetitive tasks, orchestrate workflows across tools, and empower employees to focus on high-value work. ⏳ Complete your project in just 48 hours and showcase your innovation. 🚀 Gain hands-on experience building with IBM watsonx Orchestrate. 💡 Develop practical AI agents that reshape the way teams and organizations operate. ⭐ Learn directly from experts who will support you throughout the event. 🤝 Team up or work independently to bring your vision to life. 💰 Prizes: $10,000 🧑🏻‍💻 Sign up before the Kick-Off Stream and start shaping the future with IBM watsonx Orchestrate!

Join the next edition of our flagship AI hackathon — now featuring Google, AppliedAI, and Qdrant as official partners, with over $45,500 in prizes and exclusive partner challenges. After an incredible launch earlier this year, we’re back with the next edition of our AI hackathon series leading up to the /function1 AI Conference & Exhibition in Dubai. Tap into the power of AI to innovate, build, and take your AI skills to the next level in this high-impact hybrid experience. 📅November 14–19, 2025 • Nov 14–18: Collaborate and build online with AI enthusiasts from around the world. All projects must be submitted by end of day on November 18 • Nov 18 (Dubai): An exclusive on-site build day at Festival Arena Dubai for selected participants. • Nov 19 (Dubai): Live on-stage pitching & winners announcement at the /function1 Conference. 🌟 Get support from expert mentors throughout. 👥 Go solo or team up. 📍 Please note: On-site participation is by invitation only. Travel and accommodation will not be covered for selected participants. Further details will be shared with those accepted. 🧑🏻‍💻 Secure your spot now—sign up before the Kick-Off Stream!