
𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭: Businesses and investors struggle to stay updated with real-time market trends, often relying on outdated or fragmented data sources. Traditional analysis methods lack AI-driven insights, making it difficult to anticipate risks and opportunities efficiently. 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Granite-AI Market Navigator addresses this gap by using the Bing News API to fetch real-time news and IBM Granite AI models (Granite-13b-Instruct-V2) to analyze sentiment. This AI-powered solution visualizes market trends through an interactive sentiment thermometer and provides AI-generated investment recommendations. 𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬 & 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐚𝐥𝐢𝐭𝐢𝐞𝐬: 𝐑𝐞𝐚𝐥-𝐓𝐢𝐦𝐞 𝐌𝐚𝐫𝐤𝐞𝐭 𝐍𝐞𝐰𝐬 𝐅𝐞𝐭𝐜𝐡𝐢𝐧𝐠: . Users input keywords related to business trends. . The system fetches the latest news using the Bing News API. . Displays 5-10 relevant articles with summaries and direct links. 𝐈𝐁𝐌 𝐆𝐫𝐚𝐧𝐢𝐭𝐞 𝐀𝐈-𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐒𝐞𝐧𝐭𝐢𝐦𝐞𝐧𝐭 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Analyzes news headlines and summaries using IBM Granite-13B-Instruct-V2. Determines sentiment categories: Positive, Neutral, or Negative. Displays an AI-driven sentiment thermometer (Hot = Trending, Cold = Low Impact). 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 & 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐀𝐬𝐬𝐢𝐬𝐭𝐚𝐧𝐜𝐞: Provides AI-powered recommendations based on sentiment trends. Example: High positive sentiment → Investment Opportunities.
23 Feb 2025

BandOptimizer is an innovative AI/ML-powered web application designed to optimize bandwidth usage for public sector schools and hospitals. Built with Streamlit, the app provides administrators with actionable insights by analyzing uploaded CSV files containing network data. With the power of predictive analytics, bandOptimizer categorizes bandwidth usage patterns, helping organizations manage resources more efficiently and reduce costs. The app features an intuitive interface, making it accessible for non-technical users, and includes sample datasets to ensure ease of testing. By leveraging modern technologies like Python, Pandas, and Matplotlib, bandOptimizer empowers users to make data-driven decisions for improving network performance and optimizing resource allocation.
26 Jan 2025
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The Voice-to-Voice AI Chatbot will be the next generation in conversational AI, further envisioned to permit the voice-based interaction with the accuracy; it will use the Whisper model from OpenAI for high-quality transcription of audio into text and combine this functionality with the AI/ML API to generate insightful and contextually relevant responses. By mere speech to the chatbot, which processes audio input, sends it to the AI model for intelligent analysis and then responds both in text and synthesized speech by using gTTS. It is a completely innovative tool that advances user interaction through real-time, natural conversations, fitting this tool perfectly for applications like virtual assistants, customer support, and even interactive learning environments.
11 Oct 2024