IDEAS AND TOPICS FOR AN AI EVENT

An AI Conclave Topics

General AI Concepts for All Branches:

1. Introduction to Artificial Intelligence:
2. AI Ethics and Societal Impact:
3. Machine Learning Fundamentals:
4. Natural Language Processing (NLP):
5. AI and Creativity:

AI Topics for Non-Core Branches:

Mechanical Engineering:

1. AI in Manufacturing and Robotics:
2. AI in Design and Optimization:

Civil Engineering:

1. AI in Construction and Smart Cities:
2. AI in Environmental Sustainability:

Electrical and Electronics Engineering (EEE):

1. AI in Power Systems and Smart Grids:
2. AI in Embedded Systems and IoT:

Commerce and Business:

1. AI in Business Analytics:
2. AI in Marketing and Customer Experience:
3. AI and Financial Analysis:

Interactive Workshops and Hands-On Sessions:

1. AI for Beginners Workshop:
2. AI & Data Science in Python:
3. AI in Robotics:
4. AI for Civil Infrastructure Modeling:
5. AI-Powered Business Insights:

AI Tools Overview:

• Python: A go-to language for AI and machine learning with libraries like TensorFlow, Scikit-learn, Keras, and PyTorch.
• MATLAB: Popular in engineering fields for simulation and design.
• Google Colab: A cloud-based tool for running Python AI models without setting up a local environment.
• AutoCAD/Revit/Civil 3D: Popular design and modelling tools in Civil and Mechanical Engineering with AI plugins.
• Weka: Easy-to-use data mining tool for beginners.

Suggested Guest Speakers/Topics:

• Industry Experts: Focus on the impact of AI across industries (Healthcare, Automotive, Finance).
• AI Entrepreneurs: Share how AI is driving innovation in startups.
• Academic Experts: Explain cutting-edge research in AI and its future impact.

Panel Discussions:

• The Role of AI in the Future of Jobs: How AI will change career opportunities for students in non-core fields.
• AI for Social Good: AI’s impact on sustainability, healthcare, and solving global challenges.

An AI Conclave for a diverse audience like school and college students from different branches should focus on making AI accessible and relevant for all fields. By integrating AI topics specific to Mechanical, Civil, EEE, and Commerce along with general AI knowledge, you can create a highly engaging and informative event. This cross-disciplinary approach will show students how AI can shape their future, no matter what field they are pursuing.

Tools For Demo

General AI and Machine Learning Tools:

1. Google Teachable Machine (Beginner-friendly, No coding required)
2. Google Colab (Python-based, Cloud)
3. Weka (Machine Learning tool for beginners)
4. Python (with libraries like TensorFlow, Keras, Scikit-learn, and Pandas)
5. IBM Watson Studio

For Engineering Branches (Mechanical, Civil, EEE):

1. MATLAB (with AI & ML Toolboxes)
2. AutoCAD (with AI Plugins)
3. ROS (Robot Operating System)
4. Revit (Building Information Modeling - BIM)
5. Ansys
6. PyPSA (Python for Power Systems Analysis)

For Commerce and Business Students:

1. Power BI
2. Tableau (with AI integration)
3. HubSpot (with AI-powered marketing tools)
4. Google Analytics

AI for Interdisciplinary Applications:

1. DALL-E (AI Art Generation)
2. OpenCV (Open Source Computer Vision Library)
3. Dialogflow (Google's NLP platform for chatbots)
4. Arduino with TensorFlow Lite

AI Demonstration Ideas for the Conclave:

• Sentiment Analysis with NLP: Demonstrate how AI can analyze social media sentiment using tools like Google Colab (Python with NLTK or SpaCy).
• AI-powered Chatbot Creation: Use Dialogflow to show students how to build an interactive chatbot.
• AI in Robotics: Demonstrate a basic AI-powered robot using Raspberry Pi and ROS.
• Business Data Analytics: Showcase how Power BI or Tableau can be used to generate AI-powered insights from data.
• Predictive Maintenance: Demonstrate MATLAB’s AI toolbox for predicting machinery failure in Mechanical and Electrical systems.

Other Tools to Demo:

1. ChatGPT (Pro Version)

• Description: ChatGPT is an AI-based language model developed by OpenAI, capable of generating human-like text. The Pro version offers advanced capabilities, including faster response times, priority access to new features, and enhanced understanding of complex prompts. It’s ideal for content creation, customer service automation, brainstorming, and more. It is widely used for chatbot development, writing assistance, and conversational AI applications.
• Use Case: Content generation, virtual assistants, customer interaction.

2. MidJourney

• Description: MidJourney is an AI-powered platform that specializes in generating stunning visuals and artwork from text prompts. It leverages AI to interpret user inputs and create high-quality, unique images. MidJourney is popular among artists, designers, and marketers looking to visualize ideas or create concept art without requiring advanced graphic design skills.
• Use Case: Graphic design, digital art, concept art, marketing visuals.

3. Runway ML

• Description: Runway ML is a platform that provides AI tools for creatives, allowing users to apply machine learning models to tasks such as video editing, image manipulation, and content generation. It offers an easy-to-use interface for experimenting with AI models, making it accessible to non-technical users interested in AI-enhanced creative workflows.
• Use Case: Video editing, real-time object tracking, AI-powered image editing, creative applications.

4. Hugging Face

• Description: Hugging Face is a widely known platform for Natural Language Processing (NLP). It provides a library of pre-trained transformer models for tasks like text classification, sentiment analysis, translation, and text generation. Hugging Face's community-driven hub allows users to share, experiment, and fine-tune models for various AI applications.

One Topic or Session for LLMs

Large Language Models (LLMs) are AI systems designed to understand and generate human-like text. They are trained on massive datasets and are capable of performing various natural language processing tasks, including text generation, translation, summarization, and answering questions. Here's a quick overview of some popular LLMs:

1. GPT (Generative Pre-trained Transformer) by OpenAI

• Description: GPT is one of the most powerful LLMs, designed to generate coherent and contextually relevant text. It's used in applications like content creation, chatbots, and coding assistance.
• Key Feature: Extensive pre-training on diverse datasets, excelling in open-ended text generation.

2. BERT (Bidirectional Encoder Representations from Transformers) by Google

• Description: BERT is optimized for understanding the context of words in a sentence, making it excellent for tasks like question answering, sentiment analysis, and text classification.
• Key Feature: Its bidirectional training enables it to understand the full context of a sentence, unlike traditional left-to-right models.

3. T5 (Text-to-Text Transfer Transformer) by Google

• Description: T5 treats all NLP tasks as a text-to-text problem, converting inputs into outputs. It's versatile and can handle summarization, translation, and question-answering tasks.
• Key Feature: Unified text-to-text framework for various NLP tasks, making it highly adaptable.

4. LLaMA (Large Language Model Meta AI) by Meta

• Description: LLaMA is a powerful model focused on academic research and providing efficient training for NLP tasks. It's lightweight compared to some other LLMs, making it more accessible for research purposes.
• Key Feature: A smaller architecture designed to perform well with fewer computational resources.

5. Bloom by BigScience

• Description: Bloom is an open-access multilingual LLM designed by BigScience for diverse language generation tasks. It supports over 50 languages and was built with collaborative research efforts.
• Key Feature: Open-access and collaborative, with multilingual capabilities.