Pune AI Community

🎓 Guiding the Next Generation into AI 🚀 Had the opportunity to conduct a mentorship session for students under the Educational Assistance Scheme (EAS), an initiative by Seva Sahayog Foundation. The session was delivered in Marathi (with English slides) to make it more relatable and effective💡 Covered: 🔹 What is AI?: breaking down the fundamentals 🔹 How to build a career in AI: practical pathways & guidance It was nice to interact with 120+ students from engineering, computer science, and commerce backgrounds, all eager to learn and grow 🙌 EAS, now in its 7th year, has supported 1000+ students in pursuing higher education through financial assistance and mentorship. Truly impactful work 👏 Grateful for the opportunity to contribute and support such bright minds in their journey 💙 🎥 Watch the full session here: https://lnkd.in/df-3E9_S 💬 What advice would you give to students starting their AI journey? #AI #Mentorship #Education #AIForStudents #CareerGuidance #Pune #SevaSahayog #AICommunity Dr. Anand Kolharkar Atul Nagras Shailesh Ghatpande

What started as an idea to simplify "Retrieval Augmented Generation (RAG)" has now turned into a complete learning journey 🙌 The "RAG to Riches" series was designed with one clear goal: 👉 Enable anyone to confidently start building RAG-based applications and here’s what we covered across the series: 🔹 Python Basics (4 sessions): building the programming foundation : https://lnkd.in/dNAj8K-X (by Anjali Kulkarni) 🔹 Generative AI Basics (4 sessions): ML, NLP, embeddings & LLMs : https://lnkd.in/dNn2w2dw (by Yogesh Haribhau Kulkarni) 🔹 Intro to RAG: connecting knowledge with intelligence : https://lnkd.in/d_SJGuy3 Yogesh Haribhau Kulkarni) 🔹 Bonus: Intro to AI Agents: taking a step toward Agentic RAG : https://lnkd.in/dnShVQya (by Yogesh Haribhau Kulkarni) 🙏 A big thank you to everyone who attended, learned, asked questions, and supported the initiative. Your engagement is what makes this community truly powerful. 🚀 What’s next? We’re now opening up the stage to YOU, the community! 👉 Want to share your knowledge, demo a project, or lead a session? We’d love to have you contribute and grow with us. 💬 Drop a comment or reach out us with a brief description of your talk and if available, a sample video youtube link of your past talk to puneaicommunity at gmail dot com cc yogeshkulkarni at yahoo dot com🚀! #RAG #GenerativeAI #AICommunity #LearnAI #PuneTech #AIForAll #KnowledgeSharing

🎉 4,000+ strong and just getting started! 🚀 Grateful to each one of you who has followed, shared, commented, and engaged with the "Pune AI Community (PAIC)". This milestone isn’t just a number, it’s a reflection of a growing movement to make AI accessible, inclusive, and meaningful for everyone. Together, we’re actively bridging the gap in AI knowledge across Pune, making sure AI doesn’t stay limited to a few, but reaches many. 💡 "Artificial Intelligence from classes to masses", this is not just our tagline, it’s our purpose. Through our initiatives, we aim to simplify AI and create real impact: 🔹 LetsAI: 1-hour online seminars to spark learning (already started, about 10 sessions done so far) 🔹 Zero2Hero: hands-on, in-person workshops for deep dives 🔹 A platform to showcase ideas, projects, startups, and opportunities A special thanks to everyone who has contributed, whether by attending sessions, sharing insights, or simply cheering us on. You are the reason this community thrives. 👉 If you believe in democratizing AI, help us grow even stronger: 🔗 Connect with the Founder: https://lnkd.in/di9eGpSK Follow, share, and invite your network to be part of this journey: 🌐 Website: https://lnkd.in/dZUBEEXu 🔗 LinkedIn: https://lnkd.in/d5bfn9WG 📢 Stay updated: Twitter (X): https://lnkd.in/d5zpwciy Instagram: https://lnkd.in/dm5czCGU WhatsApp Community: https://lnkd.in/dN4Vq_kR 📅 Luma Events: https://lnkd.in/dfEw4-r3 YouTube: https://lnkd.in/deEUWxbb 💬 What topic should we explore next? Drop your ideas below! Also, just to check how ready or interested you are in AI, here is a quiz question: You’re training a binary classification model on an imbalanced dataset: - 95% of samples belong to Class A - 5% belong to Class B Your model achieves "95% accuracy" on the test set. 👉 Question: Is this model actually good? If not, - What could be going wrong? - Which evaluation metrics would you use instead of accuracy? - How would you improve the model? 💬 Drop your thoughts below! #PuneAICommunity #AIForAll #ArtificialIntelligence #PuneTech #Community #AIIndia #Pune #India #ai #social

🎤 Call for Speakers | Pune AI Community (PAIC) PAIC is opening up speaking opportunities for our community members! If you're passionate about AI, Machine Learning, Deep Learning, NLP, or Generative AI, this is your chance to share your knowledge and make an impact. 🔍 Who can apply? • Students eager to showcase research or projects • Professors & trainers with fresh, unexplored topics • Practitioners willing to contribute to community learning 💡 Guidelines: • Talks must be non-commercial (no product/company promotion) • Sessions are free and open to all • No honorarium (community-driven initiative) • Talks will be recorded & published on the PAIC YouTube channel 📩 How to apply: Send us a brief description of your talk and if available, a sample video youtube link of your past talk to puneaicommunity at gmail dot com cc yogeshkulkarni at yahoo dot com🚀 #AI #MachineLearning #DeepLearning #NLP #GenAI #Pune #CommunityLearning #TechTalks

PAIC LetsAI: Introduction to Agents This session introduces the fundamental concepts of AI Agents and their role in modern AI systems. We will explain what agents are, how they differ from traditional chatbots, and why they are essential for autonomous task execution. Key components such as reasoning loops, action planning, and memory systems will be discussed. This foundational session sets the stage for building practical agent systems. Event details: 📅 21 March 2026 ⏰ 15:00 – 17:00 IST ✅ Open and free to all 🎥 Sessions will be recorded 🔗 Registration link: https://luma.com/67dwnc8f #Agents #GenerativeAI #LetsAI #PAIC #AIWorkflows

PAIC LetsAI: Introduction to Agents This session introduces the fundamental concepts of AI Agents and their role in modern AI systems. We will explain what agents are, how they differ from traditional chatbots, and why they are essential for autonomous task execution. Key components such as reasoning loops, action planning, and memory systems will be discussed. This foundational session sets the stage for building practical agent systems. Event details: 📅 21 March 2026 ⏰ 15:00 – 17:00 IST ✅ Open and free to all 🎥 Sessions will be recorded 🔗 Registration link: https://luma.com/67dwnc8f #Agents #GenerativeAI #LetsAI #PAIC #AIWorkflows

🔍 Why Geometric Kernels Matter in Modern Machine Learning In many machine learning applications today, we don’t just want predictions, we also want to understand how confident the model is about those predictions. This is especially important in high-stakes domains like healthcare, robotics, and scientific modeling. One class of models that naturally handles uncertainty is 'Gaussian Processes'. These models rely on a mathematical tool called a 'kernel', which essentially measures how similar two data points are. If two inputs are similar, the kernel gives a high value; if they are very different, the value is low. This similarity relationship helps the model make predictions and estimate uncertainty. Traditionally, kernels are designed for 'Euclidean data', the standard flat space where data points are represented as vectors with coordinates like (x, y, z). This works well for many common datasets such as tabular data or images. However, not all real-world data fits neatly into this structure. Many important datasets are inherently geometric or structured, including: • Social networks represented as graphs • Molecular structures in computational chemistry • 3D objects represented as meshes or surfaces • Planetary or climate data defined on curved/spherical surfaces (manifolds) In these cases, the underlying space is NOT FLAT, and traditional kernels struggle to represent meaningful similarities between data points. To address this challenge, researchers have developed GeometricKernels, a Python software package designed to bring kernel methods into these more complex geometric settings. The idea is to extend widely used kernels, such as the squared exponential (also known as the heat kernel) and the Matérn kernel, so they work naturally on graphs, manifolds, and other structured spaces. With these geometric kernels, machine learning models can better capture relationships in structured data while still maintaining reliable uncertainty estimates. In simple terms: ➡ Classical kernels work well in flat spaces. ➡ Real-world data often lives in curved or structured spaces. ➡ Geometric kernels bridge that gap. This development opens up possibilities for applying probabilistic machine learning techniques to domains where geometry plays a fundamental role. As machine learning continues to expand into scientific and engineering applications, tools like these will be essential for building models that are not only accurate, but also aware of their own uncertainty. 💻 GitHub: https://lnkd.in/e73vfbYX 📄 Paper: https://lnkd.in/eRCH88k4 (Ref: Viacheslav Borovitskiy's announcement post on Likedin) #MachineLearning #GeometricDeepLearning #GaussianProcesses #Kernels #Graphs #Manifolds #JMLR #OpenSource

PAIC LetsAI: Retrieval Augmented Generation Fundamentals Want to make Large Language Models more accurate, reliable, and context-aware? It all starts with Retrieval Augmented Generation (RAG). ⚡📚🤖 We’ll explore why retrieval is essential, how it enhances LLM accuracy, and how it helps reduce hallucinations. You’ll also learn about key components such as retrievers, vector stores, and generators while gaining a clear view of end-to-end RAG workflows. Event details: 📅 14 March 2026 ⏰ 15:00 – 17:00 IST ✅ Open and free to all 🎥 Sessions will be recorded 🔗 Registration link: https://luma.com/p5b43ynj If you want to understand how next-generation AI systems deliver more trustworthy answers, don’t miss this session. 🚀 #RAG #GenerativeAI #LLM #AIArchitecture #LetsAI #PAIC #FutureReady

🚀 Pune AI Community (PAIC) recently concluded its 4-part webinar series on the basics of Generative AI, an introductory learning journey that brought together AI enthusiasts, students, and professionals to explore the foundations behind today’s powerful AI systems. Over the past few weeks, we covered key concepts that form the backbone of Generative AI and modern AI applications: 🔹 Part 1: Machine Learning Foundations 📅 14 February 2026 An introduction to the core principles of machine learning including supervised & unsupervised learning, model training, evaluation, and common algorithms. 🎥 Watch here: https://lnkd.in/dZaMyGJv 🔹 Part 2: Natural Language Processing 📅 21 February 2026 Exploring how machines understand human language, covering text preprocessing, tokenization, linguistic features, and NLP tasks like classification, summarization, and question answering. 🎥 Watch here: https://lnkd.in/db375MDR 🔹 Part 3: Word Embeddings 📅 28 February 2026 Understanding how language is transformed into numerical vectors, semantic similarity, and how embeddings power applications like search, recommendation systems, and RAG. 🎥 Watch here: https://lnkd.in/dgwRJpxs 🔹 Part 4: Large Language Models 📅 7 March 2026 A deep dive into the architecture of LLMs, covering transformers, positional embeddings, attention mechanisms, and pre-training concepts. 🎥 Watch here: https://lnkd.in/dcA_8-re 🙏 Thanks to the participants who made this series engaging. We hope these sessions help more people start their journey into AI and Generative AI. 📚 If you missed the sessions, feel free to watch the recordings and continue learning! #GenerativeAI #ArtificialIntelligence #MachineLearning #NLP #LLM #WordEmbeddings #AICommunity #PAIC #LetsAI #AIWebinar #TechLearning #PuneTech