Introduction
The DataHack Summit 2024 is set to be an epicenter of innovation and knowledge, bringing together the most brilliant minds in AI and Data Science. This year’s summit will showcase transformative advancements, providing attendees with invaluable insights and practical skills.
Here are the top 10 sessions you simply cannot miss, each offering unique insights and practical knowledge to propel your understanding and application of AI to new heights.
Table of contents
- Mastering Multilingual GenAI – Open-Weights for Indic Languages
- Building Multi-Modal Models for Content Moderation on Social Media
- Learning Autonomous Driving Behaviors with LLMs & RL
- Improving Real-World RAG Systems: Key Challenges & Practical Solutions
- Agentic RAG Systems with LlamaIndex
- Coding a ChatGPT-style Language Model from Scratch in PyTorch
- Multi-Modality in LLMs: New Poster Child Everyone is Striving For!
- Finding Actor Look-alikes with Multi-modal LLMs
- Agentic AI: The Rise of Autonomous AI Agents and LangGraph
- Navigating LLM Tradeoffs: Techniques for Speed, Cost, Scale & Accuracy
1. Mastering Multilingual GenAI – Open-Weights for Indic Languages
Dive into the world of multilingual Generative AI with Viraat Aryabumi as he demonstrates how to fine-tune the aya-23-8B model for new languages using QLORA. This session will highlight the significance of integrating multiple languages, the associated challenges, and practical steps for ensuring safety and efficacy in multilingual AI.
Speaker: Viraat Aryabumi, Research Scholar
2. Building Multi-Modal Models for Content Moderation on Social Media
Explore how social media platforms manage diverse content through advanced multimedia classification techniques. Pulkit Khandelwal will cover the extraction of key audio features using CNNs and other machine learning models to improve content moderation, focusing on real-world applications and hands-on experience.
Speaker: Pulkit Khandelwal, Data and Applied Scientist II
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3. Learning Autonomous Driving Behaviors with LLMs & RL
Join Mayank Baranwal as he discusses the revolutionary approach of using Large Language Models (LLMs) to generate reward signals for reinforcement learning (RL) in autonomous driving. This session will delve into the creation of reward functions, achieving human-like driving behaviors, and practical implementations of LLMs in RL.
Speaker: Mayank Baranwal, Senior Scientist, Data and Decision Sciences
4. Improving Real-World RAG Systems: Key Challenges & Practical Solutions
Inspired by Barnett et al.’s renowned paper, Dipanjan Sarkar will explore the common challenges in building Retrieval Augmented Generation (RAG) systems and offer practical solutions. This session promises hands-on demonstrations and insights into the latest advancements in RAG technology.
Speaker: Dipanjan Sarkar, Head of Community and Principal AI Scientist
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5. Agentic RAG Systems with LlamaIndex
Ravi Theja will present the next evolution in RAG systems—Agentic RAG. Learn how these advanced systems handle complex queries with deep contextual understanding and dynamic response capabilities, enhancing performance with tools like query planning and reflective learning.
Speaker: Ravi Theja, Developer Advocate Engineer
6. Coding a ChatGPT-style Language Model from Scratch in PyTorch
Joshua Starmer will guide you through the process of coding, training, and deploying a ChatGPT-style language model using PyTorch. This hands-on session will cover model components, data formatting, and fine-tuning techniques to create a production-ready language model.
Speaker: Joshua Starmer, PhD, Founder and CEO
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7. Multi-Modality in LLMs: New Poster Child Everyone is Striving For!
Sandeep Singh will take you on a journey through the revolutionary impact of multi-modal language models. Discover how these models integrate text, images, audio, and video to transform sectors like healthcare, entertainment, and education, while addressing ethical challenges and future research directions.
Speaker: Sandeep Singh, Expert Senior Director
8. Finding Actor Look-alikes with Multi-modal LLMs
Anand S will unveil the fascinating world of identifying actor look-alikes using multi-modal LLMs. This session will demonstrate how embeddings can uncover clusters of similar-looking actors and provide insights into the overlaps in facial features across Hollywood.
Speaker: Anand S, CEO
9. Agentic AI: The Rise of Autonomous AI Agents and LangGraph
Arun Prakash Asokan will explore the rise of autonomous AI agents and the frameworks guiding their development. Learn about LangGraph and its capabilities in defining agentic AI workflows, and discover advanced RAG techniques for creating more capable AI systems.
Speaker: Arun Prakash Asokan, Associate Director Data Science
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10. Navigating LLM Tradeoffs: Techniques for Speed, Cost, Scale & Accuracy
Kartik Nighania will provide strategies to optimize large language models across dimensions such as speed, cost, scale, and accuracy. This session will feature real-world examples and tools to enhance model performance and accelerate time to market.
Speaker: Kartik Nighania, MLOps Engineer
End Note
DataHack Summit 2024 offers a wealth of knowledge and cutting-edge advancements in AI. These top 10 sessions are a must for anyone looking to stay ahead in the field, offering unique insights and hands-on experiences.
Don’t miss out on these must-attend sessions to enhance your expertise and drive impactful results at your workplace.
With a career spanning 5 years, Swati has worked with top institutions to curate content for them.
A software engineer, data science enthusiast, and a stickler for grammar who always jumps at every chance to explore food, life, and mysterious theories. A Potterhead with a passion for Psychology, she is always up for learning new theories on life. She finds herself amused with books, podcasts, and vlogs that add value to life.
