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Aditya
Gautam
Tech Lead, Machine Learning
Meta
Aditya is a seasoned Machine learning practitioner, currently working on LLM (Llama) application to enhance recommendation and ranking algorithms at scale. He has led several critical Machine learning projects in Facebook reels including user interest exploration, trend detection, quality improvement and safeguarding policy by detection violation. He played a pivotal role in mitigating misinformation on Facebook platform by pioneering effective Machine learning techniques and effectively deploying them at scale, resulting in reducing harmful content and ensuring safe user experience.With this, Aditya is also very passionate about space of AI policy and governance. He holds a master’s degree from Carnegie Mellon University and has worked in Machine learning at Google and has been a founding engineer of an AI startup at Area 120 (Google Incubator). Aditya holds a US patent and has been associated with many organizations including IEEE (Senior Member), Integrity Institute and ACM.
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29 April 2025 12:35 - 13:00
Panel discussion: Building faster, more efficient agents - Accelerating adoption across the enterprise
Explore the strategies and technologies needed to build faster and more efficient AI agents, driving broader adoption across the enterprise. In this interactive conversation, our lineup of industry practitioners will discuss best practices for optimizing agent performance, reducing computational costs, and improving scalability.
29 April 2025 14:30 - 15:00
Panel discussion: Building LLM alignment pipelines - from fine-tuning to real user feedback loops
Fine-tuning is just the beginning. As LLMs move from labs into real-world applications, achieving true alignment requires continuous learning from user interactions. In this panel, industry leaders from Google DeepMind, Walmart, Meta, and Feedback Intelligence will explore how to design end-to-end alignment pipelines - combining fine-tuning, reinforcement learning, and user feedback loops - to build safer, more useful AI systems at scale.