Faisal Abid
Google Developer Expert
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Faisal has served as a Head of AI and CTO, developing cutting-edge AI and machine learning solutions and architecting scalable systems on Google Cloud Platform that transform traditional industries.
Throughout his career leading diverse engineering teams across e-commerce, fintech, and healthcare sectors, Faisal has consistently delivered complex AI-powered systems that solve real business challenges. His approach emphasizes building microservices architectures that can scale effectively while maintaining security and performance. He excels in guiding teams through the implementation of advanced technologies, ensuring they remain agile and adaptive in rapidly evolving technical landscapes.
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Supercharge Your AI Applications: Building RAG Solutions with Gemini
In this talk, we will discuss the process of creating powerful Retrieval-Augmented Generation (RAG) solutions using Google's Gemini AI model and your own proprietary data. RAG combines the strengths of large language models with the ability to retrieve and incorporate specific information, resulting in more accurate and contextually relevant AI outputs.
You'll learn:
• The fundamentals of RAG and its advantages over traditional AI approaches
• How to prepare and format your custom data for optimal use with Gemini
• Techniques for fine-tuning Gemini on your dataset to create a specialized AI
• Best practices for integrating RAG solutions into your existing applications
• Strategies for improving response quality and maintaining data privacy
Harnessing the Power of LLMs and SQL with AlloyDB and BigQuery
Learn how to leverage Google Cloud's AlloyDB or BigQuery alongside state-of-the-art LLMs to extract deeper insights and automate complex queries from your vast data repositories.
Key topics we'll cover:
• How to use LLMs and SQL for data analysis
• Overview of AlloyDB and BigQuery capabilities and how they complement LLMs
• Techniques for using LLMs to generate, optimize, and explain SQL queries
• Strategies for natural language interfaces to your databases
• Implementing context-aware data exploration using LLMs and SQL
• Best practices for data security and privacy when combining LLMs with sensitive data
• Real-world case studies showcasing successful implementations
• Hands-on examples and code snippets to get you started
Whether you're a data scientist, analyst, or developer, this session will equip you with the knowledge to supercharge your data workflows. Discover how to ask complex questions of your data in natural language, automate report generation, and uncover hidden patterns with unprecedented ease.
From Curiosity to Creation: Building Your Own Perplexity-Style AI Search Engine
Ever wondered how Perplexity delivers those amazingly relevant search results? In this hands-on session, we'll demystify the technology behind AI-powered search engines and guide you through building your own.
You'll learn the core principles of how large language models work, understand how semantic search engines work, and walk away with practical knowledge to deploy a custom search engine on your own dataset.
Perfect for developers interested in AI applications and anyone looking to elevate their search infrastructure beyond traditional keyword matching.
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