Women in Data Science Puget Sound 2024

In the rapidly evolving landscape of search engine technology, the integration of Generative AI has marked a paradigm shift from traditional keyword-based algorithms to advanced, intent-driven models. This talk aims to dissect this transformation, elucidating how models like GPT-4 are not just enhancing search engine capabilities but are redefining them. We begin by exploring the genesis of this change – the shift from simple keyword recognition to the complex understanding of user intent. This is a journey from linear algorithms to AI models that comprehend context, semantics, and the nuanced intricacies of human language. The talk will illuminate how these AI-driven engines are now capable of predicting user intent, thereby delivering search results that are not only accurate but also contextually relevant, making information retrieval more intuitive and efficient. However, this innovation is not without its challenges. The core of this discussion will pivot to the myriad technical hurdles encountered in blending Generative AI into existing search architectures. We'll delve into the computational demands these models impose, addressing the need for substantial processing power and advanced data handling capabilities. This segment will also cover the obstacles in adapting to the rapid pace of AI technology evolution, ensuring that search engines remain not just relevant but cutting-edge. Another crucial aspect is data privacy and security – paramount in an era where user data is both vital and sensitive. We'll examine the strategies to safeguard user privacy while leveraging AI for personalized search experiences. Furthermore, we'll address the challenge of linguistic dynamism – how AI models cope with the ever-changing nature of human language and the implications this has for search accuracy and relevance. This talk aims not only to highlight the revolutionary impact of Generative AI on search engines but also to provide insights into the practical solutions and strategies being developed to surmount the associated technical challenges. It's designed for an audience deeply entrenched in data science and technology, offering a blend of high-level understanding and technical detail that will resonate with professionals in the field.