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This video is part of the appearance, “Google Cloud Presents at Cloud Field Day 20“. It was recorded as part of Cloud Field Day 20 at 16:00-17:00 on June 13, 2024.
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Google Cloud’s Vertex AI platform is built on a rich history of innovation and enterprise readiness, offering an integrated AI-optimized portfolio. The platform leverages Google’s groundbreaking technologies such as TPUs and the transformer architecture, which have been instrumental in the development of large language models (LLMs) like Gemini. Gemini stands out for its multimodal capabilities, allowing it to process and reason across text, images, audio, and video simultaneously. This multimodal approach enables advanced functionalities like identifying specific moments in a video or understanding complex prompts that combine text and images. The platform also emphasizes flexibility and choice, providing options for different model sizes and prompting windows to match various use cases and cost considerations.
The presentation highlighted the practical applications of Vertex AI through several demos. One notable example demonstrated the model’s ability to process a 44-minute video and accurately identify a specific scene based on a text prompt, showcasing its capability to handle long context understanding. Another demo illustrated the use of a multimodal prompt, where a simple doodle was used to locate a corresponding scene in the video. These examples underscore the potential of Vertex AI in real-world scenarios, such as customer service chatbots, sports highlight identification, and even complex tasks like code transformation and financial document analysis. The platform’s ability to cache context and perform batch processing further enhances its efficiency and cost-effectiveness.
Vertex AI also focuses on enterprise readiness, ensuring data security, governance, and compliance. The platform provides tools for model evaluation, monitoring, and customization, allowing enterprises to tailor models to their specific needs while protecting their data. Features like grounding APIs help ensure the accuracy of model outputs by linking responses to verified data sources, addressing concerns about AI-generated content’s reliability. Additionally, the platform supports various levels of coding expertise, from no-code to full-code, making it accessible to a wide range of users. With its comprehensive suite of tools and emphasis on security and flexibility, Vertex AI positions itself as a robust solution for enterprises looking to leverage AI for diverse applications.
Personnel: Neama Dadkhahnikoo