With this update, developers can use several new tools and models, such as the world completion model driven by PaLM 2, the Embeddings API for text, and other foundation models in the Model Garden. They can also leverage the tools available within the Generative AI Studio to fine-tune and deploy customized models. Google claims that enterprise-grade data governance, security, and safety features are also built into the Vertex AI platform.
Customers can use the Model Garden to access and evaluate base models from Google and its partners. There are over 60 models, with pals for adding newer models in the future. Also, the Codey model for code completion, code generation, and chat, announced at the Google I/O conference in May, is now available for public preview.
Vertex AI gives builders a full set of tools to help them tune, launch, and manage models in production. For example, it was the first enterprise-grade MLPaaS to offer Reinforcement Learning with Human Feedback in May. This service leverages human feedback to improve the accuracy of fine-tuned models trained with custom datasets.
Google also announced case studies and evidence of customers utilizing its generative AI platform. GA Telesis is using the PaLM model on Vertex AI to build a data extraction system that uses email orders to create quotes for customers automatically. GitLab's"Explain this Vulnerability" feature uses the Codey model on Vertex AI. This capability gives developers a natural language description of code flaws and suggestions for how to fix them.
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