With Generative AI Ops, companies have access to a team of experts to support them at every stage of transforming generative AI prototypes into production workloads.
Google Cloud has the revolutionary Generative AI Ops Services were introduced. These new services are designed to help companies transition from AI prototypes to fully functional production workloads.
In recent years, generative AI has made significant progress, but this rapid progress has led to a shortage of skilled workers. Given the increasing demand for AI solutions and companies' interest in these technologies, the need for experts in this field is clearer than ever.
What does Generative AI Ops offer?
Google Cloud Consulting and its partners have developed a customized solution for this challenge with Generative AI Ops. Companies gain access to an experienced team that guides them step by step through the implementation of their AI projects.
Generative AI Ops offers not only expertise, but also an optimized technological infrastructure for AI development. The service includes a wide range of services that are essential for the creation and optimization of AI models.
The main phases covered by Generative AI Ops are rapid engineering, design and optimization. These phases ensure that the developed AI models deliver precise and high-quality results.
Advanced techniques from Generative AI Ops
Generative AI Ops uses advanced methods such as ReAct, RAG and Thought Chaining that enable advanced production and reuse. Google emphasizes that different AI models have specific routing structure requirements and stresses the importance of choosing the right techniques for each model.
Google also offers support with performance and system evaluation. Google Cloud Consulting helps companies to develop customized evaluation frameworks for their AI applications.
Comprehensive support for companies
Google's expertise enables companies to optimize their AI system architectures and model selection processes, reducing delays and costs. Google also provides monitoring and observation capabilities to minimize errors and undesirable outcomes.
Another advantage is support for the integration and testing of AI applications. This ensures that AI models are efficiently integrated into business processes. This includes setting up cloud environments for hosting AI models, developing APIs for model management and carrying out load tests to evaluate model performance.
With Generative AI Ops, companies can exploit the full potential of generative AI and significantly increase their innovative strength. This comprehensive support makes the difference in the successful implementation and use of AI in production.
