Published on: March 18, 2025 / update from: March 18, 2025 - Author: Konrad Wolfenstein
Vertex AI: Google's comprehensive AI platform in change-Image: Xpert.digital
Future strategy of Google: The growing role of Vertex Ai
Integration and progress: The strategy behind Vertex Ai
Vertex AI has established itself as a central pillar in Google's AI strategy and continuously develops. The platform introduced in 2021 combines advanced technologies and offers developers like companies powerful tools for AI development. At a time when Google operates various AI offers in parallel, a strategic development is emerging that indicates more integration or convergence in these platforms.
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Basics and range of functions of Vertex AI
Vertex AI is Google's comprehensive, cloud-based AI platform, which is accessible via the Google Cloud Platform. It combines the most advanced technologies of Google Cloud ML Engine and Automl in a single, coherent environment. This integration enables developers and data scientists to develop and implement high-quality ML models regardless of their level of experience.
The platform offers access to over 40 proprietary models and more than 80 open source and third-party models via the so-called “Model Garden”. Particularly noteworthy is the access to Google's Gemini models that have multimodal skills and can process various input types such as text, video, code, audio or images. This versatility makes Vertex AI a powerful solution for complex AI tasks.
At the center of Vertex AI is an innovative development environment that fundamentally simplifies the collaborative work on AI projects. The platform offers fully managed notebooks that enable teams to work together on ML models and to exchange knowledge in real time. By seamlessly linking these interactive notebooks with AI pipelines, workflows can be made efficiently.
MLOPS functionalities and technical architecture
The MLOPS functionalities of Vertex AI set new standards in industrial ML development. The platform offers continuous pipeline for continuous integration and deployment, automated workflow orchestration and comprehensive model monitoring. These functions enable companies to efficiently manage, monitor and optimize their ML models.
The technical architecture of Vertex AI supports both Automl approaches for fast development cycles and custom training for specialized requirements. Automl automates critical processes such as model selection, hyperparameter optimization and model validation, while customer training offers maximum flexibility in the development of specialized ML solutions.
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Differences between Google Ai and Vertex ai
Google currently operates several AI platforms in parallel, including Google Ai Studio and Vertex AI. This separation is not a random decision, but the result of a strategic focus on various target groups and applications.
The differences between these two platforms are clear and are shown in different areas: While Google Ai Studio provides a rather limited range of Gemini models, Vertex AI includes a broader range of model, including Gemini 1.0 Ultra and Ultra Vision. Google AI Studio users can register with a simple Google account and use the platform with an API key. In comparison, Vertex AI requires a Google Cloud account that is bound to specific terms of use and billing models, and requires a Google Cloud service account for authentication. Google AI Studio user interface serves as a test field, while Vertex AI Studio is available as a professional tool for corporate applications. The supported functions also differ significantly: Google AI Studio does not offer enterprise functions or MLOPS integration, while Vertex AI provides comprehensive enterprise functions such as customer encryption key, virtual private clouds, data location control and access transparency as well as complete MLOPS functions. This clear differentiation shows that Google AI Studio is primarily aimed at developers and technically experienced users who want to experiment and develop applications with Google's AI models. On the other hand, Vertex AI is specially tailored to the needs of companies and professional developers who want to develop and implement AI solutions on a large scale.
Summarized:
- These differences show that Google Ai Studio is more likely to be developed for developers and technically versed users who want to experiment with Google's AI models and develop their own applications. The platform acts as a workshop for AI developers and offers extensive options for interaction with the Gemini models.
- Vertex AI, on the other hand, is aimed at companies and professional developers who want to develop and provide AI solutions on the company scale. The platform offers comprehensive enterprise functions such as customer encryption keys, virtual private clouds, data location control and access transparency.
Migration and integration between the platforms
Google offers clear migration paths from Google Ai to Vertex AI, which indicates a possible future consolidation of the platforms. The migration includes various steps:
- Setup of a Google Cloud account (if not yet available)
- Activation of the required APIs for Vertex AI
- Migration of prompt from Google Ai Studio to Vertex Ai Studio
- Upload training data to a cloud storage bucket for use to Vertex Ai
- Adaptation of the code for the use of the Vertex Ai Gemini API instead of the Google Ai Gemini Api
For developers who are already working with Google AI, Google offers detailed instructions and code examples for migration. This facilitates the transition between the platforms and enables developers to use the extended functions of Vertex AI without having to start from zero.
Interestingly, there are also solutions that enable parallel use of both platforms. A YouTube video explains how to seamlessly switch between Google Ai Studio and Vertex Ai with the new Google Gen AI SDK for Python. This indicates that Google recognizes the various entry points in its AI technologies and wants to offer flexibility for developers.
Convergence and future development
The development of Vertex AI is an ongoing process that benefits from Google's continuous innovation in the field of artificial intelligence. The platform is constantly being expanded to include new functions and improvements that meet the changing requirements of AI development.
Despite the current separation between Google Ai Studio and Vertex AI, there are signs of possible convergence or at least a closer integration of these platforms in the future. The repeated migration “from Gemini in Google Ai to Vertex Ai” indicates that Google is actively working on the further development of its AI infrastructure.
In the long term, we could see closer integration or convergence of these platforms, especially as part of the further development of Vertex AI and the progressive integration of AI functions into the entire Google ecosystem. This development would enable Google to use its resources more effectively and to offer a more consistent user experience across various AI offers.
Future developments in Vertex AI promise even more powerful Automl functions, expanded MLOPS capacities and increased support for Edge Computing. These innovations will enable companies to integrate AI even deeper into their business processes and to draw a greater benefit from their data.
Google's AI platforms in comparison: solutions for developers and companies
Vertex AI has established itself as a central pillar in Google's AI strategy and continuously develops. The platform combines advanced technologies and offers developers like companies powerful tools for AI development.
The currently operated platforms Google Ai Studio and Vertex AI meet different needs and are aimed at different target groups. While Google AI Studio enables low-threshold entry into AI development, Vertex AI offers comprehensive enterprise functions and MLOPS capacities for professional use.
However, the clear migration paths and the increasing integration between the platforms indicate a possible future convergence. This development would enable Google to offer a more consistent and powerful AI infrastructure that is suitable for both beginners as well as for professional developers and companies.
In the fast-moving world of AI technology, it remains to be seen how these platforms will develop. But one thing is certain: Google focuses on its AI technologies both in developer support and corporate solutions in order to take a leading position in the competitive market for AI solutions.
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