Vertex AI
Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case.
Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.
Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
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Amazon Bedrock
Amazon Bedrock is a comprehensive service that streamlines the development and expansion of generative AI applications by offering access to a diverse range of high-performance foundation models (FMs) from top AI organizations, including AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon. Utilizing a unified API, developers have the opportunity to explore these models, personalize them through methods such as fine-tuning and Retrieval Augmented Generation (RAG), and build agents that can engage with various enterprise systems and data sources. As a serverless solution, Amazon Bedrock removes the complexities associated with infrastructure management, enabling the effortless incorporation of generative AI functionalities into applications while prioritizing security, privacy, and ethical AI practices. This service empowers developers to innovate rapidly, ultimately enhancing the capabilities of their applications and fostering a more dynamic tech ecosystem.
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UBOS
Unlock the potential to turn your innovative concepts into AI applications within moments. Our no-code/low-code platform empowers everyone, from seasoned developers to everyday business users, to craft cutting-edge AI-based applications in just 10 minutes. Effortlessly connect with APIs such as ChatGPT, Dall-E 2, and Codex from OpenAI, along with the ability to implement custom machine learning models. You can create tailored admin clients and CRUD functionalities, enabling efficient management of sales, inventory, contracts, and beyond. Develop interactive dashboards that convert data into insightful actions, driving innovation within your organization. Additionally, easily set up a chatbot to enhance customer support and create a truly omnichannel experience through various integrations. This comprehensive cloud platform harmonizes low-code/no-code tools with advanced technologies, ensuring your web applications are scalable, secure, and straightforward to oversee. Revolutionize your software development journey with our versatile no-code/low-code platform, which is ideal for both business users and skilled developers, paving the way for limitless possibilities. Moreover, the user-friendly interface ensures that anyone can get started quickly, making technology accessible to all.
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BentoML
Deploy your machine learning model in the cloud within minutes using a consolidated packaging format that supports both online and offline operations across various platforms. Experience a performance boost with throughput that is 100 times greater than traditional flask-based model servers, achieved through our innovative micro-batching technique. Provide exceptional prediction services that align seamlessly with DevOps practices and integrate effortlessly with widely-used infrastructure tools. The unified deployment format ensures high-performance model serving while incorporating best practices for DevOps. This service utilizes the BERT model, which has been trained with the TensorFlow framework to effectively gauge the sentiment of movie reviews. Our BentoML workflow eliminates the need for DevOps expertise, automating everything from prediction service registration to deployment and endpoint monitoring, all set up effortlessly for your team. This creates a robust environment for managing substantial ML workloads in production. Ensure that all models, deployments, and updates are easily accessible and maintain control over access through SSO, RBAC, client authentication, and detailed auditing logs, thereby enhancing both security and transparency within your operations. With these features, your machine learning deployment process becomes more efficient and manageable than ever before.
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