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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Windsurf Editor
Windsurf is a cutting-edge IDE designed for developers to maintain focus and productivity through AI-driven assistance. At the heart of the platform is Cascade, an intelligent agent that not only fixes bugs and errors but also anticipates potential issues before they arise. With built-in features for real-time code previews, automatic linting, and seamless integrations with popular tools like GitHub and Slack, Windsurf streamlines the development process. Developers can also benefit from memory tracking, which helps Cascade recall past work, and smart suggestions that enhance code optimization. Windsurf’s unique capabilities ensure that developers can work faster and smarter, reducing onboarding time and accelerating project delivery.
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Qwen3-Coder
Qwen3-Coder is a versatile coding model that comes in various sizes, prominently featuring the 480B-parameter Mixture-of-Experts version with 35B active parameters, which naturally accommodates 256K-token contexts that can be extended to 1M tokens. This model achieves impressive performance that rivals Claude Sonnet 4, having undergone pre-training on 7.5 trillion tokens, with 70% of that being code, and utilizing synthetic data refined through Qwen2.5-Coder to enhance both coding skills and overall capabilities. Furthermore, the model benefits from post-training techniques that leverage extensive, execution-guided reinforcement learning, which facilitates the generation of diverse test cases across 20,000 parallel environments, thereby excelling in multi-turn software engineering tasks such as SWE-Bench Verified without needing test-time scaling. In addition to the model itself, the open-source Qwen Code CLI, derived from Gemini Code, empowers users to deploy Qwen3-Coder in dynamic workflows with tailored prompts and function calling protocols, while also offering smooth integration with Node.js, OpenAI SDKs, and environment variables. This comprehensive ecosystem supports developers in optimizing their coding projects effectively and efficiently.
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Posit
Posit delivers a comprehensive ecosystem for modern data science, uniting open-source technologies with enterprise-grade collaboration and deployment tools. Positron, its free data-science IDE, blends the immediacy of a console with powerful debugging, editing, and production capabilities for Python and R developers. Posit’s suite of products allows organizations to securely host analytical content, automate reporting, and operationalize models with confidence. With strong support for open-source tooling, the company enables teams to build on transparent, extensible technologies they can fully trust. Cloud solutions simplify how users store, access, and scale their projects while maintaining reproducibility and governance. Customer success stories from organizations like Dow, PING, and the City of Reykjavík highlight the impact of Posit-powered applications in real-world environments. Posit also fosters a thriving community, offering resources, events, champions programs, and extensive documentation. Built by data scientists for data scientists, Posit helps teams adopt open-source data science practices at enterprise scale.
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