Google AI issued new 5 new AI / Developers platforms

Google Cloud has just been revealed to five special agents for the development of developing engineering work – to reduce the hand attempt, accelerate the analysis, and reduce the barrier to advanced data and Code Auto Auto Auto Automation. Each agent deals with a distinct engineering challenge, from the management of the GitTub data pipelines. Here's a detailed look at what these people do, the technical diagnosis, and how they get into today's cloudy well – native and indigenous.

1. Data agent in Brequery

Brochury data brings the default language language in the creation of data pipeline and administration within the GROOQIORY'S STAGEMENT. This significer is addressed to the data engineer and analysts who want to focus on understanding rather than smell boatplate data pipes.

Key Skills:

• Default data installation: You create and manage data pipes from sources such as Google's storage that has simple promotion, reducing the need for ETL text documents.
• Zero data quality: Maintains data quality and flexibility in AI test
• To prepare for data assisted by AI: They do the defaults of data cleaning, Metadata production, and evolution of Schema, supporting both formal and informal information.
• Visible status: Engineers can clearly describe the pipes in natural language, and the agent produced and increased the required SQL or Dafazi.

Technical Basis:

Designed in Gemini, agent for the purpose of the recognition and the code of code, with a strong integration of the Grequery information engine for details and data data to Metadata data.

2. The Agent of Notebook (Business NoteBooklm)

The Writing Book Agent, Available as a Business Aterookborlm, Supercharges of Biovobooks have booklets of EM-TOD-END

Key Skills:

• Ed & Engineering feature: Runs to analyzing data analysis (EDA) and features of features with Resourvational Promplow
• ML-Sexual prediction: Produce predictions and models directly within the booklet, reduce the boilerplate code and the order of the booklet.
• The foundations of all information Organize and synchronize research, documents, and redesigned datasets, active types of groups.
• Synthesis content: It summarizes the findings, producing FAQs, and can produce audio summaries to use asynchronous.

Technical Basis:

The NoteBooklm business is different from the GeneralBookll Product – including in large booklets, using the control based on early scope, and is controlled by the Enterprise Security and partnership.

3. A relief of the code that is looking at

The look at the responsible code embark on the productive AI in the ABely and Platform test, making analytics available to non-users without delay without delay without technology without expertise.

Key Skills:

• Question Language Questions: Users ask questions in clear English and receive seeing things, the Python code, or active charts like issuing.
• Custom View & Appearance: It produces lookml options and JSON formatting from elections from prompts, accelerates Dashboard development.
• Active insight: It explains how to analyze the way and raise tracking questions, to promote trust and access.
• Awareness of Data Code: Uses the Semantic Semantic layer to ensure accurate questions and are appropriate for business descriptions.

Technical Basis:

Enabled by Gemino and Aleemer's Expend the API, the assistant interpreting the Natural language have been prepared, SQL, and visible code, to close groups between business users and analyzes.

4. Database Migration Agent

The Database Migration Agent (DMS with Gemini Accent) simplify and accelerate the transformation of estate information (eg.

Key Skills:

• SCHAME SCHEMA & Code: Reviews and transforming stored procedures, functions, and schemas in landfire format, reducing the manual effort and the risk of immigration.
• Time to rest forth: LEVESS REPPICATION SPRUPTICE based on zero Dowthing during the migration.
• Descriptive Migration: It provides a stranger in a stranger along the legacy and the target code, with detailed Development descriptions.
• Unemployed operation: You are completely controlled by Google Cloud, without the provision of infrastructure required.

Technical Basis:

An agent uses Gemini to understand and interpret Database Details, verify the effects of migration, and direct users by each process of process.

5. Gimbub Agent (Gemini Github Actions)

Gemino Gitkuub Agent Agent Agent, Dear Agent Ai Ai Ai Ai Actential Gitcharges Automatic Gitcharges.

Key Skills:

• Try Trech: Automatic labels, prioritize, and GitTubs are GitTubs based on content and project context.
• Application Review: The code code review, suggests improvement, and provides immediate feedback, reducing the responsibilities of the code review.
• Collaboration involving Engineers can convey functions by marking the agent in the news or prs (eg, “Write exams of this bug”).
• Working for Operations: Vessels with default travel transaction but completely open with the resource and stolen with specific group needs.

Technical Basis:

Designed in Gemini Cli, agent Running Asynchronous responding to GitUB events, using the context of the accurate Acts, and is directly meets Gitub Atem Piplines.

Summary Temple: New Agents in AI new developers

Summary

These agents represent the important jumping to him The Development ToolPeriods, labor-active activities treated by AI, advancements that release to the removal and receipt of business. They reduce the technical for analytics, migration, and cooperation, during storage (or boost) ceiling of Cloud-Scale Data and Code.

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