- Google Cloud add six new AI agents for data scientists, engineers and more
- Advanced analysis will become more accessible with the AI of natural language
- A solid database is equally important, but Google can help you migrate
Google Cloud has launched six new tools of artificial intelligence agents to help data engineers, data scientists, developers and commercial users who obtain even more productivity benefits.
Writing a “new era where the specialized agents of AI work autonomously and cooperatively to unlock ideas on scale and speed”, the managing director of Data Cloud, Yasmeen Ahmad, explained the benefits of a “unified, unified and native of AI” cloud on the connected tools when it comes to using AI.
In addition to new specialized agents, Google Cloud is also launching a series of API, tools and protocols, as well as updates to unify data.
Google Cloud launches even more AI agents
The first agent, for data engineers, is designed to automate complex data pipes by allowing engineers to describe tasks and then building and executing workflows autonomously. A separate key migration agent will simplify the migration of inherited databases such as MySQL to Splay, eliminating hours of tedious administrative work.
Data scientists will benefit from an agent who automatically performs exploratory data analysis, data cleaning, features engineering and ML predictions, offering step by step and collaborative comments, while commercial users and commercial analysts can use two separate agents designed to answer questions about data and interpret the code with visualizations and explanations, which means that non -technical users can perform advanced analysis.
Finally, Gemini Cli Github actions will automate applications, tests, reviews and implementation for developers.
“The true potential for the change of agent is done when developers not only use existing agents, but also extend them and connect them to their own intelligent systems, creating a broader network,” said Ahmad.
With its new agents, Google Cloud hopes to reduce the entry barrier in advanced data analysis “, you were[ing] The line between operational and analytical worlds. “
