Google Colab, Google’s cloud-based notebook tool for coding, data science, and AI, is gaining a new “AI agent” tool, Data Science Agent, to help Colab users quickly clean data, visualize trends, and get insights on their uploaded data sets.
First announced at Google’s I/O developer conference early last year, Data Science Agent was initially launched as a standalone project. However, Google decided to integrate it into Colab with the goal of helping users access the agent directly from a Colab notebook, said Kathy Korevec, director of product at Google Labs, in an interview.
Data Science Agent is available for free as of this week in Colab, although Colab limits free users to a relatively low amount of computing. Google offers a range of paid Colab plans with higher limits starting at $9.99.
Data Science Agent is primarily aimed at data scientists and AI use cases, but the agent can also help find API anomalies, analyze customer data, and write SQL code. All users need to do is upload their data and ask the agent a question.
Data Science Agent uses Google’s Gemini 2.0 AI model family on the backend, along with “reasoning” tools to help with feature engineering and data cleaning tasks. Korevec told TechCrunch that Google is constantly improving the agent and using techniques including reinforcement learning, as well as integrating user suggestions, to enhance Data Science Agent’s performance.
Data Science Agent currently only supports CSV, JSON, or .txt files under 1GB in size. It can analyze about 120,000 tokens in a single prompt, which works out to about 480,000 words.
Korevec said that Data Science Agent may come to additional dev-focused Google apps and services in the future.
“We’re scratching the surface of what people can do here,” she said. “Because it’s an agent, we can integrate it into a bunch of different tools, and I don’t necessarily want to force people who are shy about looking at the code to go to Colab.”