Google Deep Research: AI Google to help with research

Google has just announced a new artificial intelligence (AI) tool called Deep Research. This tool allows users to use Gemini’s AI Bots to perform searches on the web and compile detailed reports based on their findings. This innovation is part of Google’s strategy in developing AI agents capable of performing complex tasks for users. With Google Deep Research, users can focus more on decision making and analysis rather than spending time on manual research.

What is Deep Research?

Deep Research is an AI feature designed to simplify the research process, especially for professionals, academics, and business users. With this tool, users can:

1. Develop a research plan: Gemini will create a multi-step research plan based on the topic the user requests. This plan may include identification of key information sources, specific search steps, and time estimates for completing research.
2. digging in-depth information: Gemini started his research by looking for pieces of interesting information on the web, verifying the accuracy of the data, and conducting related searches repeatedly to ensure the completeness of the data.
3. Prepare a detailed report: The end result is a report that includes the main findings complete with links to the information source website, designed to be easy to read and analyze.

Currently, Deep Research Only available in English and accessible to customers Gemini Advanced. Google suggests that expansion into other languages is in the planning stage.

Main Features of Deep Research

• Customizable research plan: Users can edit or approve the research plan prepared by Gemini. This feature provides flexibility for users to adapt the research process to their specific needs.
• Interactive Report: You can ask Gemini to expand certain parts of the report, add additional context, or customize it as needed.
• Integration with Google Docs: Research results can be exported directly to Google Docs for further editing, team collaboration, or documentation.

How to use Deep Research?

To use this feature, the steps are:

1. Gemini access: Go to the Gemini platform and change the dropdown model to “Gemini 1.5 Pro with Deep Research.”
2. Specify the topic: Prompt research topics to Gemini. For example, you can ask Gemini to research the impact of AI technology on global education.
3. Review the research plan: Check and adjust the research plan made by AI. You can add specific focus areas or exclude some irrelevant sources.
4. Get reports: Wait for the report to finish, then review and adjust as needed. You can also request additional reports based on previous findings.

Deep Research Comparison with Perplexity Pages

real usage example

Academic Studies: Researchers can use Deep Research to explore related literature in a short time, saving the time usually required for manual searches.

Business Strategy: Companies can take advantage of this feature to compile market reports, analyze industry trends, or identify new business opportunities.

Creative Content: Writers and journalists may ask Gemini to draw up an article framework or collect relevant statistical data for their work.

Why is Deep Research Important?

In the information age that is full of data, Deep Research provide solutions to the following challenges:

1. Time efficiency: AI can complete research which usually takes hours in just a matter of minutes, giving users more time for analysis.
2. Information accuracy: Gemini ensures that the information collected comes from reliable sources, reducing the risk of dissemination of invalid information.
3. Ease of use: Integration with Google Docs allows users to directly use research results without the need for additional conversions, reducing technical barriers.
4. Scalability: With in-depth research skills, Deep Research is suitable for various scale needs, from individuals to large organizations.

Other innovations in Gemini 2.0

Announcement Deep Research is part of the launch Gemini 2.0, the latest model of Google that marks a new era of Agent AI. In addition to Deep Research, Google also introduced Gemini Flash 2.0, a faster version of chatbot and available for developers.

What is Agent AI?

Agent AI is an AI system designed to perform tasks independently. Examples of applying agent AI are:

• Deep Research: Conduct complex research with structured results.
• chatbot: Helping users with real-time information, including answering questions related to specific data.
• Automation: Running complex business processes such as financial data analysis, logistics management, or project management.

Google is not the only company to explore AI agents. Other companies such as OpenAI, Microsoft, and even small startups also continue to develop similar technologies for various needs, from personalization to business optimization.

Deep Research Challenges and Future

current limitations

1. Language availability: only supports English, which limits accessibility for non-English users.
2. limited access: This feature is only available to customers Gemini Advanced, so that it cannot be widely accessed by the general public.
3. Dependence on online sources: The accuracy of the report depends on the quality of the information source on the web. Bias or incomplete information can affect research results.

future potential

• Improved language support: Google can expand language support to reach more users around the world, including Indonesian.
• Advanced Research Features: Includes deeper data analysis, graphic visualization, and trend prediction based on historical data.
• More affordable price: Open access to a wider segment of users, including students and MSMEs.
• Collaboration with academic resources: Integration with scientific journals and education databases to improve the accuracy and relevance of reports.

Conclusion

Google’s Deep Research is a big step in utilizing AI for research and productivity. With advanced features such as multi-step research plans, interactive reports, and integration with Google Docs, this tool is an attractive solution for professional users. However, further development is needed to make it more inclusive and user-friendly. In addition, cross-sectoral collaboration can open up new opportunities in the application of this technology, ensuring the benefits can be felt by the wider community in various fields.