OpenAI Deep Research
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OpenAI has done it once again!
At the beginning of February, OpenAI released a new feature in ChatGPT called "Deep Research" that allows AI to go through the internet and conduct multi-step research. This model has been developed to piece together large amounts of online information and use this information to complete complex research tasks. Without a doubt, OpenAI's Deep Research can do in 10 minutes, the work what a human takes several hours to do. In this blog, we would like to talk about how this model works, what it does, and other relevant information.
Deep Research acts as an intelligent agent that conducts its research independently. This means that this agent can look through the internet, analyze all the data found, and compile all the information from online sources to create very thorough reports. It can also perform asynchronous research, which means that it can start research on its own, continue the research while users do something else, and notify them when it's done.
Moreover, this model uses end-to-end reinforcement learning (E2E RL) to learn all the steps between the initial input and output on complex browsing and reasoning tasks. This makes the model plan its steps to find and put information together with real-time data.
Furthermore, it also means that this model can browse through text, images, PDFs, or whatever it can find on the internet, completely changing everything based on the new information found. Particularly, it can go through user-uploaded files and make use of Python tools for graph plotting and data visualization.
Note: This model is powered by an upcoming OpenAI version, the o3 model, which has been improved to handle extensive web browsing and data analysis tasks.
Like any other technology, OpenAI's Deep Research model has its limitations: