What It Is and How It Functions

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What It Is and How It Functions



Deep research in ChatGPT

HIGHLIGHTS

OpenAI Unveils Deep Research Feature in ChatGPT

Deep research is tailored for professionals in finance, science, policy, and engineering who need accurate information.

This innovative tool can also assist everyday users with tasks such as product comparisons when shopping.

In a significant move, OpenAI has rolled out a groundbreaking feature in ChatGPT known as ‘deep research.’ This advanced functionality is specifically crafted to manage intricate, multi-layered online research tasks, analyzing and condensing information from numerous sources in a much quicker time frame than any human could achieve. Read on for an in-depth look at OpenAI’s cutting-edge research agent and how it can benefit you.

Understanding Deep Research in ChatGPT

Deep research represents the latest innovation from OpenAI as a specialized AI agent that autonomously performs comprehensive research tailored to user inquiries. As stated by OpenAI, “It achieves in mere minutes what would require hours for an individual.” This feature leverages an optimization of OpenAI’s o3 model, tailored specifically for web browsing and data analysis tasks.

Differing significantly from standard responses provided by ChatGPT, deep research delves into extensive datasets, which include a variety of formats such as text, images, and PDFs readily available on the internet. This capability enables it to modify its analytical approach based on the data it unearths, transforming it into an indispensable resource for users seeking deep insights and understanding.

OpenAI denotes that deep research has been fundamentally designed for professionals in finance, scientific fields, public policy, and engineering domains who require precise and trustworthy information. Yet, it’s equally valuable for everyday users engaging in activities like comparing products prior to making a purchase.

One of the remarkable attributes of deep research is its capacity to uncover niche and often non-apparent information that may reside across various hidden sources. As OpenAI articulated in its blog post, “Every output generated is meticulously documented, complete with clear citations and a logical summary of its reasoning, facilitating ease of reference and verification.”

“Deep research was equipped through end-to-end reinforcement learning, focusing on complex browsing and reasoning challenges across diverse fields. This rigorous training has enabled it to conceptualize and execute multi-step pathways to gather the information needed while adapting in real-time as new data emerges,” the organization emphasized.

How to Access Deep Research Feature

To utilize the deep research capability within ChatGPT, users simply need to select it in the messaging interface. After posing a query, which could range from a competitive analysis of streaming services to a tailored report about the most suitable commuter bicycles, the tool springs into action.

A sidebar interface will become visible, displaying the methodologies and resources employed during the research process. Users can expect the entire process to take between 5 to 30 minutes, culminating in the generation of a detailed report. OpenAI has also mentioned that forthcoming updates will facilitate the inclusion of embedded images, data visualizations, and various analytical outputs to enhance the overall clarity of information presented.

Recognizing its current limitations, OpenAI has acknowledged that deep research is not free from flaws. “It may occasionally generate unverified facts or draw incorrect conclusions,” the company concedes. However, it assures users that these inaccuracies occur with reduced frequency compared to earlier models of ChatGPT.

Additional reading: OpenAI Faces Legal Challenges in India: Here’s the Background

Availability of Deep Research

Currently, the deep research facility is exclusive to ChatGPT Pro users, restricted to 100 queries monthly. OpenAI intends to extend access to Plus and Team users in the near future, followed by Enterprise clients. Moreover, they are also working on a more efficient and cost-effective version of deep research.

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