Introduction to Deep Research

Summary

In this video, Mark from OpenAI introduces the groundbreaking 'Deep Research' capability, an advanced multi-step web browsing model designed to assist with knowledge work. Deep Research enables agents to autonomously search, synthesize, and reason through content, generating comprehensive, fully cited reports. With applications spanning from market research to personal product buying decisions, this feature revolutionizes tasks that would otherwise require significant manual effort. The technology is a key step in OpenAI's AGI roadmap, enabling agents to tackle increasingly complex challenges. Deep Research is launching on Pro, with plans to expand to other platforms soon.

Takeaways

• 😀 Deep Research is a new capability launched by OpenAI that performs multi-step research on the internet, synthesizing content and reasoning about the information it uncovers.
• 🌐 The Deep Research model removes latency constraints, meaning it can take longer (up to 30 minutes) to provide answers, allowing it to perform more autonomous and complex tasks.
• 📄 The output from Deep Research is presented as a comprehensive, fully cited research paper, similar to something an expert or analyst would produce.
• 💼 Deep Research can be used for various applications such as knowledge work, market research, and even personal tasks like finding specific items or preparing presentation content.
• 🔍 One of the key features of Deep Research is its ability to browse the web, access different sources (including PDFs, images, and tables), and synthesize the gathered information.
• 🧑‍💻 Users can provide a query to Deep Research, which then clarifies requirements and begins searching, with the model adjusting its plan based on the new information it discovers.
• 🏢 Deep Research is initially launching on Pro, with plans to roll it out to Plus, Team, Education, and Enterprise tiers in the future.
• 🤖 The model is powered by a fine-tuned version of OpenAI's soon-to-be-released O3 reasoning model, trained using end-to-end reinforcement learning for browsing and reasoning tasks.
• 📈 In tests, Deep Research reached new highs in accuracy on expert-level tasks, completing complex tasks that would typically take humans many hours.
• 🎿 Users can apply Deep Research to personal use cases, such as researching products to buy, as demonstrated in the example where Deep Research was used to help purchase skis for a vacation.
• 🧠 OpenAI's ultimate goal is to create an AGI that can autonomously uncover and discover new knowledge, with Deep Research serving as a foundational step toward that vision.

Q & A

What is Deep Research, and what makes it unique?

Deep Research is a new feature developed by OpenAI that allows the model to browse the web, analyze content, and generate synthesized reports based on the information found. Its unique aspect is its ability to perform multi-step reasoning over extended periods (up to 30 minutes), helping solve complex tasks that require deeper analysis.

How does Deep Research help with tasks like market research?

Deep Research can automate tasks like market research by analyzing large amounts of data, such as market penetration and product adoption rates, saving users hours of manual effort. It synthesizes relevant findings and presents them in an organized format for easy decision-making.

What are the potential use cases for Deep Research?

Deep Research can be used for various applications, including academic research, market research, product analysis, and even personal inquiries like finding specific products or understanding niche topics. It allows users to gather information without spending significant time on manual research.

How does Deep Research improve over typical search engine results?

While search engines provide a list of search results, Deep Research goes further by actively browsing, analyzing, and synthesizing information from multiple sources, then delivering a comprehensive report with structured findings and citations, much like a human expert would.

What technology powers Deep Research?

Deep Research is built on OpenAI’s O3 reasoning model, which has been fine-tuned to improve browsing and reasoning capabilities. It uses end-to-end reinforcement learning to efficiently browse the web and provide valuable insights.

How does Deep Research handle complex tasks that require multiple steps?

Deep Research is designed to work autonomously over extended periods. It can tackle multi-step tasks by continuously gathering data, refining its understanding, and synthesizing a report with progressively more accurate insights. Tasks can take between 5 to 30 minutes to complete.

Can users interact with Deep Research to refine their searches?

Yes, users can interact with Deep Research by asking clarifying questions and adjusting the scope of the research. The model adapts based on the feedback provided, ensuring the final output is aligned with the user’s needs.

What kind of data sources does Deep Research use?

Deep Research can pull data from various sources, including web pages, articles, images, tables, and PDFs. It processes and synthesizes this information to create a structured report that answers specific research queries.

How does Deep Research align with OpenAI's AGI roadmap?

Deep Research is part of OpenAI's AGI (Artificial General Intelligence) roadmap because it represents a step towards more autonomous AI agents capable of handling long, complex tasks. OpenAI believes that deep research agents, which can think longer and more independently, are key to advancing AGI.

When will Deep Research be available to more users?

Deep Research is launching today for Pro users and will soon be available on desktop and mobile platforms. OpenAI plans to expand access across more user tiers, including Education and Enterprise, in the near future.