OpenAI Deep Research vs GPT-4o: Check Its Feature, Compatibilities and Accuracy Level

In -depth research is a pioneering function of ChatGPT. It aims to conduct multi -step research on the Internet and condense the time for human work into a few minutes. It uses advanced reasoning to comprehensively information, providing a comprehensive report similar to research analysts.

What is in -depth research?

In -depth research is a kind of agency ability in ChatGPT:

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• Perform thorough online research
• Analysis and comprehensive information about hundreds of sources
• Generate detailed, well -checked reports

It uses the upcoming OpenAI O3 model for operation. This model is optimized for web browsing and data analysis, which can explain a lot of text, images and PDFS online.

What are the main characteristics of in -depth research?

• Acting ability: Independent operation to complete the research tasks.
• Multiple -step research: find, analyze and comprehensive online resources.
• Supported by the Openai O3 model: optimized web browsing and data analysis.
• Reasoning and analysis: search, interpretation, and analysis of a large number of texts, images and PDFs.
• Documents and citations: Provide a clear process of reference and abstract.

In-depth research and GPT-4O: Comprehensive comparison

aspect	In -depth research	GPT-4O
definition	Use the verified source of the manual to study in -depth research.	AI -driven instant response is based on a large number of data sets.
Purpose	In -depth research task	Real -time dialogue
speed	Slow-need time to collect data, analyze and verify.	Super fast-generating structured response within a few seconds.
accuracy	Very high-based on peer review, factual inspection and cross-reference.	Gao-is usually reliable, but depends on training data and real-time updates.
Depth	Broadly-covering fine differences, historical background and expert views.	Good-providing abstracts and insights, but may lack a deep context.
Source reliability	Trust-use academic journals, government reports and expert opinions.	Variable-after training by different data sets; real-time resources may lack credibility inspection.
Factual inspection	Manual and strict-need to verify from multiple sources.	Automation-can be searched through the Internet for factual examination, but it is not always lost.
Prejudice and objectivity	Balance-can minimize it by consulting various views.	Potential prejudice-inheritance of prejudice from training data and Internet sources.
Best	Academic research, decision -making, investigating news, comprehensive, verified analysis	Quick view, brainstorming, general knowledge, summary, multi -mode, fast answer
interactive	Low-Search and synthesis of self-driven.	Gao-dynamic participation and interactive explanation.
Creativeness and innovation	Human leaders-rely on professional knowledge, intuition and analysis and reasoning.	AI Assistance-An idea, but lack of human intuition.
Cost and accessible	Excessive-need to subscribe, expert consultation or institutional access.	Affordable-free/basic version, and high-quality version of high-quality features.
Ease of use	Complex-requires research skills and professional knowledge.	Users are friendly-simple, intuitive and available for everyone to access.

The final judgment:

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Use in -depth research to conduct high -risk reports, academic research and policy decisions. Use GPT-4O to make fast views, ideas and abstracts-but always verify accuracy!

Why do you need to study in -depth research, rather than other chat GPT?

Key benefits:

• Efficiency: Complete research tasks within 5 to 30 minutes
• Reliability: Provide the output and references of comprehensive records
• Multi -functional: For finance, science, policies and engineering professionals, and personalized consumers are useful

app:

• Competitive analysis
• Policy introduction
• Market research
• Personalized product recommendation

Source: Canva

What are the purpose and benefits of in -depth research?

The purpose and benefits of in -depth research are:

Target user	benefit
Knowledge worker	Thorough, precise and reliable research
Shopkeeper	Personalized advice
Research analyst	Clearly referenced comprehensive report

• Integrated knowledge: Promote the creation of new knowledge by comprehensive data.
• Save time: accelerate complex and time -consuming network research.

How does it work?

Step process:

• Start inquiries: Select “In -depth Research” in ChatGPT, and then enter the query.

• Information collection: model search and compile information from multiple sources.

• Analysis and synthesis: Inconsistent power is integrated into a comprehensive report.

• Report Delivery: A detailed report is provided, and a reference and summary are provided.

For example:

• Assessing stream platform
• Detailed report on market trends
• Suggestions for high value purchase

In -depth research is an advanced AI system that uses end -to -end reinforcement learning to train and train complex browsing and reasoning tasks in various fields.

It is:

• Plan and execute multi -step query to find related data.
• Tour back and adapt to real -time information when needed.
• Browse files for extraction and analysis of content extracted.
• Generate and embed visual data, such as graphics and images.
• Quote specific sources to improve credibility.

Data source: docomative.ai

Critical function

Detailed ability of in -depth research:

feature	describe
Multi -step reasoning	Find data through the plan search strategy.
Real -time adaptability	Adjust the search based on the change input.
User file browsing	Analyze and extract related information from the file.
Picture and image generation	Create and embed visual representation.
Source reference	Refer to specific sentences to ensure credibility.

Due to its strict training, in -depth research has achieved the latest performance in various public assessments on real world issues.

getting Started

• Access: Now you can use Pro users, and will soon be expanded to Plus and team plans.
• Interface: It is easy to use the side fence to track progress and source.
• Notice: Reporting will be reminded when you are ready.

In -depth research represents our important step in the AGI vision, and can generate new knowledge through comprehensive information.

Human last exam

Recently conducted in -depth research on human beings. This is an expert assessment involving more than 100 subjects, including linguistics, rocket science, ecology and classics. It has reached a record of 26.6 % accuracy, which is greatly better than other AI models.

Comparison

Model	accuracy(%)
GPT-4O	3.3
GROK-2	3.8
Claude 3.5 Fourteen Elements Poems	4.3
Gemini thinking	6.2
Openai O1	9.1
Deepseek-R1*	9.4
Openai O3-mini (middle)*	10.5
Openai O3-mini (high)*	13.0
Openai in -depth research	26.6

Note: Some models are evaluated on only text, and in -depth research and use of browsing and Python tools.

In -depth research shows that human beings seeks professional information, thereby realizing the substantial improvement of chemistry, humanities, social sciences and mathematics.

GAIA benchmark performance

In -depth research sets a new and most advanced (SOTA) score for GAIA (General AI Assistant). The public benchmark is to evaluate AI’s real reasoning and multi -mode tasks.

Gaia score

Model	1 level	Level 2	Level 3	Average
Former SOTA	67.92	67.44	42.31	63.64
In -depth research (via@1)	74.29	69.06	47.6	67.36
In -depth research (Cons@64)	78.66	73.21	58.03	72.57

These scores reflect the ability to increase difficulty levels through high -level reasoning, network browsing and tool usage capabilities.

Expert -level task

In the internal evaluation, the field experts discovered complexity, the in -depth research hours of manual research, and greatly reduced their efforts to high -defect tasks.

Source: Openai

What are the limitations of in -depth research?

Despite impressive abilities, in -depth research still faces some challenges:

• Facts: These may have incorrect facts, although the speed is lower than other AI models.
• Credit assessment: Sometimes try to distinguish the source of authority from unreliable information.
• Confidential calibration: cannot be accurately conveyed uncertainty.
• Formulating problem: Small errors in the report and reference when publishing.
• Treatment delay: Some tasks may take longer to execute.

In the future, improvement will focus on improving accuracy, reliability and efficiency through iteration updates.

Access and available

At present, in -depth research is highly calculated. Its availability is launched in stages:

Access layer

User category	Available
Professional user	Check up to 100 inquiries per month (initial release)
Plus & Team user	Launched in the next stage
Corporate user	coming soon
Users of Britain, Switzerland, EEA	Developed access

Fast, more cost -effective versions have high query restrictions, and will soon be released to all paid users.

What is the future development of in -depth research?

Short -term plan

• Mobile and desktop expansion: In -depth research on mobile and desktop applications of ChatGPT.
• Integration with professional data sources: Expansion beyond open Web browsing to expansion based on subscribing or internal resources.

Long -term vision

• Asynchronous research and execution: in -depth research with the operator (another AI tool) for the implementation of the task of the real world.
• Enhanced AI proxy function: Make ChatGPT automatically executes increasingly complicated tasks.

in conclusion

In -depth research represents the great progress of AI -driven browsing, reasoning and research. Although it is still developing, it has an automated expert survey that provides high -quality response and the potential for improving decision -making is undeniable. In the future, improvement will further improve accuracy, reliability and efficiency, making it a precious tool for researchers, professionals and enterprises.

Source: https://dinhtienhoang.edu.vn
Category: Optical Illusion