OpenAI’s Deep Research: Unexpected Game Changer!

@key2this says:

Nice! We need more generated trash papers to spam reviewers.

@wolpumba4099 says:

*Deep Research from OpenAI: A New AI Research Analyst*

* *0:00:00** Introduction:* Deep Research is presented as an AI-powered research analyst capable of aiding in complex decision-making, like buying a new car or researching a company. It works in tens of minutes.
* *0:00:41** Key Difference:* Unlike simple question-answering AI, Deep Research consults hundreds of online sources, synthesizes information, and provides opinionated reports with conclusions.
* *0:01:12** Reasoning and Synthesis:* The tool not only fetches data but also reasons and synthesizes, offering a more comprehensive analysis.
* *0:01:25** Example Prompt:* The video mentions asking about changes in the retail industry, though the result isn’t shown.
* *0:02:01** Website Examples:* Deep Research’s website showcases examples, including one on user experience design, where the AI cites actual studies, addressing concerns about AI hallucination.
* *0:02:51** Community Examples* Three user reported use-cases were explored.
* *0:03:02** Complex Tax Situation:* Deep Research provided a personalized and exhaustive report for a complex US exit tax scenario, surpassing the results from two human accountants.
* *0:03:27** AI Impact on Graphics Card Sales:* An analysis of how AI will affect graphics card sales was deemed excellent in its research, but the conclusion was considered vague.
* *0:04:18** Daily News Briefing:* A user successfully created a tailored daily news briefing, specifying location, interests, and biases to avoid, demonstrating AI’s potential as a shield against misinformation.
* *0:05:10** Open Source Alternatives:* Open-source alternatives to Deep Research began emerging within 12 hours of its release, promoting collaborative development and accessibility.
* *0:05:31** Creating New Information:* The video highlights that organizing information is just the first step, with creating new information (like peer-reviewed papers) being the next, potentially within a year.
* *0:05:55** Early Signs of Innovation:* An example shows Deep Research making new propositions and formal arguments, hinting at a transition from analysis to genuine innovation.
* *0:06:28** User Validation:* An associate professor acknowledged the novelty of the AI’s output, albeit not entirely groundbreaking yet.
* *0:06:42** Main Take Away* This year we might start seeing new knowledge created by AI techniques.
* *0:07:07** Naming Controversy:* The video touches on the naming similarity between OpenAI’s Deep Research and a technique previously released by Google DeepMind.
* *0:07:26** Wait for Deeper Analysis:* The video waits a little after new releases to give better analysis.

I used gemini-exp-1206 on rocketrecap dot com to summarize the transcript.
Input tokens: 13160
Output tokens: 646

@theGreenPiedPiper says:

UHOH! looking like 2 minutes papers is biased!

@hectoris919 says:

You say that the AI removes bias when giving you the news because it looks up many different sources, but have you considered that the AI itself is biased?

For example, if DeepSeek made their own version of this, it would be highly biased towards their agenda. If you try asking R1 questions the Chinese government doesn’t like, it won’t give you a response (for example, “Is Taiwan a country?”)

I think for the AI to give truly unbiased reports on information, the AI model and company behind it needs to be unbiased

@zsoltlendvai5864 says:

When you realize that 150-600GB large language models are just the building blocks for a much more complex system. And these systems will be the building blocks for much much more sophisticated systems… “what a time to be alive!”