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Google is winning on every AI front

(www.thealgorithmicbridge.com)
993 points vinhnx | 3 comments | | HN request time: 0.641s | source
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tkgally ◴[] No.43662468[source]
> Gemini 2.5 Pro in Deep Research mode is twice as good as OpenAI’s Deep Research

That matches my impression. For the past month or two, I have been running informal side-by-side tests of the Deep Research products from OpenAI, Perplexity, and Google. OpenAI was clearly winning—more complete and incisive, and no hallucinated sources that I noticed.

That changed a few days ago, when Google switched their Deep Research over to Gemini 2.5 Pro Experimental. While OpenAI’s and Perplexity’s reports are still pretty good, Google’s usually seem deeper, more complete, and more incisive.

My prompting technique, by the way, is to first explain to a regular model the problem I’m interested in and ask it to write a full prompt that can be given to a reasoning LLM that can search the web. I check the suggested prompt, make a change or two, and then feed it to the Deep Research models.

One thing I’ve been playing with is asking for reports that discuss and connect three disparate topics. Below are the reports that the three Deep Research models gave me just now on surrealism, Freudian dream theory, and AI image prompt engineering. Deciding which is best is left as an exercise to the reader.

OpenAI:

https://chatgpt.com/share/67fa21eb-18a4-8011-9a97-9f8b051ad3...

Google:

https://docs.google.com/document/d/10mF_qThVcoJ5ouPMW-xKg7Cy...

Perplexity:

https://www.perplexity.ai/search/subject-analytical-report-i...

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1. stafferxrr ◴[] No.43663695[source]
Great stuff. My prompts are falling behind after seeing what you are doing here.

I find OpenAI annoying at this point that it doesn't output a pdf easily like Perplexity. The best stuff I have found has been in the Perplexity references also.

Google outputting a whole doc is really great. I am just about to dig into Gemini 2.5 Pro in Deep Research for the first time.

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2. tkgally ◴[] No.43664068[source]
> My prompts are falling behind....

If you haven’t already, you might want to try metaprompting, that is, having a model write the prompt for you. These days, I usually dictate my metaprompts through a STT app, which saves me a lot of time. A metaprompt I gave to Claude earlier today is at [1]. It’s sloppy and has some transcription errors, but, as you can see, Claude wrote a complete, well-organized prompt that produced really good results from Gemini Deep Research [2]. (I notice now, though, that the report is truncated at the end.)

[1] https://claude.ai/share/94982d9d-b580-496f-b725-786f72b15956

[2] https://docs.google.com/document/d/1np5xdXuely7cxFMlkQm0lQ4j...

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3. siva7 ◴[] No.43671529[source]
Metaprompting is the way to go. Also avoid projects attachments as it uses inferior techniques like rag