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Perplexity Deep Research

perplexity.ai

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Re: Perplexity Deep Research

#71

Post by baxtr »

alexvitkov wrote: post #50

Every week we get a new AI that according to the AI-goodness-benchmarks is 20% better than the old AI, yet the utility of these latest SOTA models is only marginally higher than the first ChatGPT version released to the public a few years back. These things have the reasoning skills of a toddler, yet we keep fine-tuning their writing style to be more and more authoritative - this one is only missing the font and colo…

Just yesterday I did my first Deep Research with OpenAI on a topic I know well.

I have to say I am really underwhelmed. It sounds all authoritative and the structure is good. It all sounds and feels substantial on the surface but the content is really poor.

Now people will blame me and say: you have to get the prompt right! Maybe. But then at the very least put a disclaimer on your highly professional sounding dossier.

Re: Perplexity Deep Research

#72

Post by ankit219 »

Every time OpenAI comes up with a new product, and a new interaction mechanism / UX and low and behold, others copy the same, sometimes leveraging the same name as well.

Happened with ChatGPT - a chat oriented way to use Gen AI models (phenomenal success and a right level of abstraction), then code interpreter, the talking thing (that hasnt scaled somehow), the reasoning models in chat (which i feel is a confusing UX when you have report generators, and a better ux would be just keep editing source prompt), and now deep research. [1] Yes, google did it first, and now Open AI followed, but what about so many startups who were working on similar problems in these verticals?

I love how openai is introducing new UX paradigms, but somehow all the rest have one idea which is to follow what they are doing? Only thing outside this I see is cursor, which i think is confusing UX too, but that's a discussion for another day.

[1]: I am keeping Operator/MCP/browser use out of this because 1/ it requires finetuning on a base model for more accurate results 2/ Admittedly all labs are working on it separately so you were bound to see the similar ideas.

Re: Perplexity Deep Research

#73

Post by upcoming-sesame »

ankit219 wrote: post #72

Every time OpenAI comes up with a new product, and a new interaction mechanism / UX and low and behold, others copy the same, sometimes leveraging the same name as well. Happened with ChatGPT - a chat oriented way to use Gen AI models (phenomenal success and a right level of abstraction), then code interpreter, the talking thing (that hasnt scaled somehow), the reasoning models in chat (which i feel is a confusing UX…

I'm pretty sure Gemini had deep research before openai

Re: Perplexity Deep Research

#74

Post by ibeff »

submeta wrote: post #57

It ends its research in a few seconds. Can this be even thorough? Chatgpt‘s Deep Research does its job for five minutes or more.

I'm getting about 1 minute responses, did you turn on the Deep Research option below the prompt?

Re: Perplexity Deep Research

#75

Post by ankit219 »

baxtr wrote: post #71
alexvitkov wrote: post #50

Every week we get a new AI that according to the AI-goodness-benchmarks is 20% better than the old AI, yet the utility of these latest SOTA models is only marginally higher than the first ChatGPT version released to the public a few years back. These things have the reasoning skills of a toddler, yet we keep fine-tuning their writing style to be more and more authoritative - this one is only missing the font and colo…

Just yesterday I did my first Deep Research with OpenAI on a topic I know well. I have to say I am really underwhelmed. It sounds all authoritative and the structure is good. It all sounds and feels substantial on the surface but the content is really poor. Now people will blame me and say: you have to get the prompt right! Maybe. But then at the very least put a disclaimer on your highly professional sounding dossie…

I think it's bound to underwhelm the experts. What this does is go through a number of public search results (i think its google search for now, coudl be internal corpus). And hence skips all the paywalled and proprietary data that is not directly accessible via Google. It can produce great output but limited by the sources it can access. If you know more, cos you understand it better, plus know sources which are not indexed by google yet. Moreover there is a possiblity most google surfaced results are a dumbed down and simplified version to appeal to a wider audience.

Re: Perplexity Deep Research

#76

Post by bsaul »

can someone explain what perplexity value is ? They seem like a thin wrapper on top of big AI names, and yet i find them often mentioned as equivalent to the likes of opena ai / anthropic / etc, which build foundational models.

It's very confusing.

Re: Perplexity Deep Research

#77

Post by RobinL »

bsaul wrote: post #76

can someone explain what perplexity value is ? They seem like a thin wrapper on top of big AI names, and yet i find them often mentioned as equivalent to the likes of opena ai / anthropic / etc, which build foundational models. It's very confusing.

They were doing web search before open ai/anthropic, so they historically had a (pretty decent) unique selling point.

Once chat gpt added web browsing, I largely stopped using perplexity

Re: Perplexity Deep Research

#78

Post by ibeff »

caseyy wrote: post #36
SubiculumCode wrote: post #31

Are there good benchmarks for this type of tool? It seems not? Also, I'd compare with the output of phind (with thinking and multiple searches selected).

The best practical benchmark I found is asking LLMs to research or speak on my field of expertise.

That's what I did. It came up with smart-sounding but infeasible recommendations because it took all sources it found online at face value without considering who authored them for what reason. And it lacked a massive amount of background knowledge to evaluate the claims made in the sources. It took outlandish, utopian demands by some activists in my field and sold them to me as things that might plausibly be implemented in the near future.

Real research needs several more levels of depth of contextual knowledge than the model is currently doing for any prompt. There is so much background information that people working in my field know. The model would have to first spend a ton of time taking in everything there is to know about the field and several related fields and then correlate the sources it found for the specific prompt with all of that.

At the current stage, this is not deep research but research that is remarkably shallow.

Re: Perplexity Deep Research

#79

Post by riedel »

upcoming-sesame wrote: post #73
ankit219 wrote: post #72

Every time OpenAI comes up with a new product, and a new interaction mechanism / UX and low and behold, others copy the same, sometimes leveraging the same name as well. Happened with ChatGPT - a chat oriented way to use Gen AI models (phenomenal success and a right level of abstraction), then code interpreter, the talking thing (that hasnt scaled somehow), the reasoning models in chat (which i feel is a confusing UX…

I'm pretty sure Gemini had deep research before openai

Yes,see sibling comment: https://news.ycombinator.com/item?id=43064111 . I think you will find a predecessor to most of OpenAIs interaction concepts. Also canvas was I guess inspired by other code copilots. I think their competence is rather being able to put tons of resources into it pushing it into the market in a usable way (while sometimes breaking things). Once OpenAI had it the rest feels like they now also have to move. They are simply have become defacto reference.

Re: Perplexity Deep Research

#80

Post by ankit219 »

upcoming-sesame wrote: post #73
ankit219 wrote: post #72

Every time OpenAI comes up with a new product, and a new interaction mechanism / UX and low and behold, others copy the same, sometimes leveraging the same name as well. Happened with ChatGPT - a chat oriented way to use Gen AI models (phenomenal success and a right level of abstraction), then code interpreter, the talking thing (that hasnt scaled somehow), the reasoning models in chat (which i feel is a confusing UX…

I'm pretty sure Gemini had deep research before openai

I said so too, I used google instead of gemini. Somehow it did not create as much of a buzz then as it did now.
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