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Perplexity Deep Research

perplexity.ai

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Re: Perplexity Deep Research

#121

Post by xiphias2 »

CjHuber wrote: post #93
TeMPOraL wrote: post #83

Earlier quoted context omitted.

Gemini was also "use us through this weird interface and also you can't if you're in the EU"; that + being far behind OpenAI and Anthropic for the past year means, they failed to reach notoriety, partly because of their own choices.

Honestly I don‘t get why everybody is saying Gemini is far behind. Like for me Gemini Flash Thinking Experimental performs far far better then o3 mini

o3 mini is still behind o1 pro, it didn't impress me.

I think the people who think anybody is close to OpenAI don't have pro subscription

Re: Perplexity Deep Research

#122

Post by calebkaiser »

rr808 wrote: post #106
exclipy wrote: post #51

Earlier quoted context omitted.

Not true at all. The original ChatGPT was useless other than as a curious entertainment app. Perplexity, OTOH, has almost completely replaced Google for me now. I'm asking it dozens of questions per day, all for free because that's how cheap it is for them to run. The emergence of reliable tool use last year is what has sky-rocketed the utility of LLMs. That has made search and multi-step agents feasible, and by exte…

> all for free because that's how cheap it is for them to run. No, these AI companies are burning through huge amounts of cash to keep the thing running. They're competing for market share - the real question is will anyone ever pay for this? I'm not convinced they will.

The question of "will people pay" is answered--OpenAI alone is at something like $4 billion in ARR. There are also smaller players (relatively) with impressive revenue, many of whom are profitable.

There are plenty of open questions in the AI space around unit economics, defensibility, regulatory risks, and more. "Will people pay for this" isn't one of them.

Re: Perplexity Deep Research

#123

Post by Kye »

lambdaba wrote: post #114
Kye wrote: post #101

Earlier quoted context omitted.

It varies a lot for me. One day it takes scattered documents, pasted in, and produces a flawless summary I can use to organize it all. The next, it barely manages a paragraph for detailed input. It does seem like Google is quick to respond to feedback. I never seem to run into the same problem twice.

> It does seem like Google is quick to respond to feedback. I'm puzzled as to how that would work, when people talk about quick changes in model behavior. What exactly is being adjusted? The model has already been trained. I would think it's just randomness.

Magic

And fine tuning.

Choose your fighter...

High level overview: https://www.datacamp.com/tutorial/fine-tuning-large-language...

More detail: https://www.turing.com/resources/finetuning-large-language-m...

Nice charts: https://blogs.oracle.com/ai-and-datascience/post/finetuning-...

The big platforms also seem to employ an intermediate step where they rewrite your prompt. I've downloaded my ChatGPT data and found substantial changes from what I wrote. Usually for the better. Changes to the way it rewrites changes the results.

Re: Perplexity Deep Research

#124

Post by rchaud »

As with all of these tools, my question is the same: where is the dogfooding? Where is the evidence that Perplexity, OAI etc actually use these tools in their own business?

I'm not particularly impressed with the examples they provided. Queries like "Top 20 biotech startups" can be answered by anything from Motley Fool or Seeking Alpha, Marketwatch or a million other free-to-read sources online. You have to go several levels deeper to separate the signal from the noise, especially with financial/investment info. Paperboys in 1929 sharing stock tips and all that.

Re: Perplexity Deep Research

#125

Post by brookst »

lambdaba wrote: post #114
Kye wrote: post #101

Earlier quoted context omitted.

It varies a lot for me. One day it takes scattered documents, pasted in, and produces a flawless summary I can use to organize it all. The next, it barely manages a paragraph for detailed input. It does seem like Google is quick to respond to feedback. I never seem to run into the same problem twice.

> It does seem like Google is quick to respond to feedback. I'm puzzled as to how that would work, when people talk about quick changes in model behavior. What exactly is being adjusted? The model has already been trained. I would think it's just randomness.

System prompts have a huge impact on output. Prompts for ChatGPT/etc are around a thousand words, with examples of what to do and what not to do. Minor adjustments there can make a big difference.

Re: Perplexity Deep Research

#126

Post by rnewme »

transformi wrote: post #10
simonw wrote: post #7

That's the third product to use "Deep Research" in its name. The first was Gemini Deep Research: https://blog.google/products/gemini/google-gemini-deep-resea... - December 11th 2024 Then ChatGPT Deep Research: https://openai.com/index/introducing-deep-research/ - February 2nd 2025 Now Perplexity Deep Research: https://www.perplexity.ai/hub/blog/introducing-perplexity-de... - February 14th 2025.

You forgot Huggingface researchers - https://www.msn.com/en-us/news/technology/hugging-face-resea... and BTW - I post an exact same spirit comment an hour ago... So I guess Today's copycat ethics aren't solely for products- but also for comment section . LOL.

Thinking simonw is stealing your comment is comedy moment of the day

Re: Perplexity Deep Research

#127

Post by rchaud »

stagger87 wrote: post #12
CSMastermind wrote: post #5

I'm super happy that these types of deep research applications are being released because it seems like such an obvious use case for LLMs. I ran Perplexity through some of my test queries for these. One query that it choked hard on was, "List the college majors of all of the Fortune 100 CEOs" OpenAI and Gemini both handle this somewhat gracefully producing a table of results (though it takes a few follow ups to get a…

Hopefully the end user of these products know something about LLMs and why asking a question such as "List the college majors of all of the Fortune 100 CEOs" is not really suited well for them.

Hopefully my boss groks how special I am and won't assign me tasks I consider to be beneath my intelligence (and beyond my capabilities).

Re: Perplexity Deep Research

#128

Post by rchaud »

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…

> It all sounds and feels substantial on the surface but the content is really poor.

They're optimizing for the sales demo. Purchasing managers aren't reading the output.

Re: Perplexity Deep Research

#129

Post by hansworst »

DebtDeflation wrote: post #98
CjHuber wrote: post #93

Earlier quoted context omitted.

Honestly I don‘t get why everybody is saying Gemini is far behind. Like for me Gemini Flash Thinking Experimental performs far far better then o3 mini

There's a lot of mental inertia combined with an extremely fast moving market. Google was behind in the AI race in 2023 and a good chunk of 2024. But they largely caught up with Gemini 1.5, especially the 002 release version. Now with Gemini 2 they are every bit as much of a frontier model player as OpenAI and Anthropic, and even ahead of them in a few areas. 2025 will be an interesting year for AI.

Arguably Google is ahead. They have many non-llm uses (waymo/deepmind etc) and they have their own hardware, so not as reliant on Nvidia.

Re: Perplexity Deep Research

#130

Post by rchaud »

rr808 wrote: post #106
exclipy wrote: post #51

Earlier quoted context omitted.

Not true at all. The original ChatGPT was useless other than as a curious entertainment app. Perplexity, OTOH, has almost completely replaced Google for me now. I'm asking it dozens of questions per day, all for free because that's how cheap it is for them to run. The emergence of reliable tool use last year is what has sky-rocketed the utility of LLMs. That has made search and multi-step agents feasible, and by exte…

> all for free because that's how cheap it is for them to run. No, these AI companies are burning through huge amounts of cash to keep the thing running. They're competing for market share - the real question is will anyone ever pay for this? I'm not convinced they will.

> They're competing for market share - the real question is will anyone ever pay for this?

The leadership of every 'AI' company will be looking to go public and cash out well before this question ever has to be answered. At this point, we all know the deal. Once they're publicly traded, the quality of the product goes to crap while fees get ratcheted up every which way.

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