Earlier quoted context omitted.
> pussification of silicon valley upside magazine Google nor bing can find this
https://www.google.com/search?q=pussification+of+silicon+val...
I don't see the article you are mentioning
Perplexity Deep Research
61–70 of 180 posts
Re: Perplexity Deep Research
#62Tried it and it is worse that OpenAI deep search (one query only, will need to try it more I guess...)
The openAi version costs 200$ and takes a lot longer, not sure if it is fair to compare?
Re: Perplexity Deep Research
#63It ends its research in a few seconds. Can this be even thorough? Chatgpt‘s Deep Research does its job for five minutes or more.
Openai is not running solid five minutes of LLM compute per request. I know they are not profitable and burn money even on normal request, but this would be too much even for them.
Likely they throttle and do a lot of waiting for nothing during those five minutes. Can help with stability and traffic smoothing (using "free" inference during times the API and website usage drops a bit), but I think it mostly gives the product some faux credibility - "research must be great quality if it took this long!"
They will cut it down by just removing some artificial delays in few months to great fanfare.
Re: Perplexity Deep Research
#64Earlier quoted context omitted.
https://www.google.com/search?q=pussification+of+silicon+val...
I don't see the article you are mentioning
Wild. My results are literally dozens of posts about the article.
Re: Perplexity Deep Research
#65Earlier quoted context omitted.
https://www.google.com/search?q=pussification+of+silicon+val...
Nothing with "pussification" in the title for me there.
Wild. My results are literally dozens of posts about the article.
Re: Perplexity Deep Research
#66Re: Perplexity Deep Research
#67It ends its research in a few seconds. Can this be even thorough? Chatgpt‘s Deep Research does its job for five minutes or more.
Openai is not running solid five minutes of LLM compute per request. I know they are not profitable and burn money even on normal request, but this would be too much even for them. Likely they throttle and do a lot of waiting for nothing during those five minutes. Can help with stability and traffic smoothing (using "free" inference during times the API and website usage drops a bit), but I think it mostly gives the…
Well you may be right. But you can turn on the details and see that it seems to pull data, evaluate it, follow up on it. But my thought was: Why do I see this in slow motion? My home made Python stuff runs this in a few seconds, and my bottleneck is the API of the sites I query. How about them.
Re: Perplexity Deep Research
#68I just tried it and the result was pretty bad.
"How to do X combining Y and Z" (in a long detailed paragraph, my prompt-fu is decent). The sources it picked were reasonable but not the best. The answer was along the lines of "You do X with Y and Z", basically repeating the prompt with more words but not actually how to address the problem, and never mind how to implement it.
Re: Perplexity Deep Research
#69Earlier quoted context omitted.
I use these models to aid bleeding edge ml research every day. Sonnet can make huge changes and bug fixes to my code (that does stuff nobody else has tried in this way before) whereas GPT 3.5 Turbo couldn’t even repeat a given code block without dropping variables and breaking things. O1 can reason through very complex model designs and signal processing stuff even I have a hard time wrapping my head around.
On the other hand, if you try to solve some problem by creating the code by using AI only, and it misses only one thing, it takes more time to debug this problem rather than creating this code from scratch. Understanding some larger piece of AI code is sometimes equally hard or harder than constructing the solution into your problem by yourself.
Yes it’s important to make sure it’s easy to verify the code is correct.
Re: Perplexity Deep Research
#70Earlier quoted context omitted.
Openai is not running solid five minutes of LLM compute per request. I know they are not profitable and burn money even on normal request, but this would be too much even for them. Likely they throttle and do a lot of waiting for nothing during those five minutes. Can help with stability and traffic smoothing (using "free" inference during times the API and website usage drops a bit), but I think it mostly gives the…
Well you may be right. But you can turn on the details and see that it seems to pull data, evaluate it, follow up on it. But my thought was: Why do I see this in slow motion? My home made Python stuff runs this in a few seconds, and my bottleneck is the API of the sites I query. How about them.
When you query some APIs/scrape sites for personal use, it is unlikely you get throttled. Openai doing it at large scale for many users might have to go slower (they have tons of proxies for sure, but don't want to burn those IPs for user controlled traffic).
Similarly, their inference GPUs have some capacity. Spreading out the traffic helps keep high utilization.
But lastly, I think there is just a marketing and psychological aspect. Even if they can have the results in one minute, delaying it to two-five minutes won't impact user retention much, but will make people think they are getting a great value.