4 ms·

This was inevitable. Traditional search is an inefficient way to access information in a world with large AI models. Google is being forced to do this due to c

This was inevitable. Traditional search is an inefficient way to access information in a world with large AI models. Google is being forced to do this due to competition from openAI, meta.ai, perplexity, etc.

hobs 2y ago
It's really not, they are extremely complementary.
- _heimdall 2y ago
  Not necessarily. Internet search algorithms were designed to solve the discoverability problem. LLMs are generative, they're creating content rather than finding it for you. They also serve a different business model. Sure you can have ads in LLM answers similar to Google search results, but Google is also selling clicks. LLMs are designed and used, at least today, to give you the answer so you don't need to see an original source. Beyond that, the idea of a generative algorithm being used in tandem with sponsored results sounds pretty gross in my opinion. I already don't like Google's approach to search results, but if they're also generating the responses on the fly why am I even there? Its only a matter of time before the generative algorithm is trained specifically to drive more sponsorship revenue, maybe by making up content that works better for ad bids or stuffing a reference to a sponsor into a response only because the inline ad pays or converts better.
  - hobs 2y ago
    Seems like the option is constantly retrain an LLM or give it enough tools to interact with new data as needed. For the foreseeable future LLM's are going to need RAG or huge context windows which are effectively equivalent to RAG because you are isolating from some giant corpus your useful information you want the machine to meaningfully interact with.
    - _heimdall 2y ago
      It still seems like a different use case to me, but maybe I'm wrong there. I don't mind a search algorithm including a summary as long as its true to the original, but I really don't want any generated content that's trying to predict how someone would answer my question. If LLMs end up replacing most of the use of tools like Google Search we really have moved past the discovery problem and don't necessarily want to find or see the original (human authored) content at all.
caseyy 2y ago
LLMs cannot compete on truthful high-quality information from experts. Only on plausible babble. If that’s the only information you search for, then your perspective makes sense. We shouldn’t be using LLMs for information retrieval at all. They should be summarizing individual web pages at best. That would make search more efficient. But to use plausible text generator without any guaranteed veracity checks in the pipeline for information retrieval is madness.
- deleted 2y ago
  [deleted]
ricardo81 2y ago
It is a bit surreal that you describe sucking up the world's information and spitting it out via a commercial entity and to you as a search result as 'inefficient'. Perhaps it's more inefficient for all those content creators to bother creating anything vs what you actually derive from the search result, especially if they're not attributed/compensated.

hobs 2y ago

It's really not, they are extremely complementary.

_heimdall 2y ago
Not necessarily. Internet search algorithms were designed to solve the discoverability problem. LLMs are generative, they're creating content rather than finding it for you. They also serve a different business model. Sure you can have ads in LLM answers similar to Google search results, but Google is also selling clicks. LLMs are designed and used, at least today, to give you the answer so you don't need to see an original source. Beyond that, the idea of a generative algorithm being used in tandem with sponsored results sounds pretty gross in my opinion. I already don't like Google's approach to search results, but if they're also generating the responses on the fly why am I even there? Its only a matter of time before the generative algorithm is trained specifically to drive more sponsorship revenue, maybe by making up content that works better for ad bids or stuffing a reference to a sponsor into a response only because the inline ad pays or converts better.
- hobs 2y ago
  Seems like the option is constantly retrain an LLM or give it enough tools to interact with new data as needed. For the foreseeable future LLM's are going to need RAG or huge context windows which are effectively equivalent to RAG because you are isolating from some giant corpus your useful information you want the machine to meaningfully interact with.
  - _heimdall 2y ago
    It still seems like a different use case to me, but maybe I'm wrong there. I don't mind a search algorithm including a summary as long as its true to the original, but I really don't want any generated content that's trying to predict how someone would answer my question. If LLMs end up replacing most of the use of tools like Google Search we really have moved past the discovery problem and don't necessarily want to find or see the original (human authored) content at all.

caseyy 2y ago

LLMs cannot compete on truthful high-quality information from experts. Only on plausible babble. If that’s the only information you search for, then your perspective makes sense. We shouldn’t be using LLMs for information retrieval at all. They should be summarizing individual web pages at best. That would make search more efficient. But to use plausible text generator without any guaranteed veracity checks in the pipeline for information retrieval is madness.

deleted 2y ago
[deleted]

ricardo81 2y ago

It is a bit surreal that you describe sucking up the world's information and spitting it out via a commercial entity and to you as a search result as 'inefficient'. Perhaps it's more inefficient for all those content creators to bother creating anything vs what you actually derive from the search result, especially if they're not attributed/compensated.