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Ooh, this sounds very interesting; if they can pull this off, I can totally see Google taking a serious hit (especially with the quality already declined due to

Ooh, this sounds very interesting; if they can pull this off, I can totally see Google taking a serious hit (especially with the quality already declined due to ads / SEO).

intelVISA 4y ago
Could potentially be pretty bad for Google and I'm no MS/OpenAI fan. As a complete outsider to ML my hope is NLP style search with RL + LLM is going to disrupt the Old Way.
twelve40 4y ago
while competition is welcome, wouldn't they face the same exact problem as Google - filtering out tons of crap seo text and actually trying to separate out non-noise text from that?
- maxbond 4y ago
  And if "next gen SEO" (adversarial training data that cause something to be inappropriately or disproportionately represented in responses) lands in your chat search, it isn't a matter of just setting flags in a database to ignore or penalize a set of documents - you're gunnuh have to either retrain, or add a new set of layers (or similar) to filter out/penalize these results. If this starts happening at anything close to the rate that Google encounters spam, I can't see how they would keep up.
  - visarga 4y ago
    Language models are tested with hundreds of benchmarks including everything from bias to factuality and reasoning correctness. When they have a big deficiency it shows in the test scores.
    - maxbond 4y ago
      Big deficiencies aren't monetizable by adversaries, tiny ones are (eg, impacting it's response to questions about one topic in particular). In a very narrow niche there may not be many documents to pick from, either. I don't think you can just automate this away in the context of generalized search. Search has to fulfill every niche; that seems like an indefensible position (strategically speaking, not in the moral sense). How can you benchmark bias in every niche? Your benchmarks show your reasoning is sound; what about the premises you're reasoning from? In the context of something narrowly scoped like a customer service bot, it makes sense to me how you could build expertise in constraining the model's output. But in terms of everything? But I'll admit I don't have a crystal ball, happy to eat my words if they can operate with enough traffic and got long enough to attract the attention of spammers, and still keep them at bay. I think this space is stagnant and needs to be shaken up, and that chat interfaces have potential, so I'm not trying to be a hater. I just think this is gunnuh be a very difficult aspect.
skatanski 4y ago
would it? Many here are IT professionals and technology enthusiasts, naturally drawn to the next interesting thing, next disruption. Does the average user of Google care.

Ooh, this sounds very interesting; if they can pull this off, I can totally see Google taking a serious hit (especially with the quality already declined due to ads / SEO).

intelVISA 4y ago

Could potentially be pretty bad for Google and I'm no MS/OpenAI fan. As a complete outsider to ML my hope is NLP style search with RL + LLM is going to disrupt the Old Way.

twelve40 4y ago

while competition is welcome, wouldn't they face the same exact problem as Google - filtering out tons of crap seo text and actually trying to separate out non-noise text from that?

maxbond 4y ago
And if "next gen SEO" (adversarial training data that cause something to be inappropriately or disproportionately represented in responses) lands in your chat search, it isn't a matter of just setting flags in a database to ignore or penalize a set of documents - you're gunnuh have to either retrain, or add a new set of layers (or similar) to filter out/penalize these results. If this starts happening at anything close to the rate that Google encounters spam, I can't see how they would keep up.
- visarga 4y ago
  Language models are tested with hundreds of benchmarks including everything from bias to factuality and reasoning correctness. When they have a big deficiency it shows in the test scores.
  - maxbond 4y ago
    Big deficiencies aren't monetizable by adversaries, tiny ones are (eg, impacting it's response to questions about one topic in particular). In a very narrow niche there may not be many documents to pick from, either. I don't think you can just automate this away in the context of generalized search. Search has to fulfill every niche; that seems like an indefensible position (strategically speaking, not in the moral sense). How can you benchmark bias in every niche? Your benchmarks show your reasoning is sound; what about the premises you're reasoning from? In the context of something narrowly scoped like a customer service bot, it makes sense to me how you could build expertise in constraining the model's output. But in terms of everything? But I'll admit I don't have a crystal ball, happy to eat my words if they can operate with enough traffic and got long enough to attract the attention of spammers, and still keep them at bay. I think this space is stagnant and needs to be shaken up, and that chat interfaces have potential, so I'm not trying to be a hater. I just think this is gunnuh be a very difficult aspect.

skatanski 4y ago

would it? Many here are IT professionals and technology enthusiasts, naturally drawn to the next interesting thing, next disruption. Does the average user of Google care.