3 ms·

Maybe this is a result of optimizing for most of the population, which probably decreases performance for tiny minority who search for niche things that are har

• dooglius 7y ago
  I don't think that fully captures it, Google is an advertising company, and so its incentives are all out of whack. For instance, Google probably benefits from having the top results be slightly less useful as that makes the ads at the top more likely to get clicks.
• huffmsa 7y ago
  The ML layer is probably getting in the way of the end user getting to the smaller samples. Used to be you'd get the best matches from the meta data on a page. Now there's linear algebra both trying to determine what the meta data means and what the question means, so it's going to have grouping biases. And do things like exclude seemingly random strings of numbers, because in the training data, that's usually trash, but for you, it's a part or serial number that you're looking for