I can't say I would think that Google does a particularly good job at interpreting the intent of my search queries. I often need to reformulate them to get what I'm after. But I doubt that my searches are similar to those of the general public so that is understandable.

I get the same feeling - that Google is often missing the meaning and giving me unrelated keyword matches.

It's even worse than that - it explicitly ignores quoted keywords in many cases. The only intent they care about is what guides you towards their interests.

my favorite is from today when searching for "comparison prohibited benchmarks" google decide to give me results to "comparison ALLOWED benchmarks"

Enjoyed

> Some aspects of communication are likely to prove more challenging, Hinton predicted. “Irony is going to be hard to get,” he said. “You have to be master of the literal first. But then, Americans don’t get irony either. Computers are going to reach the level of Americans before Brits.”

"They now infer your meaning and find results that match your intent -- even if the exact search string doesn't exist in the search results."

Bing seems to do the same thing. I really wish there were a grep for the web because both engines get it wrong even when I try to exclude results.

Try verbatim mode with google: http://paste.click/SWqasi

It's basically grep for the web, since it uses the actual query instead of the meaning of it.

Thanks, I did not know that was an option. It should make a few different queries quite a lot nicer. I was starting to get scared that I was wishing for the old Alta Vista.

But if I searched in the dialect of the content I would get the content. This is simply segregating the internet. Not "pushing down" rankings.

As an aside - this is a slippery slope conversation. Some people believe language requires rules. Other, more special people, think language is fluid and anarchist. The latter of those two do not make search engines.

For your aside, I don't think it's true. Search engine makers are well aware that language usage is what it is, and not what the thesaurus or grammar book says it is. Unfortunately, using machine learning to work out synonyms means you're going to miss out on minority usages, such as specialized academic jargon, or communities with millions of speakers which have slang and conversational grammar unlike "standard" English.

Try some sample "AAVE" texts in Google, it does a decent job of capturing intent.

My guess is that it's unlikely to provide sources that are in one of these dialects, as the link density will be low.