611–620 of 639 posts
Google can do this now, for example in a prototype. The tough thing is to get it to consumer-grade quality without messing up other searches. The QA process is utterly brutal because one weird search can be a scandal.
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At least this is relatively innocuous. Until recently if you did a Google Image Search for "person" or "people", it only showed white men.
I couldn't quite believe your comment when I read it so I did a Google image search for "person" and the results weren't a lot better than you'd suggested. Mostly white men, a few white women, a very few black women, a handful of Asians, and multiple instances of Terry Crews. The net result of that Google search, combined with the "Shirt Without Stripes" repo, leaves me even more unimpressed with the capabilities of…
shirt -stripes
Fishbone - Drunk Skitzo https://youtu.be/SaPGH4Yd_zc?t=231
(Apologies for the snarky low-content flip reply.)
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Google was good at launch because it was harvesting data from webrings and directories to provide it "high quality" link ranking data. However, they didn't thank or credit or share any of their revenue with the sites whose human curation helped their results become so impressive. Seeing that Google search was effective, most human curators stopped curating directories and webrings. The SEO industry picked up the slac…
Google was good because they used to optimise to giving the best search results, that was their aim. Now their aim is best profit, it seems, and their results appear to correspond (keep you on site longer).
Google's aim was to replace other sources of information with Google:
> People make decisions based on information they find on the Web. So companies that are in-between people and their information are in a very powerful position
Profit was on their minds from the very beginning:
> There are a lot of benefits for us, aside from potential financial success.
Revenue, however, was not urgent back then, to them or to their VCs:
> Right now, we’re thinking about generating some revenue. We have a number of ways to doing that. One thing is we can put up some advertising.
So over the past two decades, they executed a two-pronged approach: Become indispensable and Become profitable. But now they're trying to pivot from "at web search" to "at assisting human beings", and that's a much more difficult problem when their approach to "Become profitable" was to use algorithms rather than human beings.
Here's a useful litmus test for whether Google has succeeded at that pivot:
If you were in a foreign city and you suddenly wanted to propose marriage to your partner, would you trust Google Assistant to help you find a ring, make a dinner reservation, and ensure that the staff support the mood you want (Quiet or Loud, Private or Public)?
If so, then Google's pivot has been successful.
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I agree the parent is overthinking it, but that's underthinking it. It's been a long time since search engines were mere text matchers.
I’m uncomfortable with your use of “mere.” It might connote that what Google Search does now is an improvement.
I have the same reservations about Google as anyone, but rewriting history is never the right move. Moving beyond text matching was what made search truly useful.
https://medium.com/pinterest-engineering/pinsage-a-new-graph...
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You need to actually build up noun comprehension though, because "evidence of no remaining cancer" or other qualifier words can greatly confuse the situation. You'd also have quite a bit of fun trying to parse the phrase "no means no" or other usages where "no" is being used as a noun... And for bonus points, folks talk to search engines in broken english all the time so "shirts no single striped" is a totally reason…
The broken English aspect also happens because we know search engines don't understand English anyway.
I think the basic issue is that people just don't respect machines and want to minimize the amount of effort spend on communicating with them - I don't say "Alexa please bring up songs by Death Grips if you don't mind" I shout "Alexa! Play! Death Grips!" and then yell at it when it misunderstands.
Given exact query to human, they create environment thus context themselves.
It may also depend on whom you are asking to. For example, myself, entering this site to find out news about software & tech. Also since 'Stripe' is a company name, I assumed link will get the list of shirt shops who do not accept Stripe as a payment method/provider. (Thus some kind of protest related thing)
I literally thought about that yesterday and did not see the page thinking "That's too much for tonight".
Now seeing topic is somewhat very different.
The point that the author is making, in a very understated way, is that all three companies have PR websites that breathlessly describe their advanced AI capabilities, yet they cannot understand a very simple query that young children can.
At least this is relatively innocuous. Until recently if you did a Google Image Search for "person" or "people", it only showed white men.
"shirts -stripes" results: https://www.amazon.com/s?k=shirts+-stripes&ref=nb_sb_noss_2
So basically the AI doesn't convert "without x" to "-x" even though the basic capability needed is there. This is why AI is a hard problem, especially when it meets the real world.
It's 2020 and we're still quibbling about the terminology used in SQL, what did we expect?