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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 capabi
by rgovostes 7y ago
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.
- oconnor663 7y agoSearching for "now one with stripes this time please" yielded similarly disappointing results :) Edit: "stripes" not "stripped" ugh
- devy 7y agoGoogle's result is noticeably better though. :)
- chipperyman573 7y agoWhat's better about it? I didn't notice anything good.
- lonesword 7y agoI think he/she's being sarcastic - there's general tendency to regard google's version of "ai" as better?
- nmstoker 7y agoYou mean more stylish?!
- ckarmann 7y agoDoes Amazon pretends to do AI? They are just offering a platform to do your own Machine Learning. I don't think they ever said their search engine was doing anything smart. EDIT: scrap that, I didn't mean Alexa, which is doing AI obviously, but the search engine of Amazon's retail website. Anyway, NLP is hard and everyone sucks at it. Think about it: just building something that could work with any <N1> <preposition> <N2> or any other way to express the same requests would mean understanding the relationships of every possible combinations of N1 and N2. It means building a generalized world model that is quite different from simply applying ML to a narrow use case. Cracking that would more or less mean solving general AI which probably won't happen soon.
- 5cott0 7y agoalexa, downvote this.
- Der_Einzige 7y agoML and AI are the same thing You're right the NLP is hard, but not everyone sucks at it.
- bartread 7y ago> ML and AI are the same thing Not actually true. ML is one area of study within the field of AI. Thanks to marketing departments and slightly shoddy journalism these two things are now casually treated as equivalents, but they're really not: ML is still very much a subset of AI.
- exhilaration 7y agoI disagree, "shirt without stripes" is an unusual word choice, not one that our ML models would be optimized for. Try "solid color shirt" and you'll see how much better the results are - at least on Google.
- aguyfromnb 7y ago>I disagree, who says "shirt without stripes"? That's an unusual word choice, not one that our ML algorithms would be optimized for. If your "ML algorithm" doesn't understand straightforward language, how is it any better than a couple if-then statements? Beyond that, I'm unsure how you think "<something> without <something>" is at all unusual or difficult to decipher.
- sib 7y ago"Shirt without stripes" may (or may not) be an unusual word choice to enter into a search engine, but it's definitely one that a child would understand. Additionally, "shirt without stripes" is not the same as "solid color shirt"; as an example, take a look at: https://www.google.com/search?q=tie+dye+shirt https://www.google.com/search?q=tie+dye+shirt
- bartread 7y agoQuite so. "Shirt without stripes" can include shirts in plenty of patterns other than solid colours (paisley, polka dot, checked, battenberg, floral print, etc.).
- zacksinclair 7y agoEvery human understands that phrase and yet the AI doesn't. That's the gap that has to be fixed.
- rmetzler 7y agoYou have to realize that search is not AI. It's pattern matching. And the string "shirt without stripes" matches really good with "shirt with stripes". Levenshtein distance is 3. If vendors would use the term "shirt without stripes" than it would match great, but they call it "plain shirt".
- apocalypstyx 7y ago“I’m sorry, Monsieur, we are all out of cream — how about with no milk?”
- diegoperini 7y agoIn Zizek's words, white coffee without milk isn't black coffee.
- Alex3917 7y agoAt least this is relatively innocuous. Until recently if you did a Google Image Search for "person" or "people", it only showed white men.
- _kst_ 7y agoA former coworker had the last name "Person". They once received a letter (snail mail) addressed to "TheirFirstName Human". I never figured out what kind of mistake could have led to that.
- dhimes 7y agoMaybe a veterinarian's customer database? They would have to distinguish pet names from humans, but keep a record of all.
- _kst_ 7y agoYeah, that's one plausible explanation. (I don't remember the nature of the letter.) Relatedly, one time I picked up a prescription for a cat. The cat's name was listed as CatFirstName MyLastName. They had another (human) client with that same first and name. It turned out that on my previous visit they had "corrected" that client's record to indicate that he was a cat.
- bartread 7y agoI 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 our AI overlords.
- tines 7y agoI think the skewing of results lessening your impressed-ness is the wrong takeaway. If anything, the AI is a more perfect mirror of the society it learned from than you expected. Perhaps the right way to look at it is that we are capable of producing things that we don't understand, that are more sophisticated than we realize.
- BickNowstrom 7y agoThat point is akin to stating: These three companies have not solved the hard problem of common sense [1], so are not allowed to advertise their AI without looking silly. Nobody has solved the common sense knowledge problem yet. A solution for that would qualify as Artificial General Intelligence and pass the Turing Test. But search engines have come a long way. I even suspect that when search engines place too much logical - or embedding relevance to stop words such as "without", that, on average, the relevant metrics would go down. It is not completely ignored as "shirt with stripes" surfaces more striped shirts than "shirt without stripes". "shirt -stripes" does what you want it to do. Searching for "white family USA" shows a lot of interracial families. Here "white" is likely not ignored as much, and thus it surfaces pages with images where that word is explicitly mentioned, which is likely happening when describing race. You can use Google to find Tori Amos when searching for "redhead female singer sings about rape". Bing surfaces porn sites. DDG surfaces lists (top 100 female singers) type results. The Wikipedia page that Google surfaces does not even contain the word "redhead", yet it falls back to list style results when removing "redhead" from your query, suggesting "redhead" and "Tori Amos" are close in their semantic space. That's impressive progress over 10-20 years back. [1] https://en.wikipedia.org/wiki/Commonsense_knowledge_(artificial_intelligence) https://en.wikipedia.org/wiki/Commonsense_knowledge_(artific...
- smsm42 7y agoI think a huge Chinese room type parser with a bunch of heuristics bolted on probably provides much better bang for the buck than trying to implement actual NLP (in every possible language, or even just in English). So that's probably what nearly everybody is doing.
- acdha 7y agoGoogle has for years put out puff pieces talking about high accuracy on image tagging. It’s only within the last few months that searching my Photos library for “cat” returned something other than pictures of my dog. There’s a nuanced argument that practitioners know how ML is so dependent on training data and accuracy tails off sharply, but that nuance tends to removed from anything selling to potential customers — which has not been a great way to keep them in my experience.
- fyfy18 7y agoI'd assume pets are hard as there are so many varieties (potentially even harder than humans). For the last few years Google Photos has correctly returned photos for a search of "Lamborghini" in my albums. I'd expect "shirt stripes" to fall into that category.
- acdha 7y agoSure, I’m not saying it’s an easy problem — just that the marketing is once again setting the field up for failure by giving the impression of human-level performance but delivering results only in very narrow scenarios.