51–60 of 134 posts
Earlier quoted context omitted.
The “videos engage better than text” idea has been dominant for a few years now. It’s based on a Facebook statement?
Facebook pushed that argument hard , and there is an ongoing lawsuit over whether they misled their customers.
This shows the limitations of ML: facebook has incredible amounts of preference & behaviour data on its users; and can't even meet incredibly generic categories such as "high-earner, college educated, etc.". The reason we think we're in an "AI" boom is 90% these ad. companies hyping their own abilities (an identical strategy to that of the initial boom in the 50s). What we call "AI" today is just an associative house…
I can't speak for other people, but the reason that I think we are in an AI boom has nothing to do with online advertising. It is that computers can now recognize images, translate language, have conversations, generate articles, make realistic looking pictures, play the game of go, solve protein folding, generate realistic text to speech, recognize voices. All these things were not possible 5 years ago. Every year t…
In five years we will without a doubt have systems that play more games, solve more puzzles, fold more proteins and so on, but we'd have more progress on intelligence if we could build a machine that could reliably plumb a toilet or catch a mouse as well as a cat.
I know everyone loves to hate Facebook and articles that confirm that bias are very popular right now, but this lawsuit doesn't seem to have smoking gun evidence like the headline suggests. Have you ever written an e-mail or Slack message to a peer complaining that something at your company might not be working well? Or that something is totally broken and you think it should be prioritized in the ticket queue? Imagi…
Here's a specific example: we ran around $1k in ads last year, targeting senior-level engineers at technology companies, but the ads were getting liked by mostly people who worked minimum-wage jobs. Twitter and LinkedIn targeting were fine with pretty much the same parameters.
This is one example, obviously, but it's so trivial to see that targeting is almost completely uncorrelated with reality, that it's not hard to come up with more examples.
This shows the limitations of ML: facebook has incredible amounts of preference & behaviour data on its users; and can't even meet incredibly generic categories such as "high-earner, college educated, etc.". The reason we think we're in an "AI" boom is 90% these ad. companies hyping their own abilities (an identical strategy to that of the initial boom in the 50s). What we call "AI" today is just an associative house…
I guess there's two ways of looking at this: * 40% of targeted viewers didn't match "high-earner, college educated", the system is crap! or * 60% of targeted viewers did match "high-earner, college educated", that's amazing! I dunno... do you have a better way of reaching those targeted viewers? Do you have a better way of measuring results than abstract page views? Depending on the context, 60% could be very worth i…
This shows the limitations of ML: facebook has incredible amounts of preference & behaviour data on its users; and can't even meet incredibly generic categories such as "high-earner, college educated, etc.". The reason we think we're in an "AI" boom is 90% these ad. companies hyping their own abilities (an identical strategy to that of the initial boom in the 50s). What we call "AI" today is just an associative house…
It's not right to judge ML by the quality of recommender systems. First of all, recommenders are just a small corner of ML, and on this scale are only developed at few companies. Second, I am not 100% sure they maximize what you want to see, instead they maximize what will make them more money. That's why it sucks.
Earlier quoted context omitted.
I can't speak for other people, but the reason that I think we are in an AI boom has nothing to do with online advertising. It is that computers can now recognize images, translate language, have conversations, generate articles, make realistic looking pictures, play the game of go, solve protein folding, generate realistic text to speech, recognize voices. All these things were not possible 5 years ago. Every year t…
>recognize voices. All these things were not possible 5 years ago. FTR: https://en.wikipedia.org/wiki/Dragon_NaturallySpeaking Dragon Systems released NaturallySpeaking 1.0 as their first continuous dictation product in 1997. As of 2012 LG Smart TVs include voice recognition feature powered by the same speech engine as Dragon NaturallySpeaking.
Today voice transcription is a solved problem and while their engine might be the same in name - I’d be surprised if the approach isn’t totally different than what they were doing in 97, either that or the LG tv voice transcription probably doesn’t work as well as everyone else’s.
The deep learning revolution and the applications we’ve seen since 2015 are a major step forward and something truly different. People pretending otherwise are just acting cynical in some attempt to project intelligence or seem wise, it doesn’t work.
Earlier quoted context omitted.
Facebook pushed that argument hard , and there is an ongoing lawsuit over whether they misled their customers.
What’s the evidence they misled customers? Internal documents?
I know everyone loves to hate Facebook and articles that confirm that bias are very popular right now, but this lawsuit doesn't seem to have smoking gun evidence like the headline suggests. Have you ever written an e-mail or Slack message to a peer complaining that something at your company might not be working well? Or that something is totally broken and you think it should be prioritized in the ticket queue? Imagi…
I think there's a huge difference between "statements are being cherry picked" and Bosworth, a major confidant to Zuckerberg, stating that "[I]nterest precision in the US is only 41%—that means that more than half the time we’re showing ads to someone other than the advertisers’ intended audience". I appreciate that you're pointing out the movement du jour against Facebook, but here it looks cut and dry to me.
Talking about (inadvertent) misquotes: the quote was attributed to a "February 2016 internal memorandum sent from an unnamed Facebook manager to Andrew Bosworth, a Zuckerberg confidant and powerful company executive who oversaw ad efforts at the time [...]". (Italic emphasis is mine)
This shows the limitations of ML: facebook has incredible amounts of preference & behaviour data on its users; and can't even meet incredibly generic categories such as "high-earner, college educated, etc.". The reason we think we're in an "AI" boom is 90% these ad. companies hyping their own abilities (an identical strategy to that of the initial boom in the 50s). What we call "AI" today is just an associative house…
I can't speak for other people, but the reason that I think we are in an AI boom has nothing to do with online advertising. It is that computers can now recognize images, translate language, have conversations, generate articles, make realistic looking pictures, play the game of go, solve protein folding, generate realistic text to speech, recognize voices. All these things were not possible 5 years ago. Every year t…
Earlier quoted context omitted.
>recognize voices. All these things were not possible 5 years ago. FTR: https://en.wikipedia.org/wiki/Dragon_NaturallySpeaking Dragon Systems released NaturallySpeaking 1.0 as their first continuous dictation product in 1997. As of 2012 LG Smart TVs include voice recognition feature powered by the same speech engine as Dragon NaturallySpeaking.
Yeah I played with dragon in 97 and it was awful - it didn’t work at all, completely unusable. Today voice transcription is a solved problem and while their engine might be the same in name - I’d be surprised if the approach isn’t totally different than what they were doing in 97, either that or the LG tv voice transcription probably doesn’t work as well as everyone else’s. The deep learning revolution and the applic…
But you can't claim that something "wasn't possible 5 years" ago, if 7 years ago said feature was included in inexpensive consumer product (LG TV).
I'm not acting cynical, but it's tiresome for me to see people who claim that 20-30 years ago we all were living in a caves and catching bugs with wooden sticks, and now boom, ML!
Regarding "something truly different", well, my personal computing / mobile experience not changed that much from 2015. Honestly speaking, progress from 1995 to 2000 felt much more impressive and 'truly different'. I mean, think of it, during this timeframe we went from DOOM via V.34 modems to amazon.com and ordering pizza online.