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Twitter meets TensorFlow

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Re: Twitter meets TensorFlow

#31

Post by thelastidiot »

partiallypro wrote: post #29
llao wrote: post #2

> Machine learning enables Twitter to drive engagement, surface content most relevant to our users, and promote healthier conversations. One that wants to manipulate your mind, one that echochambers your discovery, one that censors arbitrarily.

If Twitter ever moves to a fully algorithmic timeline like Instagram (has annoying done), it will shrivel up and die. The linear timeline of Twitter is what makes Twitter....Twitter. I've noticed a lot lately that more and more I see tweets out of order because of the algorithms. I believe you can turn that off, but sometimes those are useful...but more often they are spam in the moment, especially if a big story has…

I second what you noticed. I now see myself with a WTF expression on my face when I am trying to figure out what happened with the linear timeline and all that junk I pretty much don't care about inserted in what I am interested to read. Feels like random ad inserts. Not good.

Re: Twitter meets TensorFlow

#33

Post by ericd »

llao wrote: post #2

> Machine learning enables Twitter to drive engagement, surface content most relevant to our users, and promote healthier conversations. One that wants to manipulate your mind, one that echochambers your discovery, one that censors arbitrarily.

ML is like a genie in that it is very good at optimizing exactly what you tell it to, and so you need to think long and hard about what you're telling it to optimize, because it might turn out to be bad proxy for what you really wanted.

Re: Twitter meets TensorFlow

#34

Post by nl »

pteredactyl wrote: post #28
xnxn wrote: post #21

Earlier quoted context omitted.

> Easy. If you're spectating, maybe. Completely falls apart when you try to engage in dialogue on Twitter, which is what both Twitter, Inc. and I want. Say I follow someone because I like what they say. And I want to discuss what they're saying, or to explore existing discussions. I'm going into this ready to have a thoughtful debate or two. So I open the replies, and they're what I consider to be garbage: flamewars,…

Replies with the most upvotes are at the top. That generally filters out the BS. There is a date posted versus upvote count balance that needs to be reached, but ML is not required. And this all assumes you're trying to have conversation around someone with many many followers. If you're in a small circle, none of your argument applies. Further posts by the original poster are at the top too. Yes, you may have to fil…

If you're in a small circle, none of your argument applies.

Try being a woman or Jewish and have a conversation on Twitter about - say - gaming.

Re: Twitter meets TensorFlow

#35

Post by michelb »

Maybe they can use ML on the user feedback to figure out what features people actually would like on the platform, instead of trying to figure out relevancy, which no company has ever successfully done. /s

Is there a recent in-depth article somewhere about Twitter's internals? It must be frustrating working on features very few people want to use.

I still can't edit a tweet I just posted, any video looks absolutely horrible for the first 10 seconds, the timeline is a mess, third-party developers that make interesting/much better clients are getting stomped on, and harassment is running mostly unchecked on the platform. Yet I read interesting development articles on the engineering blog. Wasted talent?

I really like the Twitter engineering blog articles, but it seems like it's just an HR tool.

Re: Twitter meets TensorFlow

#36

Post by pavanky »

mlthoughts2018 wrote: post #12

This is very confusing and meandering. It gives flow charts and lists of steps that don’t map to my experience building deep learning models at scale, and spends a strange amount of time passive aggressively dismissing Lua Torch and extolling virtues of TensorFlow that aren’t very important. As with all of these purported pipelining systems, I’m skeptical and happy to let a bunch of other people deal with the headche…

> Possibly attractive for people who just like deep C++ platform building, which is an internal drive not often found in people wanting to solve business problems with ML models.

And the world has plenty of people who are not interested in trying to solve business problems with ML models, but are rather interested in the engineering side of ML. I am one of those people. My current work (at cortex) involves improving the time taken to train the types of models not usually described in research papers.

If anyone is interested in machine learning but wants to build high performance training / serving platform, message me over twitter (@pavan_ky), Cortex is hiring.

Re: Twitter meets TensorFlow

#37

Post by blauditore »

dirkgently wrote: post #16
llao wrote: post #2

> Machine learning enables Twitter to drive engagement, surface content most relevant to our users, and promote healthier conversations. One that wants to manipulate your mind, one that echochambers your discovery, one that censors arbitrarily.

Do you remember hiw bad YouTube comments have been? And it's significantly better lately? That happened due to ML. Not everyone is out there to use ML for nefarious purpose. And there are multiple use cases for ML.

At least for music videos, comments are still pretty shitty. It feels like more than half of them are one of the following patterns:

- "Like if you're watching in June 2018?" [2k upvotes]

- "Most underrated artist of our time" [5k upvotes]

- "Wow, mad respect for " (written by verified account by other artist trying to promote their own content)

Re: Twitter meets TensorFlow

#38

Post by malcolmgreaves »

ericd wrote: post #33
llao wrote: post #2

> Machine learning enables Twitter to drive engagement, surface content most relevant to our users, and promote healthier conversations. One that wants to manipulate your mind, one that echochambers your discovery, one that censors arbitrarily.

ML is like a genie in that it is very good at optimizing exactly what you tell it to, and so you need to think long and hard about what you're telling it to optimize, because it might turn out to be bad proxy for what you really wanted.

This is a super insightful analogy! Thank you.

Re: Twitter meets TensorFlow

#39

Post by ckastner »

mindcrime wrote: post #7
llao wrote: post #2

> Machine learning enables Twitter to drive engagement, surface content most relevant to our users, and promote healthier conversations. One that wants to manipulate your mind, one that echochambers your discovery, one that censors arbitrarily.

Just to play Devil's advocate: One that wants to manipulate your mind Like your post here? Or my present reply to it? And so on... one that echochambers your discovery Which is good, because nobody has enough time in the day to process every conceivable byte of information they might stumble across... one that censors arbitrarily OK, because while everyone may have the right to speak freely, not all speech needs to b…

>> One that wants to manipulate your mind

> Like your post here? Or my present reply to it? And so on...

Except that Twitter thrives on controversy. There's controversy on HN as well, but escalations lead to flagging of content, not promotion of it.

>> one that echochambers your discovery

> Which is good, because nobody has enough time in the day to process every conceivable byte of information they might stumble across...

Strawman. This statement isn't about quantity, it's about content. Focusing on information that reinforces one's one view, instead of engaging in critical thought, is a dumbing-down.

>> one that censors arbitrarily

> OK, because while everyone may have the right to speak freely, not all speech needs to be heard by everyone...

Strawman. This isn't about what gets filtered, but who filters and how this information gets filtered.

Re: Twitter meets TensorFlow

#40

Post by rekshaw »

blauditore wrote: post #37
dirkgently wrote: post #16

Earlier quoted context omitted.

Do you remember hiw bad YouTube comments have been? And it's significantly better lately? That happened due to ML. Not everyone is out there to use ML for nefarious purpose. And there are multiple use cases for ML.

At least for music videos, comments are still pretty shitty. It feels like more than half of them are one of the following patterns: - "Like if you're watching in June 2018?" [2k upvotes] - "Most underrated artist of our time" [5k upvotes] - "Wow, mad respect for " (written by verified account by other artist trying to promote their own content)

28 people hate don't appreciate art!!1 [video has 28 dislikes]
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