321gogo

321gogo t1_ja3rjow wrote

I’d argue the opposite. 1. TikTok and YouTube are all popular because of the connection with the creator, much more than tv/movies. 2. These are so heavily centered around trends, which is another form of viewer to viewer connection. You feel a part of something bigger still. 3. These are still “social” media - comments and sharing are a huge part of the platform and popularity. 4. Customization takes effort from the viewer which is the opposite direction these platforms are trying to move in. The whole point of TikTok is they got rid of user discovery, lowering the barrier to entry and getting rid of the most common exit journeys for users.

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321gogo t1_ja2dgqq wrote

I don’t think people want this generally though. A huge part of media is being able to connect with others over it. On top of that most people are attached to the message the creators are trying to convey behind their art.

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321gogo t1_izrjlai wrote

What do you mean “figure it out”? I’m not familiar with the example, but this sounds like a fairly simple application of ML. At the end of the day it is just finding trends in extremely large datasets that humans don’t have the brain power to process. Just because humans can’t do that work doesn’t mean we can’t understand it.

For example with predicting the pregnancy. A human might try to predict this by working backwards. You can first just try to understand the persons age and if they are female. Not too crazy to figure out from purchase history. Maybe you see that the person is in a relationship because they started buying Mens shampoo. Maybe they started buying dogfood and you find in your training data people tend to have a child within a few years of getting a pet. Tons of little things that can point you in the right direction. Now a computer is just doing this but ramped up to the max. The applications are very simple, the computation is the part the is complex.

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321gogo t1_izqfe7j wrote

> they provide results that are difficult to understand

Care to elaborate on this? I’m no expert in AI/ML, but generally I wouldn’t say the results are difficult to understand. I think it’s pretty clear that computers can outperform humans by a wide margin in analyzing large sets of data. Most of these concepts are applications of this computing power.

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