如何利用人工智能在OTT领域省钱

了解更多关于人工智能和流媒体的信息流媒体东部2022.

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Nadine Krefetz: Realistically, you're training a system with 信息 to look for certain things. And in 紫溪's case, you're training within the transfer side. In Michael's case, it could be on the production side or the monetization side. For Ethan, realistically, if you're not getting cost savings, what kind of value are you seeing? Because now we started to talk about the fact that you can have people doing other things, 但伊森, 例如, are there things that you are having delivered, 你在创造价值吗, that you could not create in another way?

伊桑Dreilinger: 从我们的角度来看, 你可以用另一种方式创造价值, but to create that value in another way would be far more costly than applying AI to it. And I think if you look at the economies of scale, it's not just an OPEX/CapEx discussion. 这是关于用户体验的. And then ultimately on the advertising side, what the value of that is. So you go back to like the first example that I had 在哪里, 就天气而言, 我只想知道花粉的数量, 正确的? All the rest of the stuff is just useful 信息 to me, but pollen count to me is actionable. We can start to target that because now the AI knows that that's of interest to me.

So you can start to send ads to me that are tailored to that. 它也让体验变得更好. 所以这边, 当我去看天气的时候, I'm gonna go back to the place that has that 信息 easy for me to find, making it simple and making my life better. Downstream of any AI that was applied, it makes my life better as an end user. 所以它回到堆栈中. It's the same as what Eric is doing at 紫溪, 在哪里, 在QoE上, if you can continue to deliver great streams of high quality, 我不会从上面掉下来的. I'm not going to say, that stream was awful. 我不想再回去了, 删除应用程序, because I know I'm gonna get a consistent experience. And I think there's a lot of value in that. It's not value that hits a ledger any在哪里, but it's value to the brand and to the end user.

Nadine Krefetz: But would you say you are able to create something with machine learning that you would not be able to create otherwise?

伊桑Dreilinger: 哦,绝对. 一次又一次, that goes into that application of AI or machine learning into your particular foundation. 以及你想用它做什么. We've done some projects 在哪里 we were creating highlights using AI, 不涉及人类, just creating highlights from different sporting events. We've done some stuff on the political side with residential and congressional debates 在哪里 you're pulling out the highlights of the debates and sort of matching up the responses. So they kind of make some sense and stuff along those lines. So there's a lot of value to be created there, Is there an audience for that? That's the next question you have to figure out. And then obviously there are some ways to use AI to find the audience for that stuff you've just created. 这可能不是一个好的商业模式, but you can then start to use those AI learnings that you've got. With what Michael's doing with transcriptions, 如果发现是下一步, 我们来看看这些转录, and feed them back into a natural-language understanding model. And then you can start to create derivatives of that programming and start to serve up some bite-sized pieces of programming that drive people back into full content. So there's lots of different ways to start to apply that and create value from it.