Listen to native speakers pronounce “azure” in real conversational contexts with synchronized timestamps and subtitles.
Because those are a lot faster, I can just set those as one.to Azure. It's part of the service.
translation uh there was a government service called Bashinhi so some of them had that expertise uh basically took uh chat GPT and then along with Bashini uh built an application inside of WhatsAppuh and invoking uh Azure open AI services to create this application for farmers uh and they did this pilot in a in a village in India in Bwan in Hariana and what happened therewas that uh farmers could speak in the natural language and this was essentially um grounded in the government's public uh benefit schemes which a lot of the farmers aren't even aware that they
So we threw back and forth a bunch of layout sketches.This is like bright azure seas and should really feel like summer.
through the web uh many of you will know that in the midnight in 2008 Microsoft made a splash or at least attempted toby developing its or introducing its Azure platform for development probably the most uh successful one from abusiness applications perspective is an extension of salesforce.com which we'll talk about a little bit later that uses
Seems like AI might also have a thing about sheep.So this again, is Azure's Vision API.And this is a picture I took in Scotland on vacation.
democratized this technology that was once in the nineties, for example, you needed equipment that cost hundreds of thousands of dollars to do compression. It was the size of a car,is basically powering every server online, right? Even at Microsoft cloud called Azure, I'm quite sure seventy, eighty percent of the servers are running Linux. All your Android phones are running
And obviously Google Cloud has a lot of offerings, but I think this kind of Gemini name brand is important for them to build.Google Cloud will continue to do well, but that's a more complex thing to explain in the ecosystem, because that's competing with the likes of Azure and AWS rather thanon the model provider side.
And so I think one thing that I've been exploring is how do we balance out creatingIf we look at machine learning, for example, if I'm using-- I don't know, in terms of Flow or Azure or whatever it might be for real-time face detection.
So image recognition algorithms do all kinds of really strange things, which leads us to giraffe sighting number two.So this is a herd of giraffe walking along a dirt road, according to, this is powered by Microsoft Azure's imagerecognition. So they tend to, these algorithms tend to see giraffes a lot.
French fries in and lined them up on the counter and they just flew out of the store. So, I thought, "OK, it's about home cooking." And so, what I like to do is go to specialty foodstores, but even sometimes I go to Milan and see the colors of the new fashions. And one year, I remember when I was doing my first book, they were doing cantalope and azureblue and raspberry together and I thought, "Oh, that's good for the colors of the book." And that's what I did. So, I think about something that I would wanna eat and I say this-- I'm
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