Apple hires employees and licenses tech from AI podcast startup Huxe

Apple hires employees and licenses tech from AI podcast startup Huxe

We’re used to reading about novel ways of recruiting people en masse from another company, but a “reverse acqui-hire deal” was a new one to us. You’ll be aware of an acqui-hire deal, where one company – usually a major corporation – buys another outright in order to absorb the entirety of their staff and their skills. But the reverse of this is, apparently, when it hires a startup’s founders and core team, and pays a (presumably big) licensing fee for its technology – without actually buying the corporate entity itself. (One reason for doing this is to supposedly avoid hold-ups due to governments’ merger and acquisition oversight.)

With that in mind: this kind of hire ’n’ license is apparently what Apple have done with AI podcast startup Huxe, according to a new European Commission filing, as reported by MacRumors. If you’ve ever used Google’s Gemini Notebook podcast-making features – where you drop in a mix of sources and ask for an AI-generated podcast summary – you’ll have experienced something like what Huxe does, founded, as it was, by former team members who built that Gemini Notebook functionality. 

One obvious use of the tech could be for Apple to provide a service which lets its users spin up personalised podcasts in its Podcast or Music apps. Back in May, Spotify launched Studio by Spotify Labs, which can generate daily news briefings, playlists, or generate short podcasts with music mixed in. All of this underlines, essentially, what major tech companies providing streaming platforms have said all along: they’re not providing music streaming, they’re providing audio streaming. 

AI podcasts are just another step in upping the volume of the non-music content available, and removing media from the shared-community experience of a major album launch, or yet another true crime podcast – and instead making stuff that we very specifically want, as increasingly-atomised individuals. We’ll find out how we feel about that transition when we see how many people choose to use those functions.



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