Spotify just unveiled its collaboration with Google Cloud’s AI tools, aiming to revamp the personalized podcast experience such as how we discover content and receive recommendations within their audio offerings.
They’re diving into Google Cloud’s LLMs (large language models) to deeply analyze their vast library—a staggering 5 million podcasts and 350,000 audiobooks—and enhance the metadata. The goal? Making more personalized podcast experiences and tailoring them to suit listeners’ tastes.
But it’s not just about revamping their library. Spotify is also jazzing up its podcast services by automating nearly 20,000 data pipelines. This move is all about lightening the load when it comes to tedious tasks. The result? A whopping 300% improvement in their number-crunching speed, a pretty impressive feat.
And wait, there’s more! Spotify’s been testing out a pretty nifty feature—a Voice Translation tool for podcasts. Imagine, the original podcaster’s voice, but the podcast speaking in different languages, all thanks to some pretty cool AI sorcery. They’re using cutting-edge technology, like OpenAI’s voice generation, to maintain that personal touch, no matter the language.
This marks a big leap forward in making podcasts more accessible, more personalized podcast, and no matter where you’re from. This move is all about using advanced AI and cloud tech to bridge language barriers and connect people worldwide.
Behind the scenes, Spotify has been busy shifting its data operations over to Google Cloud Platform (GCP). The idea is to focus more on the music and less on managing mountains of data. They’ve also migrated many of their microservices—the tiny bits that make Spotify work—from their old data homes to Google Cloud. And for their storage needs, they’ve partnered up with Google Cloud Storage and Google Cloud Datastore.
Spotify is using Google Cloud Pub/Sub and Google Cloud Dataproc to dive into data and figure out what gets listeners buzzing. That means smarter features and better recommendations. And they’re not stopping there—they’re even using AI and machine learning to decode what users want from all the data they collect.
All these tech moves have really powered up Spotify’s computing strength, streamlined tedious tasks, and put more focus on ensuring their data is top-notch. The result? More personalized and thrilling audio experiences for us listeners.
Since 2021, Google Cloud has been Spotify’s go-to cloud provider. And now, alongside beefing up recommendations, they’re eyeing Google Cloud’s AI to identify any “harmful” content. While the full details are still under wraps, Spotify’s already got rules against content that’s sensitive or risky, and they’re using a mix of tech and real humans to keep it in check.
Google Cloud’s AI tools will also be used to improve Spotify’s personalized podcast recommendations and audiobooks. LLMs will be used to “better understand patterns behind users’ favorite spoken content,” which will presumably result in better-tailored recommendations.
That way, Spotify can fine-tune their recommendations and make sure you get more of what you love. Right now, Spotify’s dishing out suggestions for new podcasts and episodes right on your home screen, along with a “More like this” section for each podcast. Both features can be hit-or-miss, as many users have noted.