Amazon has added a new bedtime feature, called Sleep Studio, to its Echo Kids lineup. It gives children access to a curated library of sleep-focused content, including guided meditations, soundscapes, and stories from Calm, Headspace, and Moshi. The feature is included with Amazon Kids+, a subscription that comes bundled with Echo Dot Kids and Echo Pop Kids.

How it works

Parents set up sleep schedules and build playlists through the Amazon Kids Parent Dashboard. About 30 minutes before bedtime, the Echo device automatically starts playing the queued content. Kids can also trigger Sleep Studio themselves by asking Alexa, which Amazon says helps build independent sleep habits.

Amazon’s Echo Glow can also pair with the feature to add a visual cue through color-coded lighting that signals the start of a sleep window.

Content partners and availability

The content library draws from three partners. Calm contributes meditation content, lullabies, soundscapes, and sleep stories. Headspace offers wind-down content developed by child psychiatrists and pediatricians. Moshi, the kids-focused audio brand from Mind Candy, adds bedtime stories set in the Moshi Monsters universe.

Amazon says the feature was designed with child sleep research in mind, pointing to National Sleep Foundation data showing nearly half of US children do not get the recommended amount of sleep. Sleep Studio is now available on the Echo Dot Kids, Echo Pop Kids, and any Echo device with an Amazon Kids+ profile enabled. It gives Amazon’s Echo Kids hardware a clearer value proposition in the children’s tech market, where dedicated sleep apps and smart night lights have carved out a loyal audience among parents.

For years, your phone’s Camera Roll has served dual purposes. In addition to helping you revisit special moments, it has also served as an archive for all sorts of things you find online, like recipes, fashion inspiration, travel ideas, interesting quotes, funny tweets, product recommendations, and more. Today, a new app called Pool is arriving to help you finally make sense of this digital clutter.

To get started with Pool, you simply give it permission to access your photos, which are moved into categories it calls “pools.” The pools created in the app are entirely dependent on the products, places, or things that you’ve saved over time, making them specific to you.

The app is one of many reinventing bookmarking in the AI era. Startups like mymind, Fabric, and Raindrop help users organize links, images, or other saved content, but Pool focuses specifically on screenshots and then uses AI to help users rediscover and act on things they intended to revisit later, similar to apps like Captr or Sorti.

Once imported, Pool is able to track down the original link associated with a given screenshot. For instance, if the screenshot was of a product you were thinking of buying, it would link to the retailer’s website. If it was a recipe you saw on Instagram, it could pull up the ingredients and instructions the creator had shared. And so on.

The idea, explained Pool co-founder Maxime Junique, came about because both he and his co-founder Piet Terheyden had faced the same problem: They would screenshot things they wanted to remember, but then could never find them again.

“It sounds pretty obvious, right now, when we say it, but it’s something that we do so naturally — you don’t notice it, necessarily,” said Junique. The founders, who met years ago in a co-working space, asked their friends about the issue. The friends agreed that they would often screenshot and forget things, too, like design ideas or other types of inspiration.

The app was actually the first product to emerge from Spinoff Studio, the founders’ product and design studio, around three years ago. The first version was built in Lisbon over a couple of weeks while the founders lived out of a van, cranking out the landing page, website, and initial build. But they soon realized they needed to build some products that made money first, so they pivoted to B2B SaaS and shelved Pool.

The studio went on to build other products, including the CRM software Waitless, which was acquired last year.

What brought Pool back to life was the maturation of AI. Suddenly, its core idea of making sense of personal, largely unstructured datasets seemed feasible.

“We were like, it seems like a perfect time to go after this idea,” Junique told TechCrunch. “And it also seemed to us like it’s a super untapped, unexplored dataset for AI. Everyone goes after emails, bank transactions, chat logs — all of those productivity-first datasets. Who is going after this really, deeply emotional dataset we all own?”

Pool’s app also treats your screenshots like memories, meaning some of them are more relevant at the moment, while others disappear over time.

For example, if you screenshot the barcode to an event ticket, it could disappear later on after the event has taken place. Meanwhile, if you screenshot a flyer on Instagram about an upcoming event, Pool’s AI agents can help you find where to buy the tickets and link to the ticketing site.

To find things in Pool, you can search or ask its built-in AI assistant for help.

Next up, the founders plan to take this concept into a second, separate app that will operate as a personal assistant of sorts. Pool’s mascot — the little rubber duck you press and drag across the screen to enter Pool at launch — will become part of the brand for this agentic AI app they’re planning.

The founders were in Lisbon when we chatted — no longer in a van! — but were headed to San Francisco in late May to meet with investors. The startup previously raised a pre-seed round of just over $2 million from General Catalyst, Kima Ventures, Paris-based Source Ventures, and other angels, including Winston Du, Julian Blessin, and Thomas Ricouard.

Pool is available now as a free download on iOS.

The streaming service that taught a generation to scroll endlessly now wants to sell them the cure. At the Bloomberg Tech conference in San Francisco on Wednesday, Netflix’s chief product and technology officer, Elizabeth Stone, said the company is deploying generative AI to help subscribers cut through the volume of content it has spent two decades piling up.

The framing was telling. Stone described “a consumer frustration that’s brewing, which is, there’s so much content. How do I make sense of it, and what’s right for me, and what’s right for me in this moment?” The frustration is real, and Netflix is closer to its source than most.

Stone said generative AI and natural language processing are already being used to help viewers pick shows based on mood, and that the company is testing a voice interface among other experiments aimed at sharpening recommendations. The pitch is for an experience that is “more personalized, more interactive, more immersive,” in her words.

None of this is a small adjustment to a side feature. Recommendation is the product. Netflix has long held that the large majority of what subscribers watch comes from what the service surfaces rather than what they search for, which makes the discovery layer the part of the business most exposed to a better idea.

That better idea may be arriving from a competitor. Stone’s remarks land as YouTube continues to absorb television viewing time, a shift that has reframed the question for every subscription service. Keeping a viewer is no longer only about owning the title they want. It is about being the place where they decide what they want, quickly enough that they do not open another app instead.

The discovery push sits alongside a broader set of interface changes Netflix has been trailing, including short clips that play in feed and can be tapped to open a full title, save to a list, or pass to someone else. The clip feed and the AI recommendation work share a logic: shorten the distance between opening the app and pressing play.

There is an irony in the strategy that Netflix did not dwell on. The choice paralysis Stone wants AI to solve is partly a product of the company’s own catalogue strategy, the years of commissioning at volume that filled the grid faster than any human could sort it. The fix and the problem come from the same place.

Stone did not put a timeline on a wider rollout of the voice interface or detail which generative models are doing the work behind the recommendations. Netflix has said it is experimenting; it has not said when experiments become defaults. What is clear from San Francisco is the direction. The company that made the infinite scroll a habit now wants to be the one that ends it.