Operations & Scale

How Cloud Software Is Simplifying Airport Operations and Replacing Legacy Systems

As airports grow more complex, the real innovation lies in making their systems simpler, faster, and easier to act on

Updated

March 24, 2026 5:55 PM

An airplane parked at Josep Tarradellas Barcelona-El Prat Airport. PHOTO: UNSPLASH

Airports are some of the most complex systems in the world. Every day, they manage thousands of flights, passengers, crew schedules, gates and ground operations—all moving at the same time. But much of this still runs on older software that doesn’t connect well, making simple decisions harder than they need to be.

This is the gap companies like AirportLabs are trying to address. Instead of relying on multiple disconnected systems, their approach brings airport operations into one cloud-based platform. The goal is straightforward: take scattered data and turn it into something teams can actually use in real time.

In practice, this means combining core systems like flight databases, resource management and display systems into a single interface. When everything is connected, airport staff can respond faster—whether it’s adjusting gate assignments, managing delays, or coordinating ground crews. Rather than reacting late, decisions can be made as situations unfold.

Another shift is how this technology is built. Traditional airport systems often require heavy on-site infrastructure and long deployment timelines. In contrast, cloud-based platforms remove much of that complexity. Updates are faster, systems are easier to scale and teams spend less time maintaining servers and more time improving operations.

What stands out is the speed of adoption. Instead of multi-year rollouts, newer systems can be implemented in weeks, allowing airports to see improvements much sooner.

At a broader level, this reflects a familiar pattern seen across industries. As operations become more data-heavy, the advantage shifts to those who can simplify complexity. In aviation, that doesn’t just mean better technology—it means making the entire system easier to run.

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Artificial Intelligence

Can a Toy Teach a Child to Read Like a Human Would? Inside the Rise of AI Reading Companions

A closer look at how reading, conversation, and AI are being combined

Updated

February 7, 2026 2:18 PM

Assorted plush character toys piled inside a glass claw machine. PHOTO: ADOBE STOCK

In the past, “educational toys” usually meant flashcards, prerecorded stories or apps that asked children to tap a screen. ChooChoo takes a different approach. It is designed not to instruct children at them, but to talk with them.

ChooChoo is an AI-powered interactive reading companion built for children aged three to six. Instead of playing stories passively, it engages kids in conversation while reading. It asks questions, reacts to answers, introduces new words in context and adjusts the story flow based on how the child responds. The goal is not entertainment alone, but language development through dialogue.

That idea is rooted in research, not novelty. ChooChoo is inspired by dialogic reading methods from Yale’s early childhood language development work, which show that children learn language faster when stories become two-way conversations rather than one-way narration. Used consistently, this approach has been shown to improve vocabulary, comprehension and confidence within weeks.

The project was created by Dr. Diana Zhu, who holds a PhD from Yale and focused her work on how children acquire language. Her aim with ChooChoo was to turn academic insight into something practical and warm enough to live in a child’s room. The result is a device that listens, responds and adapts instead of simply playing content on command.

What makes this possible is not just AI, but where that AI runs.

Unlike many smart toys that rely heavily on the cloud, ChooChoo is built on RiseLink’s edge AI platform. That means much of the intelligence happens directly on the device itself rather than being sent back and forth to remote servers. This design choice has three major implications.

First, it reduces delay. Conversations feel natural because the toy can respond almost instantly. Second, it lowers power consumption, allowing the device to stay “always on” without draining the battery quickly. Third, it improves privacy. Sensitive interactions are processed locally instead of being continuously streamed online.

RiseLink’s hardware, including its ultra-low-power AI system-on-chip designs, is already used at large scale in consumer electronics. The company ships hundreds of millions of connected chips every year and works with global brands like LG, Samsung, Midea and Hisense. In ChooChoo’s case, that same industrial-grade reliability is being applied to a child’s learning environment.

The result is a toy that behaves less like a gadget and more like a conversational partner. It engages children in back-and-forth discussion during stories, introduces new vocabulary in natural context, pays attention to comprehension and emotional language and adjusts its pace and tone based on each child’s interests and progress. Parents can also view progress through an optional app that shows what words their child has learned and how the system is adjusting over time.

What matters here is not that ChooChoo is “smart,” but that it reflects a shift in how technology enters early education. Instead of replacing teachers or parents, tools like this are designed to support human interaction by modeling it. The emphasis is on listening, responding and encouraging curiosity rather than testing or drilling.

That same philosophy is starting to shape the future of companion robots more broadly. As edge AI improves and hardware becomes smaller and more energy efficient, we are likely to see more devices that live alongside people instead of in front of them. Not just toys, but helpers, tutors and assistants that operate quietly in the background, responding when needed and staying out of the way when not.

In that sense, ChooChoo is less about novelty and more about direction. It shows what happens when AI is designed not for spectacle, but for presence. Not for control, but for conversation.

If companion robots become part of daily life in the coming years, their success may depend less on how powerful they are and more on how well they understand when to speak, when to listen and how to grow with the people who use them.