{"id":263341,"date":"2026-05-29T12:00:27","date_gmt":"2026-05-29T04:00:27","guid":{"rendered":"https:\/\/www.grab.com\/sg\/?post_type=editorial&p=263341"},"modified":"2026-05-29T12:03:19","modified_gmt":"2026-05-29T04:03:19","slug":"from-bits-to-atoms-lessons-from-ais-leap-into-the-physical-world","status":"publish","type":"editorial","link":"https:\/\/www.grab.com\/sg\/inside-grab\/stories\/from-bits-to-atoms-lessons-from-ais-leap-into-the-physical-world\/","title":{"rendered":"From bits to atoms: Lessons from AI\u2019s leap into the physical world"},"content":{"rendered":"\t\t
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In the years since Grab first launched in Southeast Asia, we\u2019ve learned to operate in the world of bits: We orchestrate millions of rides and deliveries across the region, making sense of data streams and algorithms.<\/p>

Now, we\u2019re entering a new inflection point. As AI leaves the screen and enters the physical world, Grab is evolving into a bits-to-atoms company.<\/p>

It\u2019s the start of the era of embodied AI\u2014which is to say, AI that lives in physical hardware like autonomous vehicles (AVs), delivery robots, and other specialised robots deployed in the real world. We see robotics as very much part of the next stage of our evolution. We aim to be a global leader in urban embodied AI.<\/p>

No longer just a futuristic concept<\/h5>

We’re already well on this journey.<\/p>

Grab has an autonomous passenger shuttle service in Punggol, Singapore, under the Ai.R brand, since April 1st. You can go to rideair.ai right now and book yourself a ride there. This is the first deployment of autonomous vehicles in residential areas in Southeast Asia. It has already clocked over 40,000 kilometers and served over 3.8K public rides, without any safety incident.<\/p>

In terms of autonomous delivery robots, we have just announced our collaboration with the Punggol Digital District to deploy autonomous delivery robots there. We’re making headway in terms of practical experience, putting robots out there in the field.<\/p>

But let\u2019s take a step back to think about the challenges that exist, especially for a company like Grab that previously operated in the software space.<\/p>

The challenges are real and different from anything we’ve faced before. Software, and internet software in particular, exhibits the characteristics of zero marginal cost. So once you develop the software, and put it on the internet, distribution is almost free. Every incremental user you add, every incremental transaction doesn’t cost much. In contrast, every robot you build costs money. Every design decision you lock in, you’re committed to. If you need a new sensor after 4,000 units are in the field, that’s a real cost, not a simple redeployment.<\/p>

There are technical challenges as well. With software, if you change your mind about a design decision, it’s easy. You can just deploy the change and roll it out to users. Contrast this with robots. Let’s say you have several hundred robots out there and you need a new set of sensors. Upgrading or exchanging them comes with real costs.\u00a0<\/p>

Data is the third constraint. The internet is data-rich and allows fast feedback loops, especially at platform scale. The physical world isn’t. You have to collect it yourself, through your robots and physical sensors, which means the feedback loop is slower and smaller scale. Getting this right is what separates teams that improve quickly from teams that don’t.<\/p>

Solving these challenges is a work in progress. For one, we are investing into simulations and testing, both in closed and open courses. We make sure to get it right at a small scale before we scale up. We also ensure that we’ve laid the foundations for a solid data flywheel, where we have a feedback loop between data gathered by robots in the field and the training data that continuously improves the next generation.<\/p>

Beyond our own scale and abilities, we see partnerships playing a critical role, both in terms of supplementing our data collection, but also in terms of integrations. The more we operate, the more experience and data we collect, leading to smarter and safer deployment.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Not using tech for the sake of it<\/h5>

Off-the-shelf solutions don’t work here. We learned this the hard way with maps.\u00a0<\/p>

We found existing solutions just didn\u2019t have the coverage of Southeast Asia that we needed: For example, small side roads that only two-wheel vehicles can access weren\u2019t mapped. So we built our own: GrabMaps. Today, our operations run 100% on GrabMaps. It’s given us a massive competitive and cost advantage and it’s become a commercial asset, with companies like AWS and Microsoft engaging us as partners to access our mapping data.<\/p>

A similar philosophy applies to how we build our robots and our deployments of AVs in Southeast Asia.<\/p>

First and foremost, we have to understand that people will be comfortable with robots when they see real value created by it. Don’t start from the technical solution. Start with the customer problem.\u00a0<\/p>

In deliveries, for instance, we observe that about 70 percent of food deliveries cover over two kilometers. The real pain, from the perspective of drivers, is in the first- and last mile: meaning the part of the food pick up and delivery that involves parking, waiting at the restaurant, navigating an apartment complex, and so on. We find that about 10% of our driver time is actually occupied by these \u201ccounter-to-curb\u201d and \u201ccurb-to-couch\u201d stages of the journey.<\/p>

If these stretches can be augmented by robots in specific locations, that would be a win for drivers AND consumers. It results in time savings each trip, which potentially means more trips for each driver-partner, and thus improved earnings. As such, we believe in a hybrid future where robots don’t replace drivers but complement them, giving them \u201csuperpowers\u201d.<\/p>

In the context of autonomous vehicles, for example, we understand that there are gaps in driver supply at specific locations and timings in our cities. Complementing them with AV offerings\u2014as we have done in Punggol\u2014creates a more reliable and sustainable transport network.<\/p>

The existence of robots will also create new job opportunities. Safety drivers, remote operators, data labelers, and so on.<\/p>

Cities that work better<\/h5>

The end-goal isn’t a flashy robot. Even as a technologist, it’s easy to get carried away with the coolness of the technology. The real question is: how do we make the city work better because of robots?.<\/p>

Imagine a systems-level view of a city where a hybrid network seamlessly dispatches a robot to meet a delivery partner at the curb, or an AV to get you home safely at 3 AM.<\/p>

People will trust something when they see it creating value for them. We seek to work together with partners in the public and private sectors to bring them along for the journey and ensure safety at every stage. When that\u2019s the foundation, new opportunities will emerge from this technology as well.<\/p>

*<\/p>

Header image: Suthen Thomas, Chief Technology Officer at Grab, speaking at the Asia Tech X Singapore Summit 2026.<\/span><\/i><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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