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Why can’t you ask AI where your keys are? The simple answer is it doesn’t really know where anything is. In an abstract sense it does, like how we all know France is in Europe but it is singularly unequipped to parse spatial data in a way we all take for granted.
But, what if you could give AI an external sense of space? Making the world more AI accessible will be a true paradigm shift and will bring AI into physical world. This is our mission at Auki. We are continually surprised by what is made possible by giving AI access to this shared spatial data. And there are still countless applications that we haven’t thought of yet.
For example, what do you get when you combine an external sense of space, AR and Apple App Clips? The biggest XR product since Pokemon GO and the killer app for XR adoption.
Let’s take a look at a specific use case to see how this sense of space unlocks new possibilities.
It’s the weekend, the grocery store is full of families shopping for the week. The aisles are packed, you have one last item on your list and you’re exhausted. You can’t find toothpaste, but there is no staff in sight. Looking at the shelf in front of you, you see a sign with the text “looking for something?” and a QR code. You scan it. Within seconds and without downloading an app, you see a search field. You type toothpaste and are presented with a few product suggestions. You click. As if by magic, an arrow appears in augmented reality and begins guiding you down the aisles all the way to the toothpaste. You breathe a sigh of relief and walk product in-hand happily down the aisle. The whole process took seconds and didn’t stress you out with having to download an app or register an account.
We’ve all been there, walking down the aisles of a grocery store looking for someone to help us before eventually giving up in frustration. This isn’t an isolated case, only 11% of shoppers receive assistance within a minute of seeking help, while 44% receive no help at all. How many customers will keep looking for more than a minute and how many frustrated shoppers will keep coming back? With demographic changes and ever shrinking margins, this situation is unlikely to change. So obviously robots are the solution to this problem?
Well, yes and no. There is no question that robots will increasingly be called on to assist store staff in various capacities, but ultimately one of retail’s strengths is the ability to give in person customer service with a human touch. A 2020 study found that 64% of consumers prefer to engage with associates over robots while shopping in-store. These attitudes will shift over time but for some interactions a subset of customers will always prefer person-to-person interaction.
However, on the flip side a staggering 95% of customers do not want any interaction until they require assistance. So the solution isn’t to fill your store to capacity with either humans or robots but to employ intelligent solutions that allow customers to dictate how and when customer service interactions take place.
Case in point, in some specific scenarios customers prefer a technological solution: 85% of shoppers would rather use price scanners than ask a store associate for pricing information. In others, they prefer the human touch: 52% felt it was important to have knowledgeable in-store personnel help them make the final choice on tech related purchases.
Finding the right solution for each expectation is clearly key, particularly in novel scenarios where technology can enable new interactions, which fall outside previously available data. These new solutions will need to be evaluated case-by-case to establish whether they fall into situation A or B?
In the hypothetical scenario above, where a customer is looking for a product or a location, do they want an associate or something like a price scanner?
On the one hand, in a supermarket the customer has generally already decided that they want to buy the product in question and so any external sales pressure from an associate isn’t really a factor. However as with the price scanner, the answer to their question doesn’t require any subjective expertise. What is the price? Do you have the product, and if so, where? Add to this the lack of time for training, and in many cases associates can’t answer the question.
Another point in common with the price scanner is that the customer might want to repeat this interaction multiple times during a single visit. With the difficulty of finding an associate or even a robot if one were deployed in the store, customers are likely to feel frustrated. Especially since both robots and associates are finite resources, they do not scale well during peak times, causing more frustration as customers jostle for attention.
What if a device already existed with the sensors and spatial awareness to be able to guide customers to the product they are looking for? What if that device was already deployed to billions of customers with each customer already carrying it into the store? I am of course talking about smart phones.
A solution where customers can look up product locations and be guided to them on their smartphone has obvious upsides. Every customer has one, there’s no need to deploy expensive robots, and associates would be freed up for customer service tasks where they can add the most value.
Customers are already searching for products on their phones while walking down the aisles: 40% of consumers use their phones in store to research products and 36% use them while shopping to compare prices. These numbers don’t even include customers who keep their shopping lists on their phones. So clearly customers are used to looking up information on their phones while shopping, so what’s the hold up?
The first big hurdle is that most stores have no idea what’s really on their shelves or even where their shelves are in 3D space. Even if they do happen to have that information, none of them have the ability to share that information with customers in a streamlined way. This article won’t go too far into the weeds on this hurdle, suffice it to say that Cactus, our spatial AI platform for retail, can solve both those issues.
Once that hurdle has been cleared, the next big hurdle is getting the customer to access that information on their device. Industry standard conversion rates for retail customers to download a store specific app is reported to be as low as 5-15%. The vast majority of customers will not download an app, especially not in the frustrated situation outlined above. Trying to convert customers at their peak of frustration is unlikely to result good experiences and indeed only 44% of customers are somewhat satisfied with their experience of retailers apps.
This is despite 74% of customers expecting retailers to offer an app and 60% saying they are more likely to shop with a retailer that does. So this represents a huge opportunity for retailers if they get it right, leading both to a better customer experience and potentially to better customer retention. But how?
This takes us back to the hypothetical at the beginning of this article: imagine the customer cannot find an associate. Looking at the shelves, he sees a sign which says “can’t find what you’re looking for” and a QR code. The customer scans it and without downloading any app, within seconds he is presented with search field. He enters the product name or type and is presented with a list of relevant products. He clicks the product and his phone guides him in augmented reality to the product. The whole process took seconds and didn’t require any app downloads, account registrations or sign ins. The customer walks away happily with his product, much more likely to use this feature again.
This isn’t sci-fi, the technology exists. Combining the functionality of Apple App Clips (or Android Instant Apps) and Cactus’ Spatial AI makes it possible for customers to experience “App-less” augmented reality powered by spatial computing. We have already demonstrated that this is possible.
It could even alert the customer to the fact that there is a deal on this product. This could also give customers an incentive to download the full version of the app. Research indicates that consumers rank discounts and deals as the most valuable feature of mobile apps and conversion rates are around 20-40% for deal incentivized downloads. Particularly in a scenario where customers look up multiple products over multiple visits, the chance of converting a customer to the app is considerably higher, especially if the customer has already had a good digital customer experience so far.
Technically these experiences are not really “app-less”, they are small bit-sized experiences of a full app, again potentially streamlining the onboarding process for customers through interactions that provide value rather than friction.
In addition customers could begin adding value to the store, with customers able to flag products as out of stock or call staff through the “app-less” interface to resolve issues where a human is needed.
“App-less” AR has the potential to greatly improve the shopping experience by meeting the customer in the manner that they want at the time when they want it. The perfect complement to associates and robots, it combines three seemingly disparate technologies, App Clips, AR and retail spatial computing to create novel interactions between customers and stores, giving retailers the opportunity to create new, improved relationships with their customers and improve the workload for associates.
The technology that enabled the customer to navigate through the store is the same that allows robots and AI to do so.
This why making the world more accessible to AI and robots also makes it more accessible to humans. The ability to navigate through the store and find products can also be extended to shoppers with vision impairment or low vision. AI accessibility is part of a wider accessibility movement, since in future these technologies will help all participants engage with the physical world.
We think app-less AR is the biggest XR product since Pokemon GO. We are already deploying our external sense of space in thousands of locations and are aiming for 100,000 by the end of 2028.
The applications of making the world more AI accessible are only limited in the sense that reality is. App-less AR is just one example of an external sense of space combined with other existing technologies to create new possibilities. This is what Jensen Huang was talking about when he proclaimed that “Physical AI” would be the next step in the AI revolution.
Auki is building the Auki network, a decentralized machine perception network for the next 100 billion people, devices and AI on Earth and beyond. The Auki network is a posemesh, an external and collaborative sense of space that machines and AI can use to understand the physical world.
Our mission is to improve civilization’s intercognitive capacity; our ability to think, experience and solve problems together with each other and AI. The greatest way to extend human reach is to collaborate with others. We are building consciousness-expanding technology to reduce the friction of communication and bridge minds.
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The Auki network is a posemesh: a decentralized machine perception network and collaborative spatial computing protocol, designed to allow digital devices to securely and privately exchange spatial data and computing power to form a shared understanding of the physical world.
The Auki network is an open-source protocol that powers a decentralized, blockchain-based spatial computing network. Designed for a future where spatial computing is both collaborative and privacy-preserving, it limits any organization's surveillance capabilities and encourages sovereign ownership of private maps of personal and public spaces.
The decentralization also offers a competitive advantage, especially in shared spatial computing sessions, AR for example, where low latency is crucial.
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