Tag: AIoT

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Branding for Non-Human Audiences in the AIoT Era

Around 2024, Tesla began phasing out its T logo. Part of this may have been to emphasize the text logo for brand recognition, but recently it seems even that text is disappearing. It feels like the company is moving toward the next stage of its brand design.

Ultimately, the text will vanish, and the shape alone will be enough for people to recognize it. In consumer products, this is the highest-level approach—an ultimate form of branding that only a few winners can achieve.

I’m reminded of a story from the Macintosh era, when Steve Jobs reportedly instructed Apple to reduce the use of the apple logo everywhere. As a result, today anyone can recognize a MacBook or iPhone from its silhouette alone. The form itself has become the brand, to the point where imitators copy it.

A brand, at its core, is a mark—originally a literal brand burn—meant to differentiate. It’s about being efficiently recognized by people, conveying “this is it” without conscious thought. One effective way is to tap into instincts humans have developed through coexistence with nature, subtly hacking the brain’s recognition process. Even Apple and Tesla, which have built inorganic brand images, have incorporated such subconscious triggers into product design and interface development, shaping the value they hold today.

But will this still be effective going forward?

The number of humans is tiny compared to the number of AI and IoT devices. For now, because humans are the ones paying, the market focuses on maximizing value for them. That will remain true to some extent. But perhaps there is a kind of branding that will become more important than human recognition.

Seen in this light, Apple, Tesla, and other Big Tech companies already seem to hold tickets to the next stage. By adopting new communication standards like UWB chips, or shaping products to optimize for optical recognition, they are working to be more efficiently recognized by non-human entities. Even something like Google’s SEO meta tags or Amazon’s shipping boxes fits into this picture.

In the past, unique identification and authentication through internet protocols were either impossible, expensive, or bound to centralized authority. But advances in semiconductors, sensor technology, and cryptography—along with better energy efficiency—are changing that. The physical infrastructure for mesh networks is also in place, and branding is on the verge of entering its next phase.

The essence of branding is differentiation and the creation of added value. The aim is to efficiently imprint recognition in the human brain, often by leveraging universal contexts and metaphors, or by overwriting existing ones through repeated exposure. I’m not a marketing expert, but that’s how I currently understand it.

And if that’s correct, the question becomes: must the target still be humans?
Will humans continue to be the primary decision-makers?
Does it even make sense to compete for differentiation in such a small market?

At this moment, branding to humans still has meaning. But moving beyond that, as Apple products adopt a uniform design and Tesla moves toward minimalistic, abstract forms, branding may evolve toward maximizing value by being efficiently recognized within limited computational resources. Uniformity could make device recognition more efficient and reduce cognitive load for humans as well.

We should design future branding without being bound by the assumption that humans will always be the ones making the decisions.

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Ride-Sharing Stations Paving the Way for the Autonomous Driving Era

When Uber first appeared, I experienced many innovations, but the greatest of them was freedom.
Without complicated procedures, and most importantly, the ability to get on and off anywhere — that was the real revolution of ride-sharing.

Unlike trains, there was no need to travel to a station; you could call a car to wherever you were. The convenience of that was an experience traditional taxis could never offer.

However, the disruptive convenience of ride-sharing inevitably clashed with the taxi industry. Perhaps as a result, many major facilities now designate specific pick-up and drop-off points, and the initial sense of freedom has been lost. In many cases, taxis occupy the more convenient spots. It’s likely a measure to protect the taxi industry, but as a user, it’s nothing short of disappointing.

It’s like if Uber Eats required you to pick up your food only from a hotel lobby — it would lose much of its appeal.

Right now, it’s as if commercial facilities and transport hubs are using ride-sharing infrastructure to create their own private stations. These are clearly separated from taxi stands, and a new kind of station is appearing every day. As long as there’s a road, they can be set up relatively easily, meaning that in urban planning, their number could grow indefinitely through private initiative.

Ride-sharing fares are higher than other public transport, so it’s not for everyone. It also can’t carry large numbers of people at once, making it unsuitable for major facilities. These are issues that building more ride-sharing stations won’t solve. But building a new train or bus station is something neither an individual nor a single company can easily do — it takes enormous budgets and years of time.

In the Tokyo Ginza area, where I’ve been based for the past few years, even taxis are restricted to certain boarding points depending on the time of day. I already consider that an inefficient station. On the other hand, I’ve recently seen more Waymo vehicles on the streets. If that’s the case, I wish they’d just turn those points into stations for autonomous vehicles.

And that’s when it hit me.

What will happen when autonomous taxis become more common?
What if autonomous taxis evolve into large, articulated buses like those in London?

That could create enormous value in the future — because it would actively leverage road infrastructure to intervene in the flow of people and goods. With the right approach, even areas far from expensive city centers could attract significant traffic and activity.

In other words, now is the time to start building ride-sharing stations. They don’t exist yet in ride-sharing–barren Japan, but future commercial facilities should absolutely include them.

Otherwise, such places will become locations where neither people, nor humanoid robots, nor drones will ever come close.

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How Nvidia’s Mirror World Is Changing Manufacturing

Watching Nvidia’s latest announcements, I couldn’t help but feel that the world of manufacturing is entering an entirely new phase.

Until now, PDCA cycles in manufacturing could only happen in the physical world.
But that’s no longer the case. We’re entering a time when product development can be simulated in virtual environments—worlds that mirror our own—and those cycles are now run autonomously by AI.

It’s clear that Nvidia intends to make this mirror world its main battlefield.
With concepts like Omniverse and digital twins, the idea is simple: bring physical reality into a digital copy, migrate the entire industrial foundation into that alternative world, and build a new economy on top of Nvidia’s infrastructure.

In that world, prototypes and designs can be tested and iterated in real time, at extreme levels of precision.
Self-driving simulations, factory line optimization, structural analysis of buildings, drug discovery, medical research, education—it’s all happening virtually, without ever leaving the simulation.

The meaning of “making things” is starting to shift.
Before anything reaches the physical world, it will have gone through tens of thousands of iterations in the virtual one—refined, evaluated, and optimized by AI.
We’ve entered a phase where PDCA loops run at hyperspeed in the digital realm, and near-finished products are sent out into reality.

This isn’t just about CG or visualization.
It’s about structures that exist only in data, yet directly affect actions in the physical world.
The mirror world has reached the level of fidelity where it can now be deployed socially.

In this era, I believe Japan’s role becomes even more essential.

No matter how detailed the design, we still need somewhere that can realize it physically, with precision.
In a world where even the slightest error could be fatal, manufacturing accuracy and quality control become the decisive factors.

And that’s exactly where Japan excels.

Things born in simulation will descend into reality.
And the interface between the two—“manufacturing”—is only going to grow in significance.

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Tesla Optimus will become infrastructure

The age of AI has already begun.

With ChatGPT, we can now generate text, images, voice, even video. It’s not “coming soon” — it’s already here.

But changing the physical world takes one more step: integration with IoT.
AI can process data, but it can’t touch the real world. That’s where robots come in — they allow AI to physically interact with reality. Optimus is a symbol of that.

Tesla Optimus is a device meant to carry us into the age of automation, without rewriting our entire society.
From AI’s point of view, it’s the interface to the real world.
No need to reinvent roads, elevators, or doors. Optimus — and other robots being built by Big Tech — are designed to move through the world as it is. They’re general-purpose labor bodies, built to help AI function inside existing human infrastructure.

What we’re seeing now is, I think, a robot plan to AIoT the world.
Everything will be connected, automated, decision-capable, and able to act.
And the reason robots need to be humanoid is finally becoming clear: they’re designed to fit into our world, not the other way around.

Automation will move faster than we expect.
Car companies might end up as manufacturers of “just empty boxes” — simple transport units. These boxes don’t need intelligence. In fact, automation works better when things follow spec, stay predictable, and don’t think too much.

In Japan’s case, I wouldn’t be surprised if the government eventually distributes robots like Tesla Optimus.
You give up your driver’s license, and in return, get a subsidy for a household robot. That kind of world might not be a joke — it might be real, and sooner than we think.

But the tech and quality needed to make those robots — that’s where Japan comes in.

Humanoid robots are hard to build. They can’t afford to break down. Batteries, motors, sensors, thermal systems, materials — all of it needs to be precise and reliable.
That’s exactly what Japan has spent decades getting good at.

Manufacturing and quality control — those might be Japan’s last strongholds.
And they’re exactly what the world is looking for right now.

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