I took a research/nomadic trip to what has been called the place of necessary pilgrimage for anyone who is serious about being relevant in technology. China.
Honestly, the closest I thought I’d ever get to China was “Tintin in China” But oh how that story has changed.
What follows is really a digest of my impressions specifically regarding technology – so beware – from here on might be very technical for a lot of you, regardless and for what it’s worth, I suggest you find an excuse to go at least once, that your perceptions may receive realignment.
The dominant artificial intelligence conversation in the West is still centred on models and compute. That was not the conversation I encountered at MWC Shanghai, the technology conference I got myself into the minute I landed.
Across the conference floor, in technical sessions, industrial policy announcements and presentations from telecom companies, infrastructure providers, manufacturers and public-sector leaders, a different theme dominated: How are we building the infrastructure that will allow billions of intelligent systems to actively operate in the physical world? Forget chatbots.
It focused on what the future of factories, ports, robots, cameras, vehicles, satellites, utilities, warehouses, cities and public infrastructure looked like hinged on what speakers variously described as Physical AI, Embodied AI, Industrial AI, AIoT and physical intelligence.
China is not only trying to build more capable artificial intelligence. It is trying to build the operating system for an AI-enabled physical economy. It instantly made sense how they have the most deployed industrial robots: from factory floors to hotel lobbies.
How do you connect intelligent machines? How do you reduce the cost of the hardware? How do you process data at the edge? How do you maintain secure communication between devices? How do you support billions of realtime sensors? How do you create standards that allow systems from different companies and countries to work together?
The dominant Western AI narrative treats the model as the centre of the universe. In Shanghai, the model often appeared to be one layer inside a much broader industrial stack.
That stack includes chips, networks, sensors, devices, cloud infrastructure, edge computing, security, manufacturing, logistics, regulation and business models.
Intelligence is important. Granted. But intelligence without deployment infrastructure remains stifled.
A phrase that appeared repeatedly across several presentations was that the network would become the nervous system of the intelligent economy.
It baffled me why so much of the conference was devoted to 5G-Advanced, eRedCap, LTE-M, NB-IoT, satellite connectivity and non-terrestrial networks.
And then I began to see the big picture emerge from the noise. These technologies are being positioned as the communications layer for machines. Factories, vehicles, cameras, drones, meters, containers, robots and industrial equipment are all expected to become intelligent nodes within a distributed system.
The objective is not merely to connect more people. It’s to connect everything – not so far-fetched if one experiences the current Chinese ecosystem. Everything is linked. Everything.
One of the most important technologies discussed at the conference was eRedCap. I’d never heard of it. Yet it may become one of the more consequential technologies of the next decade.
Let me attempt to explain. Today, connected devices largely sit at two extremes. At one end are low-power technologies such as NB-IoT and LTE-M. These are designed for devices that transmit very small amounts of data, such as electricity meters, water meters, environmental sensors and simple asset trackers.
At the other end is full 5G, designed for high-bandwidth, high-performance applications such as smartphones, video streaming and ultra-low-latency communications.
But a growing number of intelligent devices sit between those two categories. AI cameras, industrial monitors, wearables, logistics systems and machines running edge intelligence need more bandwidth than a simple sensor, but they do not need the full cost, complexity and energy consumption of smartphone-class 5G.
eRedCap is being designed to fill that gap.
Several speakers described it as the missing middle layer of the cellular ecosystem. It offers more capability than traditional low-power IoT, while remaining cheaper and more energy-efficient than full 5G.
That makes it particularly relevant for the next generation of intelligent devices.
Traditional IoT was built around predictable behaviour. A meter would send a reading. A sensor would report a temperature. A tracker would report a location. The next generation of devices will behave differently. They will process multiple inputs, interpret context and make decisions at the edge. Their data requirements may change from one moment to the next.
One speaker described this as the shift from structured IoT to chaotic IoT. Chaotic doesn’t mean broken. It means dynamic and unpredictable.
Another recurring theme was that cybersecurity can no longer be treated as an optional feature. Before nko’?
The European Cyber Resilience Act was repeatedly cited as a major turning point for manufacturers of connected products. The argument was that the legislation will have an effect similar to GDPR.
GDPR began as a European privacy regulation, but its influence quickly spread beyond Europe because global companies had to redesign products and processes in order to continue serving the European market.
Manufacturers regardless of what end of the spectrum their devices sit on, will increasingly be expected to build vulnerability management, software updates, incident reporting, secure communication and lifecycle support into products from the beginning. Security therefore becomes a passport to market access.
The shift toward physical AI – this just means robotics, btw – also makes Edge computing more important.
Sending every camera feed, sensor reading and machine signal to the cloud is often too expensive, too slow and too inefficient. Makes sense. A robot will make immediate operational decisions at the edge.
The architecture is simple: the sensor captures information, edge AI interprets it, and only the relevant result is transmitted.
As more intelligence moves into devices, edge inference may become one of the largest computing markets of the coming decade.
The same infrastructure being developed for industry is also being applied to public safety.
A former technology leader and captain within the Hong Kong Police Force described the evolution in three stages.
The first stage is reactive surveillance. Cameras record what happened, and humans review the footage afterwards. Where we are now.
The second stage is proactive safety. AI systems analyse crowd density, movement patterns, flooding, traffic conditions and environmental signals in order to identify emerging risks. What Accra seems to need.
The third stage is what he described as autonomous resilience. Cameras, drones, robots, emergency services, transport systems and environmental sensors work together to coordinate a response. This sounds like the plot of every dystopian movie.
The most important point was that the value does not come from installing more cameras. It comes from active integration.
A public camera network can support policing, crowd management, flood monitoring, drainage management, disaster response and major public events if data can move safely across agencies.
The camera stops being a single-purpose surveillance device and becomes part of a larger urban sensing system.
The idea seems more amenable in a place like China than in places less used to a surveillance culture. But it could easily become the norm.
I’m not sure I was ready to be bombarded with the heft of information that I received on my very first day. And I must mention that there were some sessions of this conference I was plainly not allowed into because I wasn’t an official.
There was a conversation about autonomous vehicle tech that I didn’t get into which bummed me out because it was bound to be a continuation of the camera integration thing. President Xi was recently on his way somewhere and ALL Teslas on the highway he was meant to be traveling on were diverted onto a separate road. Just the Teslas. Turns out the reason was that they suspect the Tesla cameras of being able to be “hijacked” and used to take pictures of secret Chinese government buildings that he’d be visiting. Sit with that for a bit.
Then Huawei was launching something important which I actually tried to get into only to be told quite sternly by a girl who looked more like a humanoid robot -no joke- that I “was not an official”. Her security looked at me like I was a spy. I calmly stepped back. A bunch of men in suits walked briskly in soon after. Maybe it was my jeans.
Anyway. All this made me start thinking about here and how we risk repeating the same mistake we made during the internet era.
The opportunity for us is clearly beyond adopting AI tools. It’s to participate in the infrastructure, deployment, operations, data generation, maintenance, services and local applications surrounding them.
Africa has several advantages. We have rapidly growing cities, expanding infrastructure, young populations, mobile-first economies and many sectors in which legacy systems are either weak or absent.
These conditions create the possibility of building AI-native infrastructure. The opportunity is particularly strong in agriculture, logistics, utilities, financial services, healthcare, transport, public administration and urban management.
For Ghana, the use cases are already visible.
In agriculture, connected systems could support cocoa traceability, crop monitoring, logistics, disease detection and yield prediction.
At the Tema Port and across regional trade corridors, hybrid connectivity and IoT could improve container tracking, customs visibility and freight management. And curtail y’know… Ahem. One would think acfcta would get behind that. But they seem plagued with smaller issues.
In financial services, AI and connected systems could support fraud detection, transaction intelligence, branch operations and customer services.
In utilities, smart metering, predictive maintenance and grid visibility could reduce losses and improve service delivery.
In government, the same infrastructure could support tax administration, public safety, fraud analytics, environmental monitoring and more efficient public services. I talk a lot about this stuff in my previous piece so I won’t dwell here.
But capturing these opportunities will require local capability, governance, standards, partnerships, data strategy, infrastructure and a clear understanding of where value will accumulate. Plus, national resolve.
The conference on its own suggested a broader way to think about the AI economy. This was a rude awakening for Day 1 of my immersion. It was a culture shock – combined with getting a grasp of their closed payment, transport and transactional ecosystems.
Artificial intelligence as “on screen chatbot” tech is going away. No coincidence that I hear OpenAI is toying with speakers. I digress. The real opportunity for economic value depends on the interaction between intelligence, connectivity, energy, manufacturing capacity, security and deployment systems.
China appears to understand this clearly. Its governance system makes it the ideal testing ground to deploy it. It’s a no brainer that Dubai has a three year plan to mirror China’s level of tech integration. The EVs that the west won’t get have already inundated showrooms and streets from Dubai to Abu Dhabi.
The question for Ghana, Africa and the rest of the world is whether we’re even paying attention. I thought I was. But I was obviously very removed from reality. I think the Chinese deliberately have a closer off ecosystem to fend off a real awareness of what they abrew in their pots. These people are living in the future. And it’s “normal”.
While I was there, they would go on to usher in the first Embodied AI IPO with Unitree, which will make it the first chance the world has to invest in physical AI, have active discussions about blocking off Chinese models from the west, host a scary number of AI research, academia, supply chain and industry conferences, become the second entity to recapture a rocket a la SpaceX, while fending off typhoons. All in a day’s work.
We’re in for some very interesting days ahead.
-For Uncle Charlie and Baaba.
Until next time,
Spyda.