In the digital era, artificial intelligence (AI) is becoming the foundation of most technological innovations. However, as AI becomes increasingly pervasive, a critical question arises: where should AI reside to truly create value? The answer is becoming clearer – at the edge, where data is generated and consumed.
1. A World of 30 Billion Devices and a New Challenge for AI
Today, our planet hosts nearly 30 billion edge devices: from smartphones, laptops, cars, XR glasses, wearables, drones, and robots, to network infrastructure and industrial IoT systems. This is where data is continuously generated in real time, deeply embedded in the specific contexts of individuals and industries.
For many years, AI has primarily been trained and operated in the cloud, where computing resources are virtually unlimited. Yet in practice, not every problem needs – or should – be pushed to the cloud. Overreliance on cloud computing introduces latency, increases energy consumption, raises privacy concerns, and is ill-suited for scenarios that require instant response.
This is why Edge AI – artificial intelligence at the edge -has become an inevitable direction.
2. What Is Edge AI and Why Does It Matter?
Edge AI refers to running AI inference directly on devices, rather than sending data back to centralized servers. When intelligence is located close to where data is created, systems gain multiple advantages at once:
- Faster processing with lower latency
- Higher reliability without continuous connectivity
- Better security and privacy, as data does not need to leave the device
- Greater energy efficiency, ideal for battery-powered devices
The cloud is well suited for training AI models thanks to its vast resources, but inference should happen on-device. Otherwise, it’s like driving a Porsche to the neighborhood grocery store when walking or cycling would be far more sensible. AI inference, too, needs to be efficient, energy-saving, and accurate – right on the device you use.
3. The Convergence of Connectivity, Computing, and Intelligence
Over decades, successive generations of mobile technology (3G, 4G, 5G, and soon 6G) have built a global connectivity foundation, with roughly a ten-year innovation cycle per generation. In parallel, on-device computing power has been improving almost every year, enabling AI to become “smaller yet smarter.”
Today, a modern smartphone can run hundreds of AI applications—from image processing and real-time language translation to security and performance optimization. Personal computers powered by next-generation chips can operate hundreds of AI copilots, becoming true companions for work and creativity.
4. Smaller AI, but Smarter and More Personalized
Unlike massive cloud-based AI models with trillions of parameters, Edge AI focuses on smaller models specialized for specific tasks. This specialization unlocks major advantages:
- High personalization, with deep understanding of user context and behavior
- Multimodality, combining data from cameras, sensors, voice, and biometricsParallel execution of multiple specialized models instead of relying on a single general-purpose model
More importantly, Edge AI forces AI systems to become more reliable, verifiable, and ethically compliant – especially in fields such as healthcare, agriculture, transportation, and smart cities. This does not simplify computer science; on the contrary, it demands that engineers become better system architects than ever before.
Innovation Only Matters When It Is Applied
No matter how advanced, technology has no value unless it is applied in real life.
In many countries, including Vietnam, startups are applying Edge AI to highly practical problems: sustainable agriculture, robotics, smart cities, industrial systems, healthcare, and emerging domains such as drones and space technologies. What they share in common is not “doing AI for the sake of AI,” but using AI as a tool to solve concrete problems and generate real economic value.
5. Vietnam and the Opportunity in the Edge AI Era
The global technology ecosystem is witnessing a new convergence in Vietnam: national technology strategies, a strong entrepreneurial spirit, and a growing pool of high-quality AI talent.
With a solid foundation in mathematics, a young engineering workforce, and increasing attention to intellectual property, Vietnam has the opportunity not only to adopt Edge AI, but also to create innovations with global impact.
