Today, artificial intelligence is mostly associated with large cloud platforms and high-performance data centers.
However, a new development is increasingly gaining importance:
Embedded AI.
We discuss this today in an interview with Mark Richter-Taslaman, Key Account Manager at Telic.
What Does Embedded AI Mean?
With Embedded AI, AI models are executed directly on devices.
Instead of transferring large amounts of data to the cloud, information is processed locally and decisions are made directly on site.
Why This Approach Is Interesting
For many industrial applications, Embedded AI offers significant advantages:
- Faster Response Times
Decisions can be made immediately on the device.
- Reduced Data Traffic
Not every piece of information needs to be transmitted and stored.
- Greater Data Sovereignty
Companies retain more control over their data.
- Fewer Dependencies
Cloud infrastructures are used more selectively.
- Research as a Key Factor
At Telic, we are actively looking into how AI can be used efficiently on IoT devices.
"In the future, we may not even need to collect huge amounts of data to make decisions. Perhaps the device itself can already make many decisions." says Richter-Taslaman.
This development opens up new possibilities for intelligent machines, sensors, and industrial applications.
Challenges Remain
Embedded AI is still in its infancy.
The processing power available on devices is significantly lower than in data centers.
Therefore, models must be specifically optimized.
This is precisely where an exciting field of research currently lies.
Conclusion
The future of AI will not take place exclusively in the cloud.
Part of the next wave of innovation will take shape directly on the devices.
For companies, this means:
more speed,
more control,
more efficiency.
And that is precisely why Embedded AI will play a central role in the IoT market in the coming years.
