Artificial Intelligence is becoming the heart of modern software development practices. Almost every week sees the emergence of a new large language model, coding assistant or some sort of AI-based SaaS application. For us, developers, the tools have become absolutely amazing and make our work easier.
However, while everyone is obsessed with the generative AI, another revolution is going on in those industries where there is no web interface.
This revolution takes place at the junction of software and physical world.
Introducing A IoT or Artificial Intelligence paired with the Internet of Things.
The Other Side of AI
Today most of AI applications deal with digital input: documents, chats, images or even code.
Industrial operations work differently.
Industries like factories, logistics, energy or construction create huge amounts of sensor data generated by machines, equipment, cameras, RFIDs, GPS devices and many other connected pieces of hardware.
Collecting this data is good.
Making sense of it in real time becomes revolutionary.
And that's when AI becomes not just another chatbot but an engine of operations. Data Is Ubiquitous. Intelligence Is Not.
Many companies have already deployed connected devices in their infrastructure.
It's not about gathering more data.
It's about solving questions like:
What device will likely break soon?
Where has the crucial inventory gone?
Why has production slowed?
What workflow causes the most delay?
How to predict safety hazards rather than document them?
Traditions dashboards only show you what happened.
AI predicts what will happen next—and what to do next.
Creating AI in the Physical World Is a New Kind of Engineering Challenge
Creating A IoT is not just about plugging an LLM into an API.
It's about considering:
Sensor quality
Streaming data infrastructure
Edge vs. Cloud computing
Device networking
Hardware engineering
Latency constraints
Security concerns for distributed devices
Scaling across thousands of connected devices
You're creating software that works within physical processes, where reliability is more important than innovation.
The A IoT stack Data Is Ubiquitous. Intelligence Is Not.
Many companies have already deployed connected devices in their infrastructure.
It's not about gathering more data.
It's about solving questions like:
What device will likely break soon?
Where has the crucial inventory gone?
Why has production slowed?
What workflow causes the most delay?
How to predict safety hazards rather than document them?
Traditions dashboards only show you what happened.
AI predicts what will happen next—and what to do next.
Creating AI in the Physical World Is a New Kind of Engineering Challenge
Creating A IoT is not just about plugging an LLM into an API.
It's about considering:
Sensor quality
Streaming data infrastructure
Edge vs. Cloud computing
Device networking
Hardware engineering
Latency constraints
Security concerns for distributed devices
Scaling across thousands of connected devices
You're creating software that works within physical processes, where reliability is more important than innovation.
The A IoT stack Data Is Ubiquitous. Intelligence Is Not.
Many companies have already deployed connected devices in their infrastructure.
It's not about gathering more data.
It's about solving questions like:
What device will likely break soon?
Where has the crucial inventory gone?
Why has production slowed?
What workflow causes the most delay?
How to predict safety hazards rather than document them?
Traditions dashboards only show you what happened.
AI predicts what will happen next—and what to do next.
Creating AI in the Physical World Is a New Kind of Engineering Challenge
Creating A IoT is not just about plugging an LLM into an API.
It's about considering:
Sensor quality
Streaming data infrastructure
Edge vs. Cloud computing
Device networking
Hardware engineering
Latency constraints
Security concerns for distributed devices
Scaling across thousands of connected devices
You're creating software that works within physical processes, where reliability is more important than innovation.
The A IoT stack Data Is Ubiquitous. Intelligence Is Not.
Many companies have already deployed connected devices in their infrastructure.
It's not about gathering more data.
It's about solving questions like:
What device will likely break soon?
Where has the crucial inventory gone?
Why has production slowed?
What workflow causes the most delay?
How to predict safety hazards rather than document them?
Traditions dashboards only show you what happened.
AI predicts what will happen next—and what to do next.
Creating AI in the Physical World Is a New Kind of Engineering Challenge
Creating A IoT is not just about plugging an LLM into an API.
It's about considering:
Sensor quality
Streaming data infrastructure
Edge vs. Cloud computing
Device networking
Hardware engineering
Latency constraints
Security concerns for distributed devices
Scaling across thousands of connected devices
You're creating software that works within physical processes, where reliability is more important than innovation.
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