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AI Technology

Our AI work focuses on machine learning that makes networks, codecs and devices smarter and more efficient.

AI focus

Artificial intelligence is moving from the data center into radios, video codecs and the chips inside everyday devices. We focus on the inventions that make that shift practical, efficient and reliable, and on bringing them to the companies building the next generation of connected products.

AI innovation in everyday life

The AI technologies we focus on are quietly improving networks and devices. Here are a few of the ways they make a difference.

Smarter Networks

Machine learning that adapts radio settings in real time for better coverage and capacity.

Efficient Video

Learning-based tools that compress video further without losing quality.

On-Device Intelligence

Compact models that run on phones and cameras, keeping data private and responses fast.

Energy Savings

AI that powers down unused network resources to cut energy use.

Better Images

Neural processing for clearer photos and video in low light.

Predictive Maintenance

Systems that spot network faults before customers notice them.

Featured

AI-Native Air Interfaces, Explained

Machine learning is being designed into the radio layer itself, letting networks adapt to conditions in ways fixed algorithms cannot. This paper explains what an AI-native air interface is, why it matters for 6G, and what it means for the devices and networks that will use it.

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Explore our AI focus areas in depth

Learn more about the research areas shaping AI in networks and devices.

Responsible AI

As AI moves into networks and devices, it needs to be efficient, reliable and trustworthy. The inventions we focus on help make that possible:

  • Compact models that run with less power
  • On-device processing that keeps personal data private
  • Predictable behavior for safety-critical systems
  • Standards-based approaches that work across vendors

Responsible AI is better for users, for industry and for society.

Our AI focus

Our AI work spans three connected areas.

Following what’s next in AI

We follow machine learning research for networks, media and devices.

  • Monitoring AI-native network research
  • Following learning-based video and image coding
  • Tracking efficient on-device models

The standards behind AI

AI is becoming part of the standards for wireless networks, images and video.

AI/ML for NRCellular
JPEG AIImage coding
NNCNeural network coding
VCMVideo for machines

AI Technology insights

The AI technologies we focus on are quietly improving networks and devices.

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