AI Technology

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AI: Innovate with Confidence

It's a brave new world for engineering. From data centers to smart cars, artificial intelligence (AI) and machine learning (ML) are changing the way we design, validate, and deploy cutting-edge innovations. Explore Keysight's AI technology and insights to disrupt the status quo and bring bold new breakthroughs to market.

Learn the fundamentals of AI

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Report

Innovating on 6G with Artficial Intelligence

Discover end-to-end capabilities for simulating, testing, and evaluating networks and devices as 5G systems evolve towards 6G.

Juniper and Keysight: Building Next Generation AI Networks
AI Industry Solutions
AI Data Center Solutions
Executive Perspective: Keysight AI Portfolio

AI Technology is Shaping the Future

Artificial Intelligence (AI) is transforming modern product design. Keysight integrates AI technology across the development lifecycle to enable faster product design and development. Discover how Keysight can help you accelerate your next innovation in a range of emerging AI-driven use cases.

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Improve efficiency & agility

AI leverages high-quality data to expedite product development and reduce the cost and time needed to bring better products to market.

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Fast-track time to market

Integrating AI technology into workflows accelerates time to market, improves productivity, and enables companies to quickly scale product development.

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Streamline development

AI and digital twins allow product development teams to automate repetitive tasks and reduce skillsets required to troubleshoot issues.

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Accelerate innovation

AI-driven tools boost product confidence by eliminating speculation in the design process, improving both the usability and customer experience.

Dive deeper into AI with self-paced learning

Bootcamp

AI Networking Essentials

Course

Revolutionizing 6G Research Using AI-Driven Design

Bootcamp

Automated Testing for High-Speed Digital Standards

Explore our AI technology-powered tools

AI Workload Emulation

Optimize AI Data Centers with Real-World Emulation

Keysight AI (KAI) Data Center Builder delivers highly tunable AI workload emulation, pre-packaged benchmarking apps, and dataset analysis tools to improve the performance of AI / ML cluster network fabric.
Software Test Automation

Improve Quality with AI-Powered Software Testing

Eggplant AI-powered test automation software leverages model-based digital twin testing and artificial intelligence to supply extensive coverage, optimized user experience, and accelerated release cycles. This secure, user-friendly solution tests any type of software on any platform or device.
Circuit Design

Level Up EDA with AI-Assisted Circuit Design

Next-generation EDA software gives engineers new tools and enhancements to bring efficiencies into their printed circuit board (PCB), RF and microwave, 5G / 6G, and high-speed digital design flows.
Ethernet Testing

Validate AI-Ready Interconnects and Infrastructure

Test the reliability, stability, performance, and interoperability of Ethernet devices and interconnects that use 212 Gb/s electrical lane interfaces, including silicon chips, optical transceivers, active / passive cables, and networking equipment.
Radar Scene Emulation

Train the AI Algorithms that Power Self-Driving Cars

Radar Scene Emulator (RSE) helps train algorithms to interpret radar reflections detected by automotive radar sensors. Keysight’s first-to-market technology combines hundreds of miniature radar target simulators into a scalable screen that can emulate objects with extreme precision.

Discover our AI-driven use cases

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AI Data Centers

Emulate AI Data Center Workloads

Emulating AI Data Center workloads requires a consistent, repeatable, and scalable testing methodology. Learn how to optimize network and data center infrastructure for AI training performance and efficiency.

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Apply AI to 6G Channel Modeling

6G requires advanced technologies to meet ambitious performance goals. Learn how AI-driven models can enhance real-time adaptability and performance — enabling dynamic responses to channel impairments and environmental changes.

AI Data Centers

Test PCIe Interfaces

PCIe technology is widely used for the interconnect of CPUs / GPUs and AI accelerators. The high-speed serial interface minimizes latency and allows scalable system architectures independent of the underlying ASIC technology.

Software Testing

Automate Mobile Device Testing

Learn how to use AI-driven computer vision to ensure reliable Android app performance across devices and OS versions with GUI-level dynamic element validation and model-based testing.

AI Data Centers

Test AI Data Center Networks

Learn how to emulate AI / ML workloads in a lab environment to benchmark and measure network fabric performance using high-density traffic generators​​ and specialized software for repeatable results.
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Frequently asked questions about AI

The four types of AI technologies are grouped based on how closely they match humans’ intellectual capabilities:

 

  • Reactive Machines: simple, rule-based systems that do not use past experiences in decision making.
  • Limited Memory: learning models based on large datasets that leverage previous experiences to optimize results. This is where most AI systems are operating today.
  • Theory of Mind: a system that understands human emotions and is able to interact and act appropriately. Theoretical research is currently underway to develop this AI technology.
  • Self-Aware AI: a system that has independent thoughts and feelings, possesses consciousness, and is self-aware. This AI technology could theoretically be available in the future.

Industries being transformed by AI technology include education, entertainment, healthcare, retail, finance, agriculture, legal, transportation, and others. Existing features are being rapidly adopted, and new capabilities are coming online at an accelerated pace. Three examples of AI-powered applications are automated notetaking during doctor’s visits, chatbots, and self-driving cars.

As AI-based systems are deployed with advanced features in important segments of society, there are numerous ethical considerations, including:

 

  • large amounts of personal data
  • lack of transparency in decision-making
  • unknown responsibility for wrong decisions
  • biased answers
  • intellectual property concerns
  • corporate and governmental misuse

As AI technology evolves, it's essential to ensure usage is in line with legislation and societal expectations.

There are numerous limitations for AI technology, including:

 

  • dependence on large datasets
  • propensity to generate false or fabricated results 
  • unknown or unproven ROI — especially where there are large capital investments in infrastructure
  • bias towards training data
  • power consumption (electrical and computational)
  • lack of proven and hardened security solutions
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Take the next step

Leverage Keysight's deep domain knowledge and industry-leading design, emulation, and test solutions to reap the benefits of integrating AI into your product development.

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