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  1. Illustration of person using smartphone, with floating speech bubbles symbolizing a conversation with a chatbot
    Generative AI

    Artificial intelligence, real benefits: Applying generative AI in CX

    Generative AI has seemingly limitless potential for brands who lead with their digital CX. Investigate the benefits of AI customer service.

  2. Illustration of two blocks of text running through an icon of a robot, meant to symbolize generative AI
    Generative AI

    Generative AI 101

    Generative AI is a type of AI that can be used to generate new content such as text, images, audio, video, code or synthetic data. Discover exactly how generative AI works and what you can do with it.

  3. Illustration of a diverse group of people standing in front of a globe, meant to symbolize impact sourcing
    Responsible AI

    The critical role of impact sourcing on AI model expansion

    Addressing bias in AI models is a key principle of responsible AI. Discover how diversifying your team of AI contributors through impact sourcing can help.

  4. Hour glass with sand falling
    Linguistic Annotation

    Are we headed for an AI data shortage?

    Discover how a potential AI training data shortage for language models could affect your business, and what you can do to offset its impact.

  5. A piggy bank falling into a robot hand
    AI Use CasesFinancial Services & Fintech

    Six AI technologies set to define the future of banking

    Artificial intelligence is set to define the future of banking. Learn about how banks are using machine learning, RPA and other AI-powered tech.

  6. Visualization meant to symbolize data classification
    Data Annotation

    What is data classification?

    AI data demands classification to be useful at scale. Learn the benefits, challenges and best practices of data classification.

  7. Illustration of a mountain made up of data that's topped with a flag
    Data Annotation

    Five common data annotation challenges and how to solve them

    Data annotation can create bottlenecks in AI and machine learning projects. Learn how to improve data quality and overcome data annotation challenges.

  8. Illustration of an assembly line with bugs being removed from computer code via automated arms, meant to symbolize quality assurance in AI training data
    AI Best Practices

    Quality assurance best practices for AI training data

    Training AI systems demands observing data quality best practices. Learn more about AI data quality control in this primer.

  9. model cars driving in the same lane
    Computer VisionAutomotive

    Does data hold the key to autonomous vehicle safety?

    Experts believe autonomous vehicles will substantially improve road safety. Discover how large, diverse and accurate datasets are enabling this vision.

  10. Illustration of various technology and icons meant to symbolize machine learning
    Data Annotation

    Data labeling fundamentals for machine learning

    Machine learning demands massive amounts of clean, structured, labeled data. Learn the fundamentals of data labeling for successful AI training.

  11. Two people with virtual reality (VR) goggles meant to symbolize the metaverse
    Computer Vision

    The expanding frontiers of computer vision in the metaverse

    Learn how computer vision will play a vital role in transforming the metaverse into a commercially accessible reality for brands across industries.

  12. Robotic hand interacting with an interface meant to represent artificial intelligence
    Data Annotation

    The contemporary trifecta of data-centric AI

    Data-centric AI is driving the success of current machine learning initiatives. Learn about the leading role of data in the AI lifecycle and the three key factors powering the data-centric approach.

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