- Generative AI
Generative AI survey results: Customers expect brands to be transparent
A survey conducted by TELUS Digital unveiled consumer concerns about misinformation and bias in generative AI. Learn more.
- Generative AI
Three ways RLHF is advancing large language models
Learn how reinforcement learning from human feedback helps AI models respond to complex human preferences, reduce bias and decrease the occurrence of hallucinations.
- Data Collection
Data governance with AI data collection
Robust data governance not only improves data quality, it offers a standard to ensure that data is consistent, complete and accurate. Find out more.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
Check out our solutions
Enrich your data with our range of human-annotation services at scale.
Learn more