ResourceS
Blogs
Data Matters: Our thoughts and views on the state of digital data
How to Manage Hallucinations in Generative AI
Learn about managing hallucinations in Generative AI – uncovering what they are, why they occur, and strategies to effectively manage them.
The Power Of RAG: How Retrieval-Augmented Generation Enhances Generative AI
Learn the power of RAG, and how it enhances Generative AI models
Artificial General Intelligence vs Generative AI: Which is the Future?
Dive into the future of AI with AGI and GenAI. Understand their roles, practical applications, and potential synergies.
How to Manage Model Drift in Generative AI
Understand model drift types, and strategies for effective management. Ensure accuracy with monitoring, retraining, and representative data.
How Do You Source Training Data for Generative AI?
Explore the importance of sourcing quality training data for AI models, understand its role, and learn effective methods for data collection.
Data-Centric AI: Optimizing Data for Generative AI Fine-Tuning
Discover the data-driven revolution in AI fine-tuning. Explore the evolution, tools, and power of Data-Centric AI for enhancing generative models.
Reward Modeling for Generative AI
Explore the power of reward modeling, its role in shaping large language models, and its future implications, all in our latest blog post.
What is Generative AI?
Discover Generative AI: a machine learning sub-field creating diverse content. Understand its components, workings, and applications.
What is Prompt Engineering for Generative AI?
Learn about the importance of prompt engineering in generative AI models and how it influences the quality of AI-generated content.
What is Retrieval Augmented Generation (RAG)?
Dive into AI’s exciting advancement, Retrieval Augmented Generation (RAG), and discover its mechanism, benefits, and applications.