Why AI Needs Semantic Technologies and Data Quality to Thrive

Artificial intelligence (AI) is undeniably powerful, but even the most advanced AI models are only as good as the data they’re trained on. While AI can perform impressive tasks like generating human-like text or predicting outcomes, it relies heavily on the underlying structure, meaning and quality of its data. That’s where semantic technologies and data quality come into play. These two pillars are crucial for AI to move from just being “smart” to being truly effective and reliable. This interesting topic came to us from Bio-IT World in their article, “AI Can’t Fix Bad Data: Why Semantic Technologies Are Key to R&D Acceleration.”

Semantic technologies refer to tools and frameworks that enable machines to understand, interpret and use data meaningfully. They go beyond raw data by attaching meaning to it, often through metadata, taxonomies or ontologies. Think of them as the glue that connects scattered pieces of information into a cohesive, understandable web.

AI often struggles with ambiguity and nuance. Semantic technologies add layers of context to data, helping AI systems make better decisions. It also standardizes data across systems. This ensures that AI can work seamlessly with data from multiple sources, whether it’s pulling medical records, financial data or customer behavior metrics.

Even with semantic technologies, poor-quality data can derail an AI project. AI models thrive on large datasets, but if those datasets are riddled with errors, inconsistencies or biases, the AI’s performance will suffer.

By combining the interpretive power of semantic technologies with the reliability of high-quality data, we can unlock AI’s full potential, ensuring it’s not just intelligent but also effective, fair and trustworthy. It’s not just about teaching machines to think; it’s about teaching them to understand.

Access Innovations knows information science. We also know AI and are uniquely positioned to get the most out of the new AI engines. We use various techniques to enhance your data and train focused language models so that you get better results.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.