Why inter‑annotator agreement is critical to best‑in‑class gen AI training
What is inter‑annotator agreement (IAA) and why is it important? IAA measures how consistently multiple annotators label the same content. It helps quantify whether annotation guidelines are clear and whether annotators share a reliable understanding. Common metrics: Even seasoned experts often show α = 0.12–0.43 in high‑subjectivity tasks like emotional attribute scoring, especially before refining […]
Why gen AI quality requires rethinking human annotation standards
From accuracy to agreement: A new lens on quality Traditional AI annotation tasks (e.g. labeling a cat in an image) tend to yield high human agreement and low error rates. Annotators working with clear guidelines often achieve over 98% accuracy — sometimes even 99.99% — especially when backed by tech-assisted workflows. But these standards don’t […]
Human insight in data annotation: Training creative gen AI
Insight in gen AI data annotation Traditional AI focused on pattern recognition and classification tasks, based on clearly defined labels. But generative AI brought a paradigm shift, striving to emulate human creativity and expertise. This requires a different approach to training data. Human annotators have evolved from labelers to insightful collaborators, enriching the data with […]
Precision in data annotation: What’s needed for gen AI models
Precision in gen AI data annotation Gen AI models learn to create novel content. However, for these models to be reliable and useful, their content should be grounded in accurate information and logical structures. In gen AI data annotation, precision extends beyond accurate facts; it also encompasses creativity and nuance. Precise outputs should be factually […]
Human touch in gen AI: Training models to capture nuance
Humanity in gen AI data annotation Data annotation is not just about accuracy and precision. It requires human expertise and careful oversight to ensure AI models interact with the world in a meaningful, relevant, and responsible way. Drawing from our most recent whitepaper, “Beyond accuracy: The new standards for quality in human data annotation for […]
Accelerating the new AI: Key insights from our latest whitepaper
The key to gen AI success? High-quality data powered by human expertise Building accurate and reliable generative AI models demands vast amounts of high-quality training data. Achieving this is easier said than done: it requires the right blend of efficient workflows, deep-domain knowledge, and human oversight. With over 30 years at the forefront of AI […]
What Humans Hear That Machines Miss: 10 Hidden Language Cues
Irony and Sarcasm What it is: Saying the opposite of what is meant, often with a tonal cue. Example: “Oh, fantastic job…” said with clear frustration. Why machines miss it: Literal interpretation of words leads to mislabeling intent. Pragmatic Implicature What it is: Inferring meaning beyond explicit words, based on context. Example: “It’s cold in […]
Inside Sigma’s 2025 CSR report: Driving positive impact
Making a difference: How Sigma is driving positive change Guided by Sigma’s core values, our Environmental, Social, and Governance (ESG) program shows how we create a positive impact for our employees, communities, and the planet. Here are a few key insights from our CSR report: Environmental responsibility We are taking steps to reduce our carbon […]
Behind the scenes of creating the book ‘Nature’s Palette’ with AI
The concept: Blending art, science, and AI We began by brainstorming coffee table book ideas that would appeal to a broad, international adult audience. AI generated a host of possible topics and then provided additional data on the popularity of certain topics and categories. Humans narrowed these options down to the most appealing. A book […]