Human annotators in AI: Adding context & meaning to raw data
Let’s start with the basics: Who are data annotators? Data annotators are responsible for manually labeling and categorizing data, to ensure it’s understandable and useful for machine learning algorithms. This process, known as data annotation, involves tagging, reviewing, and validating various types of unstructured data, including text, images, video, and audio. The result is a […]
Your gen AI data roadmap: 5 strategies for success
Gen AI data roadmap to kickstart your journey 1 – Preparing for gen AI begins with a data strategy Data is the fuel of AI. For companies to fully leverage the potential of this technology, a strong data foundation is imperative. This involves addressing data management issues related to quality, security, transparency, integration, storage, and […]
How gen AI is transforming the role of human data annotation
5 key challenges of human data annotation in the gen AI era The potential of the global data collection and labeling market is immense, with a projected revenue of US$17 billion by 2030, growing at nearly 30% annually. Domain-specific models are driving rapid growth in specialized industry sectors, such as healthcare. Here’s why human data […]
Scaling generative AI: How companies are harnessing its power
Scaling generative AI: Benefits, risks, and limitations Before generative AI, traditional AI technology focused on solving well-defined problems. These traditional AI models were designed for specific tasks, such as text classification, entity extraction, and predictive modeling, limiting business applications to narrow domains. A glimpse back at McKinsey’s State of AI in 2022 reveals popular enterprise AI use […]
Gen AI Outlook: Key trends shaping its development in 2025
7 Key trends shaping gen AI in 2025 Domain-specific models Gartner predicts that by 2027, more than 50% of the gen AI models used by enterprises will be tailored to specific industries or business functions, massively more than just 1% seen in 2023. While foundation models are trained with colossal amounts of general knowledge data […]
Addressing data challenges with AI-powered solutions
Companies collect terabytes of data every day, but most of its potential remains untapped. Making sense of raw, unstructured information is one of the most pressing data challenges for organizations. For those using data to train their own GenAI models, the challenge is even more complex: not only do they need sheer volumes of data, […]
Data annotation for Gen AI: Sigma’s upskilling strategy
Data annotation for Gen AI demands new skills. Learn how Sigma upskills its team for creativity, critical thinking, and more.
Building ethical AI: Key challenges for businesses
What does ethical AI mean? Ethical AI can be defined as AI that incorporates ethical guidelines, including promoting individual rights, anti-discrimination, non-manipulation, bias reduction, and privacy into its core design (and ongoing maintenance). In other words, ethical AI is AI that’s built and maintained (via policies, processes, and teams) to adhere to the human and brand […]
Welcome to Sigma AI’s Blog
Welcome to Sigma.AI’s inaugural blog post! We have recently undergone many changes here at Sigma in order to provide an even more personalized and better service, emphasize our industry leading results, and highlight our extensive capabilities and experience in data creation, cleansing, labeling, and annotation. Sigma AI is dedicated to getting you the highest quality, […]