Most artificial intelligence models are trained through supervised learning, meaning that humans must label raw data. Data labeling is a critical part of automating artificial intelligence and machine learning model, but at the same time, it can be time-consuming and tedious work. A Korean startup called AIMMO, which uses software and humans to label and categorize image, video, sound, text and sensor fusion data, built an AI data annotation platform, enabling the data labeling faster for enterprises. AIMMO announced today it has raised $12 million in a Series A round to advance its data labeling technology and spur global expansions. Seven venture capital firms participated in the latest round: DS Asset Management, Industrial Bank of Korea, Hanwha Investment & Securities, S&S Investment, Toss Investment, Korea Asset Investment & Securities and Venture Field.

As machine learning (ML) technology improves and uses cases grow, more companies are employing ML to optimize their operations through data. As a branch of artificial intelligence (AI), ML is helping companies to make data-based predictions and decisions based at scale. The AES Corporation is a power generation and distribution company. They generate and sell power used for utilities and industrial work. They rely on Google Cloud on their road to making renewable energy more efficient.