Labelbox has had a productive start to the year, rolling out several new features aimed at enhancing the training and efficiency of AI models. Key updates include the integration of the Monaco code editor into the Labelbox platform, offering improved coding experiences with features like syntax highlighting and auto-completion, alongside enhanced support for environment variables and multi-file project execution. Additionally, the platform has introduced powerful automation tools for audio speech recognition and text extraction from documents, utilizing AI models like Whisper and ChatGPT-powered OCR to streamline these processes and reduce human error. The Alignerr Connect tool has been enhanced with a refined user interface and the launch of a public marketplace to connect users with AI expertise, while the AI interview tool Zara™ has received upgrades in connectivity, responsiveness, and security. These developments underscore Labelbox's commitment to delivering high-quality datasets and AI talent for the creation of advanced models, with further innovations anticipated in the coming months.