Scale AI—which helps companies like ChatGPT improve the data that feeds their systems—is pictured on a laptop in New York on Aug. 16, 2023. On TikTok, Reddit, and elsewhere, posts are popping up from ...

When we talk about artificial intelligence, most people immediately think of futuristic robots and self-driving cars. But here’s the truth I’ve learned over years of working with data and leading ...

Artificial Intelligence (AI) continues to capture attention for its ability to transform financial services. From accelerating onboarding to improving anti-financial crime outcomes, AI is reshaping ...

Why it matters: Accurate labeling sets the ceiling for AI performance, and even advanced algorithms fail without high-quality annotated data. How it’s done: Annotation covers text, images, audio, and ...

Labeling and annotation platforms might not get the attention flashy new generative AI models do. But they’re essential. The data on which many models train must be labeled, or the models wouldn’t be ...

New clients are invited to assess quality through a free pilot project - no contracts, no commitments - before moving forward with a full engagement. To learn more or launch a free annotation pilot, ...

Is it possible for an AI to be trained just on data generated by another AI? It might sound like a harebrained idea. But it’s one that’s been around for quite some time — and as new, real data is ...

Data development platform Encord is going beyond business analysis to become "the world's only multimodal AI data development platform." To fine-tune an AI model, you need quality -- and sometimes ...

Your AI isn't just learning from your data; it’s making dozens of untracked copies of it, leaving sensitive customer info ...

Robotics programs require egocentric, multi-sensor training data at a scale that is growing exponentially, creating a procurement challenge distinct from any prior AI development cycle Annotation ...

Poor training data does not just hurt model accuracy. It triggers a costly chain reaction. This article shows data leaders exactly where the money bleeds and what to do about it.