Recent advancements in large generative models have resulted in widespread interest in their ability to act on complex instructions. These so-called foundational large language models (LLMs), e.g., ...

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Amid the boom of AI in application building, companies face a significant data-labeling problem, especially when it comes to labeling images or other media content they want to train deep learning ...

High-quality data labeling underpins every successful AI model. Combining human oversight, automation, and synthetic data can cut costs while improving precision. With strong workflows and the right ...

Heartex, a startup that bills itself as an “open source” platform for data labeling, today announced that it landed $25 million in a Series A funding round led by Redpoint Ventures. Unusual Ventures, ...

Before you can even think about building an algorithm to read an X-ray or interpret a blood smear, the machine has to know what’s what in an image. All of the promise of AI in healthcare — an area ...

Simple data labeling is becoming obsolete as AI models require more complex training data, says Turing's CEO. AI training companies need to be a "proactive research partner" for major labs, Jonathan ...