Small models, big results: Achieving superior intent extraction through decomposition
Generative AI
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How to Annotate Radiology Data for an AI Model
Correctly identifying when a medical finding is absent rather than present is crucial when working on this specific task (for example, extracting labels from radiology reports using CV) about the presence or absence of prespecified pathologies. This article aims to highlight radiology data annotation from the perspective of a data annotation company, examining what goes…
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Red Teaming for LLMs: Exposing Risks, Reinforcing Safety, and Building Trustworthy AI
With their capacity to generate human-like content at a massive scale, LLMs are exposed to additional risks compared to traditional software systems. They can produce harmful responses, such as hallucinated content, various forms of toxic/ hate speech, copyrighted material, and personally identifiable information that is not meant to be shared. These kinds of failures can…
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Instruction Tuning for Large Language Models
The mannequin is uncovered to numerous examples of directions, starting from easy queries to complicated multi-step duties. This helps the mannequin be taught to interpret and execute directions precisely, making it extra usable and adaptable. To strengthen LLMs’ capacity to understand and act on directions, instruction tuning datasets from LLM information firms like Cogito Tech…
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