Cleanlab
cleanlab.ai
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Overview
Cleanlab is a company founded in 2021 by researchers from the Massachusetts Institute of Technology who developed confident learning, a method for finding label errors in datasets. Its open-source library and commercial studio automatically detect mislabelled, duplicated and outlier examples so teams can fix data instead of endlessly tuning models. The company has extended the approach to scoring the trustworthiness of large language model answers.
News
Cleanlab CEO: Agentic AI won't really gel until 2027
Curtis Northcutt, whose startup focuses on agentic orchestration and finding ways to reduce hallucinations, says companies are already scrambling to get ahead of the fast-evolving tech.
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Prevent LLM Hallucinations with the Cleanlab Trustworthy Language Model in NVIDIA NeMo Guardrails
As more enterprises integrate LLMs into their applications, they face a critical challenge: LLMs can generate plausible but incorrect responses…
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OpenAI's o1 surpassed using the Trustworthy Language Model
See results from using the Trustworthy Language Model to: detect hallucinations/errors from the o1 model and improve its response accuracy.
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CROWDLAB: The Right Way to Combine Humans and AI for LLM Evaluation
CROWDLAB improves your team's LLM Evals process by automatically producing reliable ratings and flagging which outputs need further review.
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Cleanlab Saves 90% on GPU Costs with Inferless Serverless Inference Inferless
Learn how Cleanlab cut GPU costs by 90% and boosted performance with Inferless. Discover the benefits of faster cold starts, efficient cost management, and seamless environment separation in their transition to serverless GPU inference.
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