From casual to cultured, the iMerit blog tackles a wide array of topics related to security, expertise, and flexibility in the artificial intelligence and machine learning data-enrichment marketplace.
Jun 17, 2026
iMerit placed 1st at CVPR 2026 Auto3D Challenge, outperforming 11 teams with a no-3D-label pipeline using SAM 3, CLIP, and LoRA adaptation.
Sep 29, 2021
The blog explores how video machine learning (ML) systems can learn common sense with a little help from human annotators and video ML models.
Sep 22, 2021
Poor-performing ML and AI models are all too common. In this blog, we outline troubleshooting techniques and key considerations for evaluating your AI/ML model.
Sep 20, 2021
Hand-picked dataset search engines, aggregators, and repositories for your ML projects. Full list in iMerit’s blog post.
Sep 17, 2021
Learn more about the good, bad, and ugly of crowdsourced data annotation and where subject-matter experts can make-or-break a successful AI project.
Sep 16, 2021
iMerit CEO Radha Basu talks with Lindsey Asis at AI for Good Foundation, about the importance of inclusion, quality AI data, and iMerit's business model
Sep 15, 2021
Learn the telltale signs that it may be time to outsource your data labeling to a professional team, and why it will save you a big headache in the long run.
Sep 9, 2021
iMerit’s Brett Hallinan and autonomous vehicle industry expert Chris Barker dive into the latest headlines about the $1 trillion federal infrastructure bill and its impact on autonomous vehicles.
Sep 1, 2021
Learn how iMerit adapts to edge cases found during annotation and assumption testing to improve model accuracy and deployment readiness.
Aug 24, 2021
Pairing words with images helps NLP systems better mimic human understanding, boosting performance across captioning, QA, and classification.
Jul 29, 2021
With key takeaways from iMerit's Webinar at ODSC, learn how to ensure high-quality data and achieve ML Project success.
Jul 29, 2021
With the key takeaways from iMerit's CVPR 2021 session, learn how providing context to images can greatly improve data annotation accuracy.
Jul 29, 2021
Learn how transfer learning enables an application with limited training samples, like Alzheimer’s detection, to benefit from a much larger training set.