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.
Mar 3, 2021
Read more about top AI applications in the medical field and how data annotation plays an important role in the development of healthcare technology.
Jan 28, 2021
Learn more about Salesforce Einstein as an example of AI capabilities packaged into a big software vendor’s product for creating further differentiation.
Jan 20, 2021
Learn more about how data labeling providers are keeping up with growing demand by strategically providing accurate and efficient tooling options to the customer.
Jan 11, 2021
Read more about the top ways in which AI will drive innovation across industries in 2021 and beyond.
Jan 5, 2021
Read more about USGS’s goal to develop a national-scale, geospatial database of the most important mines and mineral districts of the United States.
Jan 5, 2021
Read more about how iMerit’s Solution team collaborates with the client’s team to provide accurate and efficient data for machine learning.
Jan 5, 2021
Learn more about challenges that geospatial data analysts are facing and how to mitigate those challenges using machine learning.
Jan 5, 2021
Read more about the combination of art and science that goes into data annotation methodology for a semantic segmentation workflow of a field crop.
Dec 15, 2020
Find out more about the importance of quality of data labeling for your AI program, including both technical and financial aspects.
Dec 8, 2020
Find out how a partnership orientation and solutions approach brings flexibility, power, and productivity to data annotation workflows.
Dec 8, 2020
Read more about importance of getting value from AI solutions, both with AI training and operations, by creating metadata or labeling data.
Nov 30, 2020
Learn more about how retail investment in AI algorithms fall into two categories - customer experience and e-commerce operations.