June has been a wild, all-hands-on-deck kind of month! We went out into the field to converse with customers and research scientists on the cutting edge of AI and ML as sponsors of 5 conferences: CVPR, International Conference on Machine Learning, Energy Drone & Robotics Summit, O'Reilly AI Conference in Beijing, and AI World Government. 

Most readers of this blog already know that training machine learning algorithms requires huge amounts of annotated data. But a recent survey of data scientists we commissioned with Dimensional Research gave us a concrete definition of “huge”. A full 72% of the nearly 300 survey respondents reported that, in their current project, production-level model confidence will require more than 100,000 labeled data items. And 10% indicated they’d need more than 10 million! That’s a lot of bounding boxes and polygons!

In our latest long form piece, we describe five qualities you should look for in a video annotation solution provider:

Disclosure: We are not a Cognilytica client and we are not mentioned in this report.

AI is shaping up to be a large engine for job creation. Automating processes through machine learning and artificial intelligence will change the way we work and will change the work that we do.

We know how hard it is to prepare training data for machine learning projects. We’ve been labeling and annotating training datasets for enterprise data science teams for years.