“Advanced AI models are increasingly created and run on the cloud, but need good quality data from edge devices. The high volume and complex nature of this data has created a new exascale-class problem. Akridata is addressing the problem by managing smart pipelines for ingesting, filtering, curating, tracking, and staging of AI data.”

“Most academic datasets are far from the industry's needs. In our case, we have rather small objects in fairly big images. This is probably a common problem, but in academia it is kind of a niche.”

“Data-Centric AI solutions such as Akridata’s Edge Data Platform fill that need and help customers to match the sophistication of their analytics and models with high-quality and relevant data.”

“Today we have models that are extremely good at mimicking the data that you train them to mimic, but they can only become as good as that data, not better. The data can always get a little better and cover more corner-cases while models can at best be perfect within the data distribution that they know about.”

“One of the biggest challenges for data scientists focused on visual data is the ability to visualize three-dimensional visual data in a two-dimensional format and gain in-depth understanding from them.”