The amount of data generated each day boggles the mind. IDC forecasts the total will grow to 5.2 zettabytes in 2025, and it’s accelerating exponentially — 90 percent of the world’s data was generated in the past two years alone. (For point of reference, a zettabyte is the equivalent of 250 billion DVDs.)
It’s a lot for anyone to wrap their head around — particularly data scientists tasked with leveraging that data to train, validate, and test machine learning systems. To making wrangling it a little easier, software engineer Yosi Taguri two years ago teamed up with three colleagues — Shay Erlichmen, Joe Salomon, and Rahav Lussato — to found MissingLink.ai. Today, it launched publicly.
“We’re at an incredible tipping point with all the data we need to solve really important problems, like saving lives through cancer detection and providing safer, smarter driving on the streets,” Taguri said. “But wading through all that data to find the meaning from it is tough and requires too much manpower. MissingLink allows every engineer to build complex AI machines in a way that wasn’t possible before.”
To that end, MissingLink.ai offers end-to-end management and deployment tools that simplify coding and model training processes. It supports popular machine learning frameworks such as Google’s TensorFlow, Facebook’s Caffe2, PyTorch, and Keras, and instantly syncs changes to data, obviating the need to copy files manually. As for experiments, which the system automatically delegates to available compute resources and runs in parallel, they…