ML engineers aiming to truly automate ML pipelines need a way to natively enable continuous integration of machine learning models to production. Several services can incorporate CI/CD into ML pipelines. Still, they place data scientists into a black-box silo situation so that they must build, train, track, and deploy within a closed technology stack.
Iguazio was selected to assist the digital transformation of Sheba with real-time AI and machine learning operations (MLOps) in several projects. "Sheba will use the Iguazio Data Science Platform to foresee and lessen complications in cases such as Covid-19 patient deterioration or support decision-making throughout surgery.
"We are honored to be supporting Sheba...incorporating AI into these many real-time use cases is setting a new standard for medical centers worldwide, commented Asaf Somekh, Co-Founder and CEO of Iguazio."
“Using Iguazio, we are revolutionizing the way we use data, by unifying real-time and historic data from different sources and rapidly deploying and monitoring complex AI models to improve patient outcomes and the City of Health’s efficiency”, said Nathalie Bloch, MD, Head of Big Data & AI at Sheba Medical Center.
"The 12 coolest machine-learning startups include companies that are developing leading-edge technology for building machine-learning models and collecting and managing the vast amounts of data needed to train those models."
"These are data science software systems with extremely complicated convoluted structures...We have, perhaps unsurprisingly, gone beyond the point where we can handle all of those things manually"