"We review the MLOps sector and the offerings of 14 vendors that aim to help customers automate, govern, and monitor AI experiments, deployments, performance, and accuracy. We also look at technologies like feature stores that are in their early days now but which we see as making big gains in ubiquity in the future."
Applying data science models to streaming data in real-time delivers several advantages. It can supercharge the performance and accuracy of AI-powered applications through the rapid consideration and ingestion of newly identified insights.
We’re proud to share that Iguazio has received an honorable mention in the Gartner Magic Quadrant for Data Science and Machine Learning Platforms, 2021. This is the second year in a row that Iguazio receives this recognition.
"Today, the AI Infrastructure Alliance (AIIA), officially launched with the mission to create a robust collaboration environment for companies and communities in the AI and ML space. This global Alliance brings together top technologists across the AI spectrum and includes a wide range of member companies."
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.