Tag: MLOps
Feb 25, 2021 |
In an effort to create a standard set of tools that would help data science teams collaborate on AI development, an infrastructure initiative launched this week will promote a unified stack for developing and scaling machine learning models. Read more…
Dec 10, 2020 |
Despite greater spending on staffing and use cases, investors in machine learning have so far reaped few returns as they struggle with life cycle issues related to data governance, security and auditing requirements. Read more…
Dec 9, 2020 |
DataRobot announced more late-round investments this week along with an expanded partnership with big data leader Snowflake Inc. that would extend the reach of its enterprise AI platform.
A Series F funding round announced last month and led by Altimeter Capital raised $270 million. Read more…
Nov 25, 2020 |
Data science used to be somewhat of a mystery, more of a dark art than a repeatable, scientific process. Companies basically entrusted powerful priests called data scientists to build magical algorithms that used data to make predictions, usually to boost profits or improve customer happiness. Read more…
Nov 5, 2020 |
Tools continue to be introduced to allow machine learning developers to monitor model and application performance as well as anomalies like model and data drift—a trend one market tracker dubs “ModelOps.”
The latest comes from Algorithmia, which this week launched an enterprise platform for monitoring machine learning model performance. Read more…
Nov 4, 2020 |
Intel Corp. has quietly acquired another AI platform developer, Israeli-based Cnvrg.io.
The acquisition, confirmed by Intel late Tuesday (Nov. 3) to the web site TechCrunch.com, is the latest in a flurry of deals by the chip maker (NASDAQ: Read more…
Sep 11, 2020 |
The rapid maturation of machine learning operations (ModelOps) tools is leading to a “breakout year” for ModelOps, Forrester says in a recent report.
The ML lifecycle is a potential nightmare for many organizations, write Forrester analysts Mike Gualtieri and Kjell Carlsson in an August report, titled “Introducing ModelOps to Operationalize AI.”
“This process takes too long and is fraught with technical and business challenges, just with one model,” the analysts write. Read more…
Jul 7, 2020 |
As data science platforms expand across enterprise applications like predictive analytics, automated machine learning vendors are steadily integrating AI models with emerging infrastructure to ease deployment and orchestration.
For example, data science automation specialist dotData this week released a container-based machine learning model aimed at real-time prediction. Read more…
May 4, 2020 |
As a growing percentage of enterprise AI projects stall, data science platform vendors are teaming with cloud and data management specialists to move AI projects from the model-building stage to production workloads. Read more…
