Tag: ModelOps
Databricks Unleashes New Tools for Gen AI in the Lakehouse
Fresh off its announcement of the acquisition of MosaicML on Monday, Databricks today unleashed a torrent of new AI capabilities at its Data + AI Summit designed to enable its customers to create generative AI applicatio Read more…
Why DataOps-Centered Engineering is the Future of Data
DataOps will soon become integral to data engineering, influencing the future of data. Many organizations today still struggle to harness data and analytics to gain actionable insights. By centering DataOps in their proc Read more…
TIBCO’s ModelOps Takes AI Models Out of the Lab and Onto on the Road
Data management firm TIBCO has unveiled its new TIBCO ModelOps platform designed to enable faster deployment of AI models at scale. The Palo Alto-based company cited a 2021 survey from NewVantage Partners that showed Read more…
A ‘Glut’ of Innovation Spotted in Data Science and ML Platforms
These are heady days in data science and machine learning (DSML) according to Gartner, which identified a “glut” of innovation occurring in the market for DSML platforms. From established companies chasing AutoML or Read more…
The Maturation of Data Science
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 Read more…
Algorithmia, Datadog Team on MLOps
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 la Read more…
A ‘Breakout Year’ for ModelOps, Forrester Says
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 organization Read more…
Operationalizing Analytics: Conquering the Last Mile
Per research from McKinsey, only 8% of companies successfully scale analytics. To improve this abysmal rate, organizations must conquer what’s been called the last mile of analytics. For those who can, the payoff is tr Read more…
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