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Tag: MLOps

Google Cloud Overhauls AI with Vertex Launch

Google Cloud today unveiled Vertex AI, a fundamental redesign of its automated machine learning stack. In addition to integrating the individual components of the stack more closely together, Vertex AI also introduces ne Read more…

DataRobot Refreshes AI Platform, Nabs Zepl

DataRobot unveiled several enhancements in its automated machine learning platform today, including the introduction of features like composable ML and continuous AI. The company, which is holding a virtual conference to 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…

Algorithmia Adds Data Governance Tools

Data governance and a growing list of compliance rules remain key considerations for managing machine learning models in production. Vendors are responding to the growing risks with compliance frameworks as they flesh ou Read more…

AI Infrastructure Gets a Stack

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 mac Read more…

ML Deployment Woes Persist

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…

DataRobot, Snowflake Expand AI Collaboration

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 anno 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…

Intel Buys Another AI Startup

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 t 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…

MLOps Vendor dotData Boosts Automation with Containers

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 orchest Read more…

Growing Focus on MLOps as AI Projects Stall

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…

An Open Source Alternative to AWS SageMaker

There’s no shortage of resources and tools for developing machine learning algorithms. But when it comes to putting those algorithms into production for inference, outside of AWS’s popular SageMaker, there’s not a Read more…

DataRobot Snags Data Prepper Paxata

Automated machine learning softer provider DataRobot yesterday announced the acquisition of Paxata, a provider of self-service data preparation and data fabrics. And it didn’t take DataRobot long to release the first n Read more…

It’s Time for MLOps Standards, Cloudera Says

Just as operational standards have been established for data management via DataOps, the industry needs to create open standards for machine learning operations, or MLOps, according to Cloudera, which today unveiled a ca Read more…

ParallelM Aims to Close the Gap in ML Operationalization

A startup named ParallelM today unveiled new software aimed at alleviating data scientists from the burden of manually deploying, monitoring, and managing machine learning pipelines in production. Dubbed MLOps, Parall Read more…

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