MLOps Archives - Liwaiwai

MLops Is The Hot New Cloud Computing Career Path

Amid the popularity of ChatGPT, MLops spending will surge in 2023 as leaders increase investments in machine learning. Cloud pros should take a look. ClearML, an open source MLops platform announced its new research report: “MLOps in 2023: What Does the Future Hold?” This study polled 200 machine learning decision-makers in the United States, examining key trends in machine learning and MLops (machine learning operations). Putting the potential vendor self-serving bias aside for now, ClearML’s study found that MLops now enjoys wide-scale adoption within enterprises; 85% of respondents said they had a dedicated MLops budget in 2022. And 14% said…

Streamline Your Models To Production With The Vertex AI Model Registry

Machine learning (ML) is iterative in nature — model improvement is a necessity to drive the best business outcomes. Yet, with the proliferation of model artifacts, it can be difficult to ensure that only the best models make it into production. Data science teams may get access to new training data, expand the scope of use cases, implement better model architectures, or simply make adjustments as the world around your models is constantly changing. All of these scenarios require building new versions of models to be released into production. And with the addition of new versions, it matters to be…

Building A Machine Learning Platform With Kubeflow And Ray On Google Kubernetes Engine

Increasingly more enterprises adopt Machine Learning (ML) capabilities to enhance their services, products, and operations. As their ML capabilities mature, they build centralized ML Platforms to serve many teams and users across their organization. Machine learning is inherently an experimental process requiring repeated iterations. An ML Platform standardizes the model development and deployment workflow to offer greater consistency for the repeated process. This facilitates productivity and reduces time from prototype to production. When first trying ML in the cloud, many practitioners will start with fully managed ML platforms like Google Cloud’s Vertex AI. Fully-managed platforms abstract out many complexities to…

Charmed Kubeflow 1.6 Is Now Available From Canonical

Canonical, the publisher of Ubuntu, announces today the release of Charmed Kubeflow 1.6, an end-to-end MLOps platform with optimised complex model training capabilities. Charmed Kubeflow is Canonical’s enterprise-ready distribution of Kubeflow, an open-source machine learning toolkit designed for use with Kubernetes. Charmed Kubeflow 1.6 follows the same release cadence as the Kubeflow upstream project. This latest version follows the Kubeflow roadmap and comes with performance enhancements and more advanced model training capabilities. Speed up digital transformation: take models from concept to production Charmed Kubeflow helps data science teams automate tasks and boost productivity, helping companies lower costs. The platform’s components use charms – Kubernetes…

How Wayfair Is Reaching MLOps Excellence With Vertex AI

Editor’s note: In part one of this blog, Wayfair shared how it supports each of its 30 million active customers using machine learning (ML). Wayfair’s Vinay Narayana, Head of ML Engineering, Bas Geerdink, Lead ML Engineer, and Christian Rehm, Senior Machine Learning Engineer, take us on a deeper dive into the ways Wayfair’s data scientists are using Vertex AI to improve model productionization, serving, and operational readiness velocity. The authors would like to thank Hasan Khan, Principal Architect, Google for contributions to this blog. When Google announced its Vertex AI platform in 2021, the timing coincided perfectly with our search for a…

AI Booster: How Vodafone Is Supercharging AI & ML At Scale

One of the largest telecommunications companies in the world, Vodafone is at the forefront of building next-generation connectivity and a sustainable digital future. Creating this digital future requires going beyond what’s possible today and unlocking significant investment in new technology and change. For Vodafone, a key driver is the use of artificial intelligence (AI) and machine learning (ML), enabling predictive capabilities in enhancing the customer experience, improving network performance, accelerating advances in research, and much more. Following 18 months of hard work, Vodafone has made a huge leap forward in advancing its AI capabilities at scale with the launch of its “AI…

Technology

Bridge The AI/ML Divide Between Data Science And IT Infrastructure With DKube And VMware Tanzu

One of the key challenges of commercializing artificial intelligence and machine learning (AI/ML) projects is that IT and data science teams often operate in separate environments with very little synergy. As a result, AI/ML projects tend to incur high costs and rarely make it into commercial production. Now, with DKube Machine Learning Operations (MLOps) Platform on VMware Tanzu, the divide between teams can be closed. DKube on VMware Tanzu enables you to save time, resources, and cost with IT and data science teams collaborating via best-in-class model operations and infrastructure management. Learn more about our partnership and how we work…

First Dedicated AI Management And MLOps Platform On Google Cloud Marketplace

Editor’s note: Prevision.io has built the first ever pay-as-you-go AI management platform that simplifies the machine learning project lifecycle while offering powerful analytics capabilities. Now available exclusively on Google Cloud Marketplace, users can experiment, build, deploy, and manage AI projects in the cloud in weeks—without having extensive data science knowledge. Similar to the momentum that cloud technology has had in the business world, AI and machine learning are quickly becoming essential to the enterprise. 86% of companies now view AI as a “mainstream technology,” and corporate AI adoption rose 50% in 2021 from the year prior for initiatives such as service-operations optimization and product enhancement.…

Red Hat Lowers Barriers To Artificial Intelligence Projects With Red Hat OpenShift

Red Hat Inc., the world’s leading provider of open source solutions, today announced new certifications and capabilities for Red Hat OpenShift aimed at accelerating the delivery of intelligent applications across the hybrid cloud. These enhancements, including the certification of Red Hat OpenShift with NVIDIA AI Enterprise 2.0, as well as the general availability of Red Hat OpenShift 4.10, are intended to help organizations deploy, manage and scale artificial intelligence (AI) workloads with confidence. According to Gartner®, worldwide artificial intelligence (AI) software revenue is forecast to total $62.5 billion in 2022, an increase of 21.3% from 2021. As enterprises integrate AI and machine learning…

USAA And Google Cloud: Modernizing Insurance Operations With Machine Learning

Delivering an automated solution capable of going from images of vehicle damage to actual car part repair/replace predictions has been an elusive dream for many auto insurance carriers. Such a solution could not only streamline the repair process, but also increase auditability of repairs and improve overall cost efficiency. In keeping with its reputation for being an innovative leader in the insurance industry, USAA decided it was time for things to change and teamed up with Google to make the dream of touchless claims a reality. Google and USAA previously worked together on an effort to identify damaged regions/parts of a vehicle from a…

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