Heartbeat

FEBRUARY 29, 2024

From the versatility of Python to the robustness of Java and the web-centric nature of JavaScript , developers can choose from an extensive toolkit. The software development landscape is constantly evolving, driven by technological advancements and the ever-growing demands of the digital age.

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Iguazio

FEBRUARY 8, 2024

LLMOps is MLOps for LLMs. This blog post delves into the concepts of LLMOps and MLOps, explaining how and when to use each one. To read more about LLMOps and MLOps, checkout the O’Reilly book “Implementing MLOps in the Enterprise” , authored by Iguazio ’s CTO and co-founder Yaron Haviv and by Noah Gift.

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AWS Machine Learning Blog

MAY 7, 2024

Generative AI CDK Constructs , an open-source extension of AWS CDK, provides well-architected multi-service patterns to quickly and efficiently create repeatable infrastructure required for generative AI projects on AWS. This can have a negative impact in many ways, from delayed project timelines to loss of customer trust.

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The MLOps Blog

JUNE 27, 2023

As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. Below, you will find some key factors to consider when assessing MLOps tools and platforms, depending on your needs and preferences.

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AWS Machine Learning Blog

APRIL 26, 2023

Do you need help to move your organization’s Machine Learning (ML) journey from pilot to production? You’re not alone. Most executives think ML can apply to any business decision, but on average only half of the ML projects make it to production. Ensuring data quality, governance, and security may slow down or stall ML projects.

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The MLOps Blog

SEPTEMBER 7, 2023

Related post MLOps Is an Extension of DevOps. Writing legible, reusable, and efficient code has always been a challenge in the software development community. Endless conversations happen every day across Github pull requests and Slack threads around this topic. This situation is not different in the ML world.

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The MLOps Blog

AUGUST 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Stefan: Yeah. Thanks for having me. What is DAGWorks?

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AWS Machine Learning Blog

AUGUST 16, 2023

This post is cowritten by Shirsha Ray Chaudhuri, Harpreet Singh Baath, Rashmi B Pawar, and Palvika Bansal from Thomson Reuters. Thomson Reuters (TR), a global content and technology-driven company, has been using artificial intelligence (AI) and machine learning (ML) in its professional information products for decades.

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AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries. It also provides guidance for generating cost and usage reports for ML use cases.

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Heartbeat

MARCH 19, 2024

Like machine learning operations, LLMOps involves efforts from several contributors, like prompt engineers, data scientists, DevOps engineers, business analysts, and IT operations. Although LLMOps apply MLOps principles, it greatly emphasizes performance, reliability, and scalability. I didn't make any of these up.

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The MLOps Blog

MAY 9, 2023

Pipelines and platforms are related concepts in MLOps, but they refer to different aspects of the machine learning workflow. One of the most prevalent complaints we hear from ML engineers in the community is how costly and error-prone it is to manually go through the ML workflow of building and deploying models. If all goes well, of course ?

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The MLOps Blog

DECEMBER 28, 2022

MLOps cycle | Source How to organize ML team Centralized ML team People from different fields like engineering, product, DevOps, and ML all come together under one big team. As per a report by McKinsey , AI has the potential to contribute USD 13 trillion to the global economy by 2030. 2 What type of skills should my team possess?

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The MLOps Blog

MARCH 21, 2023

To do that, you’d need to take a systematic approach to MLOps —enter platforms! Machine learning platforms are increasingly looking to be the “fix” to successfully consolidate all the components of MLOps from development to production. We ask this during product demos, user and support calls, and on our MLOps LIVE podcast.

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