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AI meets operations

O'Reilly

First, the behavior of an AI application depends on a model , which is built from source code and training data. You need a repository for models and for the training data. And that’s essential: if you need to understand how your model behaves, and you don’t have the training data, you’re sunk.

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Trends and Topics for 2022

Adrian Cockcroft

The other continuing trend is to custom silicon, with specialized accelerators and the ARM based Graviton range from AWS, Apple’s M1 series, Tesla’s in car processor and training engines etc. Coming up on Jan 26, 2022 I’ll be presenting at the online OReilly Software Architecture Superstream event. primarily virtual?—?and

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Nurturing Design in Your Software Engineering Culture

Strategic Tech

In fact, Software Design EventStorming is like a DSL for designing business processes that translate directly into code. Provide Design Training & Coaching Training can accelerate the design learning process for any engineer or architect. They prefer to work in isolation and just deliver.

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How architecture evolves into strategy

O'Reilly Software

It's a given that we must design a system, including a local software architecture, that actually runs, that is "solid." The operating model: processes and how your company conducts its business. Talent strategy: how you source and retain talent, how you train them. It must be beautiful, like Venus, inspiring love.

Strategy 100
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Modelling Bounded Contexts with the Bounded Context Design Canvas: A Workshop Recipe

Strategic Tech

look for key business events which indicate state changes between different parts of the business process. Bounded Context Design Canvas The next step of the design process is to design your candidate bounded contexts by detailing key design criteria. create the simple-but-naive model by breaking up the timeline into sequential steps.

Design 76
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Open-Sourcing Metaflow, a Human-Centric Framework for Data Science

The Netflix TechBlog

mainly because of mundane reasons related to software engineering. We heard many stories about difficulties related to data access and basic data processing. In this hypothetical example, the flow trains two versions of a model in parallel and chooses the one with the highest score. The steps can be arbitrary Python code.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly

While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments.

DevOps 140