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How ML System Design helps us to make better ML products

Xebia

With the industry moving towards end-to-end ML teams to enable them to implement MLOPs practices, it is paramount to look past the model and view the entire system around your machine learning model. The classic article on Hidden Technical Debt in Machine Learning Systems explains how small the model is compared to the system it operates in.

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Agentic AI design: An architectural case study

CIO

Agentic AI is the next leap forward beyond traditional AI to systems that are capable of handling complex, multi-step activities utilizing components called agents. He believes these agentic systems will make that possible, and he thinks 2025 will be the year that agentic systems finally hit the mainstream. They have no goal.

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Interviewing is a noisy prediction problem

Erik Bernhardsson

So we can choose to spend one hour on system design, one hour on algorithms, etc. System design. Let’s review research and see what measurements to pick that are most predictive. Judging by the literature review earlier in this post, unstructured interviews are almost useless. Algorithms. Github portfolio.

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Why GreenOps will succeed where FinOps is failing

CIO

Capital One built Cloud Custodian initially to address the issue of dev/test systems left running with little utilization. Architects must combine functional requirements with multiple other long-term requirements to build sustainable systems. The rapid adoption of AI is making the challenge an order of magnitude worse.

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6 enterprise DevOps mistakes to avoid

CIO

But DevOps struck me as too dev-centric at the time, and my first articles questioned who owned DevOps and how DevOps was a major shift in practices. AI complements the work of developers and engineers, freeing up time for innovation, system design, and architecture,” says Andrea Malagodi, CIO of Sonar. “I

DevOps 214
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Business Analysis Tools: Reviewing Confluence, IBM DOORS, Lucidchart, Gliffy, MS Visio, and more

Altexsoft

In this article, we give credit to the software used in business analysis. For now, there is no end-to-end system to perform all BA tasks in one place. We selected the five most popular systems to compare their functionality. Review of requirements management software. The software has cloud-based and on-premise versions.

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Medical content creation in the age of generative AI

AWS Machine Learning - AI

The use cases can range from medical information extraction and clinical notes summarization to marketing content generation and medical-legal review automation (MLR process). In this post, we explore how LLMs can be used to design marketing content for disease awareness.