Remove Metrics Remove Performance Remove System Design
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How ML System Design helps us to make better ML products

Xebia

Table of Contents What is Machine Learning System Design? Design Process Clarify requirements Frame problem as an ML task Identify data sources and their availability Model development Serve predictions Observability Iterate on your design What is Machine Learning System Design?

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Why GreenOps will succeed where FinOps is failing

CIO

By emphasizing immediate cost-cutting, FinOps often encourages behaviors that compromise long-term goals such as performance, availability, scalability and sustainability. GreenOps incorporates financial, environmental and operational metrics, ensuring a balanced strategy that aligns with broader organizational goals. Multiple metrics.

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Agentic AI design: An architectural case study

CIO

An agent is part of an AI system designed to act autonomously, making decisions and taking action without direct human intervention or interaction. You can use these agents through a process called chaining, where you break down complex tasks into manageable tasks that agents can perform as part of an automated workflow.

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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

AWS Machine Learning - AI

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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GSAS Talk: Pragmatic Approach to Architecture Metrics – Part 1

Apiumhub

In their thought-provoking presentation titled “Pragmatic Approach to Architecture Metrics” at GSAS’22 organized by Apiumhub , Sonya Natanzon, and Vlad Khononov delivered valuable insights. Consequently, we assess the capacity of architecture to embrace change through various metrics. Whatever that is.”

Metrics 69
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Navigating the cloud maze: A 5-phase approach to optimizing cloud strategies

CIO

The good news is all major cloud providers frameworks do the same thing: Operational excellence Security Cost optimization Reliability Performance efficiency Sustainability The framework helps in implementing the financial controls (FinOps) that we will discuss separately, management of workloads (BaseOps) and security controls (SecOps).

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Ground truth curation and metric interpretation best practices for evaluating generative AI question answering using FMEval

AWS Machine Learning - AI

This post focuses on evaluating and interpreting metrics using FMEval for question answering in a generative AI application. FMEval is a comprehensive evaluation suite from Amazon SageMaker Clarify , providing standardized implementations of metrics to assess quality and responsibility. Question Answer Fact Who is Andrew R.