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Inside Facebook’s video delivery system

Engineering at Meta

Were explaining the end-to-end systems the Facebook app leverages to deliver relevant content to people. At Facebooks scale, the systems built to support and overcome these challenges require extensive trade-off analyses, focused optimizations, and architecture built to allow our engineers to push for the same user and business outcomes.

Systems 71
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Microsoft’s Drasi: An Open-Source Tool for Efficient Change Management Systems

Analytics Vidhya

Introduction Today, data systems evolve quickly, demanding efficient monitoring and response. Real-time change detection is essential to keeping systems stable, preventing failures, and ensuring business continuity.

Systems 175
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Redefining AIOps IT Workflows with Legacy System Visibility

Precisely

Modern IT environments require comprehensive data for successful AIOps, that includes incorporating data from legacy systems like IBM i and IBM Z into ITOps platforms. AIOps presents enormous promise, but many organizations face hurdles in its implementation: Complex ecosystems made of multiple, fragmented systems that lack interoperability.

Systems 58
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Establishing a Large Scale Learned Retrieval System at Pinterest

Pinterest Engineering

Modern large-scale recommendation systems usually include multiple stages where retrieval aims at retrieving candidates from billions of candidate pools, and ranking predicts which item a user tends to engage from the trimmed candidate set retrieved from early stages [2]. General multi-stage recommendation system design in Pinterest.

Systems 67
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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

The number of use cases/corner cases that the system is expected to handle essentially explodes. When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases.

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Getting Started with Building RAG Systems Using Haystack

KDnuggets

Retrieval augmented generation (RAG) is altering the way we use large language models, but building these systems can be hectic. In this article, you will learn how to build RAG systems using Haystack.

Systems 135
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Building a Question-Answering System Using RAG

WeCloudData

The ability to extract information from vast amounts of text has made question-answering (QA) systems essential in the modern era of AI-driven apps. RAG-based question-answering systems use large language models to generate human-like responses to user queries.

Systems 52
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Agent Tooling: Connecting AI to Your Tools, Systems & Data

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API.

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How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Is your manufacturing operation reaching its efficiency potential?

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.

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How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation metrics for at-scale production guardrails.

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Entity Resolution: Your Guide to Deciding Whether to Build It or Buy It

This will help you decide whether to build an in-house entity resolution system or utilize an existing solution like the Senzing® API for entity resolution. By the end, you'll understand what to look for, the most common mistakes and pitfalls to avoid, and your options.

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A Guide to Debugging Apache Airflow® DAGs

You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-related issues and external system failures Conduct root cause analysis for production pipelines After reading, you’ll know how to tackle a wide range of DAG-related (..)

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Leading the Development of Profitable and Sustainable Products

Speaker: Jason Tanner

A sustainable business model contains a system of interrelated choices made not once but over time. While growth of software-enabled solutions generates momentum, growth alone is not enough to ensure sustainability. The probability of success dramatically improves with early planning for profitability.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.