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Lessons Learned from Building LinkedIn’s AI Data Platform
Felix GV provides an overview of LinkedIn’s AI ecosystem, then discusses the data platform underneath it: an open source database called Venice.
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Unpacking How Ads Ranking Works @Pinterest
Aayush Mudgal discusses social media advertising, unpacking how Pinterest harnesses the power of Deep Learning Models and big data to tailor relevant advertisements to the pinners.
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LIquid: a Large-Scale Relational Graph Database
Scott Meyer discusses LIquid, the graph database built to host LinkedIn, serving a ~15Tb graph at ~2M QPS.
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The AI Revolution Will Not Be Monopolized: How Open-Source Beats Economies of Scale, Even for LLMs
Ines Montani discusses why the AI space won’t be monopolized, covering the open-source model, common misconceptions about use cases for LLMs in industry, and principles of software development.
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Multiplying Engineering Productivity in Face of Constant Change
Shweta Saraf discusses harnessing the collective intelligence of a team to not only multiply productivity, but also cultivate organizational resilience in the face of unceasing changes.
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Building a Rack-Scale Computer with P4 at the Core: Challenges, Solutions, and Practices in Engineering Systems on Programmable Network Processors
Ryan Goodfellow discusses lessons learned and open source tooling developed while delivering a product on top of the Tofino 2 switch processor.
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Retrieval-Augmented Generation (RAG) Patterns and Best Practices
Jay Alammar discusses the common schematics of RAG systems and tips on how to improve them.
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Mission, Culture, and Values: Using Them to Guide Your Company through Good and Challenging Times
Heather McKelvey discusses LinkedIn’s guidelines used to weather events, such as economic downturns, and how to turn those periods into opportunities.
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Understanding Architectures for Multi-Region Data Residency
Alex Strachan discusses challenges to build multi-region data storages, understanding why and when a business needs to do this, who are the real stakeholders, and who owns what.
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Large Language Models for Code: Exploring the Landscape, Opportunities, and Challenges
Loubna Ben Allal discusses Large Language Models (LLMs), exploring the current developments of these models, how they are trained, and how they can be leveraged with custom codebases.
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From Mainframes to Microservices - the Journey of Building and Running Software
Suhail Patel discusses the platforms and software patterns that made microservices popular, and how virtual machines and containers have influenced how software is built and run at scale today.
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Streaming Databases: Embracing the Convergence of Stream Processing and Databases
Yingjun Wu discusses the evolution of streaming databases, and the features and design principles that set streaming databases apart from conventional database systems and stream processing engines.
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