InTDS ArchivebyTorsten WalbaumWhat 10 Years at Uber, Meta and Startups Taught Me About Data AnalyticsAdvice for Data Scientists and ManagersMay 30, 2024104May 30, 2024104
InTDS Archivebyming gaoFrom Data Platform to ML PlatformHow Data/ML platforms evolve and support complex MLOps practicesOct 22, 20232Oct 22, 20232
InPinterest Engineering BlogbyPinterest EngineeringTraining Foundation Improvements for Closeup Recommendation RankerFan Jiang | Software Engineer, Closeup Candidate Retrieval; Liyao Lu | Software Engineer, Closeup Ranking & Blending; Laksh Bhasin |…Sep 26, 2023Sep 26, 2023
InEMAlphabySkanda VivekThe Economics of Large Language ModelsA deep dive into considerations for using and hosting large language modelsAug 8, 20231Aug 8, 20231
InVimeo Engineering BlogbyJon RuddellFrom idea to reality: Elevating our customer support through generative AIHow we prototyped and enhanced the Vimeo Help Desk through rigorous testing.Aug 11, 20239Aug 11, 20239
InTDS ArchivebyBarr MosesPioneering Data Observability:Data, Code, Infrastructure, & AIOutlining the past, present, and future of architecting reliable data systems.Aug 8, 20231Aug 8, 20231
InAI MindbyPaul Pallaghy, PhDA holy grail of text AI: ChatGPT / LLM generative query on YOUR OWN unlimited custom dataThis is almost bigger than ChatGPT. So-called ‘vector databases’ now enable reliable ‘semantic’ search and generative AI on unlimited…Jul 4, 202314Jul 4, 202314
InDataDrivenInvestorbyDebmalya BiswasGenerative AI — LLMOps Architecture PatternsDeploying Large Language Models (LLMs) in the EnterpriseJun 25, 20233Jun 25, 20233
InTDS ArchivebyJimmy WhitakerBootstrapping Labels with GPT-4A cost-effective approach to data labelingJun 9, 20231Jun 9, 20231
YUNNA WEIMLOps in Practice — Have you ever monitored your ML driven systems?Monitoring plays a fundamental role in any solid ML solution architecture. It gives data scientists, ML engineers and system engineers the…Jan 18, 2023Jan 18, 2023
InLyft EngineeringbyKonstantin GizdarskiBuilding Real-time Machine Learning Foundations at LyftIn early 2022, Lyft already had a comprehensive Machine Learning Platform called LyftLearn composed of model serving, training, CI/CD…Jun 28, 20235Jun 28, 20235
InTDS ArchivebyChristabelle PabalanBeyond Accuracy: Embracing Serendipity and Novelty in Recommendations for Long Term User RetentionAn examination of the factors that contribute to a good recommendation and long-term user retentionJun 26, 20234Jun 26, 20234
Simon AttardLeveraging Large Language Models in your Software ApplicationsHow can you leverage the capabilities of Large Language Models (LLMs) within your software applications?Jun 20, 20236Jun 20, 20236
Shivam AroraKnowledge Graphs For Large Language ModelsThe potential impact of LLMs extends beyond language-related tasks. With their ability to process and comprehend vast amounts of…Jun 18, 2023Jun 18, 2023
InTDS ArchivebyDr. Janna LipenkovaFour LLM trends since ChatGPT and their implications for AI buildersIn October 2022, I published an article on LLM selection for specific NLP use cases , such as conversation, translation and summarisation…May 29, 20231May 29, 20231
InTDS ArchivebyEzequiel Ortiz RecaldeAI Frontiers Series: Supply ChainAn introduction to the current use cases and possibilities in a gigantic industryJun 6, 20236Jun 6, 20236
InML6teambyJan Van LooyDeveloping AI systems in the Foundation Model ageFrom MLOps to FMOpsJun 7, 20231Jun 7, 20231
InTDS ArchivebySkanda VivekLLM Economics: ChatGPT vs Open-SourceHow much does it cost to deploy LLMs like ChatGPT? Are open-source LLMs cheaper to deploy? What are the tradeoffs?Apr 26, 202312Apr 26, 202312
InTDS ArchivebyHennie de HarderSimplify Your Machine Learning ProjectsWhy spending a lot of time and effort on a complex model is a bad idea, and what to do insteadMay 10, 20238May 10, 20238
