The Institute for Ethical AI & Machine Learning
@EthicalML
Research centre focused on developing Frameworks for the responsible design and deployment of AI. Led by volunteers: https://ethical.institute/network.html
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Kompute joins the Linux foundation @LFAIDataFdn to further the cross-vendor GPU Acceleration ecosystem for AI, Machine Learning and Advanced Data Processing use-cases 🚀
Kompute has joined @LFAIDataFdn as a Sandbox project. Released & open sourced by The Institute for Ethical AI & Machine Learning, Kompute is a general purpose GPU compute framework for AI & Machine Learning applications. hubs.la/H0W1rkM0 Learn more: #Kompute #LFAIDataFdn
Landed in London for #KubeCon Europe! If you are around let's catch up! Also join us tomorrow in our opening keynote at the KubeCon AI Day on the state of GenAI & ML in the Cloud Native Ecosystem 🚀
🥳🥳🥳 Happy New Year 2025 🥳🥳🥳 How time flies! We are celebrating 6 years since starting this weekly MLE newsletter 🎉🎉🎉 Check out the deep dives and resources in this week's edition: buff.ly/3U7DCrp
Insightful news, resources and frameworks in the Machine Learning Ecosystem this week: National AI Strategies & Regulation, Netflix's Large Scale Time Series Infra, Gauge on GenAI's Tech Debt Costs, Gradient Flow on AI Engineers, MLOps Organisational Setups + more 🚀 Check out…
Central functions support machine learning ambitions across organisations; only ~30% of organizations have a central Data / ML platform, and less than 10% have central AI Risk Governance: Establishing central functions to support teams is a growing trend in machine learning…
We are pleased to announce that our next speaker is Alejandro Saucedo on November 18. Register and find out more! ieai.sot.tum.de/event/speaker-… @chluetge @AxSaucedo #ieai.sot.tum.de #ai #artificialintelligence #aiethics
In Machine Learning, Spreadsheets just keep coming back - this time as one of the top choices for experiment tracking and model registry tools... Only a week since we launched our survey on the State of Production ML we are already seeing great insights, help us map the broader…
Fantastic episode of"Talk Python Podcast" on"Python at Netflix" featured two guests from Netflix's Python Infrastructure team, Amjith Ramanujam and Srinivasan Ramanujam 📺 youtube.com/watch?v=yPBslO… #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps #DataOps
Meta / Facebook has released their "approach to explaining (ML) ranking" 💡 This includes how posts are ranked in newsfeed, recommendations, ranking of comments, friend recommendations, notifications and more. transparency.fb.com/features/expla… #ML #MachineLearning
New free online course on "Large Language Models: Application through Production" 💡 A great resource for developers, data scientists, and engineers who aim to build applications powered by large language models. edx.org/course/large-l… #ML #MachineLearning
Future of Custom & Fine-Tuned LLMs 🔮 A great article from Outerbounds, the company behind Metaflow, which explores instruction tuning for large language models. outerbounds.com/blog/custom-ll… #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps #DataOps
ML System Design Case Studies 🖥️ Evidently AI created a fantastic resource containing 200 real-word case studies of ML Systems from 64 companies including Netflix, Airbnb, and Doordash. evidentlyai.com/ml-system-desi… #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps
🚀 This week in Machine Learning at Scale 🚀 In this edition we cover: 1) ML System Design Case Studies 2) Future of Custom Tuned LLMs 3) LLM App to Prod Databaricks 4) + more 🚀 linkedin.com/pulse/issue-23… #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps #DataOps
Dealing with Train-serve Skew in Real-time ML Models: A Short Guide 🔭 A comprehensive article that demystifies the training-serving skew on ML models, which arises due to differences between training and serving environments in real-time ML models building.nubank.com.br/dealing-with-t… #ML
Stanford has put together an informative repo which introduces the "Foundation Model Transparency Index"; a framework which rates major AI providers like OpenAI and Google on their adherence to requirements specified in the EU Parliament's AI Act. Repo: github.com/stanford-crfm/…
New course from Andrew Ng's DeepLearning.AI in collaboration with AWS on Generative AI 🚀 It includes data gathering, model selection, performance evaluation, deployment, and how to adapt and optimize models to various use cases. deeplearning.ai/courses/genera… #ML #AI
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