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Explore how multimodal embeddings work with Milvus. We will see how you can explore a popular multimodal model - CLIP - on a popular dataset - CIFAR 10. You use CLIP to create the embeddings of the input data, Milvus to store the embeddings of the multimodal data (sometimes termed “multimodal embeddings”), and we will then explore the embeddings.
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Elevate Developer Efficiency & build GenAI Application with Amazon Q
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Understanding the FAA Part 107 License ..
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Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
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In this keynote, Asanka Abeysinghe, CTO,WSO2 will explore the shift towards platformless technology ecosystems and their importance in driving digital adaptability and innovation. We will discuss strategies for leveraging decentralized architectures and integrating diverse technologies, with a focus on building resilient, flexible, and future-ready IT infrastructures. We will also highlight WSO2's roadmap, emphasizing our commitment to supporting this transformative journey with our evolving product suite.
Platformless Horizons for Digital Adaptability
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Retrieval augmented generation (RAG) is the most popular style of large language model application to emerge from 2023. The most basic style of RAG works by vectorizing your data and injecting it into a vector database like Milvus for retrieval to augment the text output generated by an LLM. This is just the beginning. One of the ways that we can extend RAG, and extend AI, is through multilingual use cases. Typical RAG is done in English using embedding models that are trained in English. In this talk, we’ll explore how RAG could work in languages other than English. We’ll explore French, Chinese, and Polish.
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
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The microservices honeymoon is over. When starting a new project or revamping a legacy monolith, teams started looking for alternatives to microservices. The Modular Monolith, or 'Modulith', is an architecture that reaps the benefits of (vertical) functional decoupling without the high costs associated with separate deployments. This talk will delve into the advantages and challenges of this progressive architecture, beginning with exploring the concept of a 'module', its internal structure, public API, and inter-module communication patterns. Supported by spring-modulith, the talk provides practical guidance on addressing the main challenges of a Modultith Architecture: finding and guarding module boundaries, data decoupling, and integration module-testing. You should not miss this talk if you are a software architect or tech lead seeking practical, scalable solutions. About the author With two decades of experience, Victor is a Java Champion working as a trainer for top companies in Europe. Five thousands developers in 120 companies attended his workshops, so he gets to debate every week the challenges that various projects struggle with. In return, Victor summarizes key points from these workshops in conference talks and online meetups for the European Software Crafters, the world’s largest developer community around architecture, refactoring, and testing. Discover how Victor can help you on victorrentea.ro : company training catalog, consultancy and YouTube playlists.
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FWD Group - Insurer Innovation Award 2024
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3b experiment involving one lab pasito and federica-ghent
1.
Experiment involving PASITO,
FEDERICA and OneLab Víctor López , Jaime Garnica, Jose Luis Añamuro Víctor Moreno, Jorge López de Vergara, Javier Aracil Ghent 15 December 2010
2.
3.
4.
5.
6.
7.
Thanks Questions?
[email_address]