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The 1926 Alabama football team was selected national champions by Billingsley and the Helms Athletic Foundation The 1964 Alabama football team was selected national champions by the AP Poll and the Coaches' Poll prior to bowl games Because of the controversy with Alabama being selected over undefeated Arkansas, the AP Poll decided to wait until after the bowl games to select their champion for the 1965 season. The 1973 Alabama football team was selected national champions in the final regular season Coaches' Poll, which was finalized prior to the post-season bowl games. Because of the controversy after the bowl loss, the Coaches' Poll began selecting their champion after the bowl games starting in 1974. The post-bowl game AP poll ranked Alabama 4th, and selected Notre Dame as its national champion. I don’t know who wrote this song, Embedded Video was sent to me. If anyone knows who wrote the song please let me know so that I may give proper credit

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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.

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Tracing the root cause of a performance issue requires a lot of patience, experience, and focus. It’s so hard that we sometimes attempt to guess by trying out tentative fixes, but that usually results in frustration, messy code, and a considerable waste of time and money. This talk explains how to correctly zoom in on a performance bottleneck using three levels of profiling: distributed tracing, metrics, and method profiling. After we learn to read the JVM profiler output as a flame graph, we explore a series of bottlenecks typical for backend systems, like connection/thread pool starvation, invisible aspects, blocking code, hot CPU methods, lock contention, and Virtual Thread pinning, and we learn to trace them even if they occur in library code you are not familiar with. Attend this talk and prepare for the performance issues that will eventually hit any successful system. About authorWith 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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Autumn

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