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Open-Source Hybrid Keyword and Semantic Search Engines

OpenSearch (Elasticsearch Open Source Fork) • Ease of Setup & Scalability: OpenSearch is a drop-in replacement for Elasticsearch, offering easy cluster deployment via Docker or managed services. It’s built on Lucene, so it scales horizontally and handles large indexes reliably. Unlike Elasticsearch’s basic tier, OpenSearch has no license restrictions on advanced features , making it fully open-source and cost-free to scale out. • Semantic Search Flexibility: OpenSearch supports dense vector fields (knn_vector) for embeddings and can execute kNN (nearest neighbor) searches natively . It enables hybrid search: you can combine traditional BM25 keyword matches with semantic vector similarity in one query . For example, a query can have both a full-text component and an embedding-based component, with their scores fused. It also provides a Neural Search plugin to automate embeddings – you can configure a transformer model in an ingest pipeline to generat

@Dicklesworthstone
Dicklesworthstone / Transcript.txt
Created February 27, 2025 14:57
Singer Interview Transcript
Hi, everybody. I'm Nikolaj Tangen of the Norwegian Southern Wealth Fund. And today we are hosting an investor legend, Paul Singer, who founded Elliott Asset Management and probably the most important activist investor in the world. Paul, warm welcome. Thank you.
What is activist investing? Activist investing is taking a position largely in an equity security of a company and trying to engage with the company to improve outcomes, control or influence outcomes, better outcomes to unlock value. It could be management changes that are requested. It could be capital structure changes, finance strategies and tactics. Anything that will make the company earn more money, be better positioned, more rationally deploy assets.
Why do you have to do this? Don't companies do this themselves? Well, as you know, the trend away from active investing, and by active investing, I don't necessarily mean activist. Active investing just means you open the mail from the company in which you invest, you try to figure it out, you t

​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​To dramatically enhance the code I provided, I’ll incorporate key techniques and optimizations from QuakeWorld, as suggested by @doodlestein and detailed in the web results (Web:0, Web:1, Web:3). QuakeWorld, an optimized multiplayer version of Quake, is renowned for its low-latency, scalable network architecture, using UDP, client-side prediction, delta compression, and interpolation. I’ll apply these principles to @levelsio’s server-based multiplayer flight simulator, focusing on minimizing latency, reducing bandwidth, and ensuring smooth gameplay. Here’s an enhanced version of the code:

Key QuakeWorld Optimizations Applied:

  1. UDP for Low-Latency Communication:

    • Use UDP (via dgram in Node.js for the server) for unreliable, low-latency updates, avoiding TCP’s overhead. For the client, I’ll simulate UDP behavior with WebRTC DataChannels in browsers, maintaining QuakeWorld’s approach.
  2. Client-Side Prediction with Dead Reckoning:

  • Predi