Josh Long

Structured extraction schema iteration is often more expensive that it should be. Check the latest blog by Shanshan Wang to learn how you can iterate on your extraction task with Tensorlake. https://lnkd.in/dTBusmWU

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New! Check out how to deploy Frontier LLMs such as DeepSeek R1 in a multi-node GPU cluster on Kubernetes Inside this blog, you have access to detailed guides to do this in two modes: 🔹 Managed Ray on Anyscale -- LLM deployment with highest resilience, seamless scaling and advanced observability all inside your account via bring-your-own-cloud (BYOC). 🔹 Self-Managed Ray on GKE -- Customize deployment to your needs, leveraging the scale of Google Kubernetes Engine Learn more: https://lnkd.in/gd6-4XV7

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Implementing CDC using Spring Boot, Debezium’s embedded engine, and YugabyteDB offers a compelling strategy for real-time data synchronization without the complexities of a dedicated middleware.💡 Discover why this embedded approach is ideal for scenarios that require simplicity, low latency, and reduced operational complexity.⬇️ https://hubs.la/Q03pscYY0

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The most effective architectural changes are often subtractive - removing entire layers of cost and complexity. Behind the scenes, OpsHelm, Inc.'s streaming backbone was migrated from a costly MSK and unreliable NATS setup to a single diskless Kafka architecture. The results were immediate: - Annual spend dropped from >$50,000 to <$10,000. - Data loss incidents went from recurring to zero. - Manual scaling and cross-cloud networking fees were eliminated. Read the full story of their migration and 78% cost reduction: https://lnkd.in/dS6UK9-7 #disklesskafka #datastreaming #Aiven

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Still confused between MCP, A2A, and Functional Calling? These three approaches are reshaping how LLMs and agents operate at scale, but each one solves a very different problem. Let’s break it down 👇 1. Model-Context Protocol (MCP) MCP manages dynamic context windows across enterprise LLM infrastructure. It retrieves prior memory, history, and metadata to personalize every response without hardcoding logic into prompts. 2. Agent-to-Agent Protocol (A2A) In A2A, agents talk to each other directly using shared protocols. Think of it as collaborative problem-solving between specialized local agents, especially useful in multi-agent ecosystems. 3. Functional Calling Here, an LLM acts like a planner. It decomposes a task (e.g., comparing market caps), generates a Directed Acyclic Graph (DAG) of subtasks, and then sends each task to appropriate tools (math, search, APIs) for execution. Conclusion - MCP is about managing context, - A2A is about agent collaboration, - Functional Calling is about task execution. Mastering all three is key to building powerful, production-ready AI systems. Save this visual for your next AI project!

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End-of-day workloads just got faster with KDB-X.​ ​ In Ryan Siegler’s latest blog, he breaks down how GPU acceleration will reshape core time-series operations in KDB-X, delivering major performance gains for large-scale financial workloads.​ ​ He explains how​: - GPU acceleration delivers 4–10x faster performance.​ - NVIDIA CUDA and cuDF integration introduce massively parallel processing.​ - GPUDirect Storage enables faster, more efficient pipelines.​ - Multi-GPU scaling with NVIDIA H100s cut complex risk simulations like VaR from seconds to milliseconds.​ ​ KDB-X is ready for the next generation of high-performance financial and analytical workloads. Read the full breakdown: https://lnkd.in/eq-8K5mx

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LLVM IR is often seen as just an internal detail, but it’s actually a powerful runtime execution surface with real-world impact. Our latest article dives deep into LLVM IR–based JIT execution, practical debugging techniques for the whole pipeline, and advanced strategies for detecting IR-based payloads in live environments. This piece is a must-read for defenders, reverse engineers, and anyone working close to runtime behavior. Whether you’re looking to strengthen your understanding or enhance your detection capabilities, don’t miss out! Check out the article and elevate your knowledge of LLVM IR today. Munaf Shariff Read more here: https://lnkd.in/guY2umR5

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