TechSmith Transition to Annual Subscription Pricing Model in 2025 â TechSmith Support
support.techsmith.com/hc/en-us/articles/27009223314701-TechSmith-Transition-to-Annual-Subscription-Pricing-Model-in-2025
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āļāļēāđāļāļīāļāđāļĨāđāļ Microsoft (āļāļĢāļ°āđāļāļĻāđāļāļĒ) āļĒāđāļēāļĒāļāļāļāļāļīāļĻāđāļŦāđāļāđāļŦāļĄāđāđāļāļĢāļāļ 30 āļāļĩ āļāļāļāđāļāļāļāļēāļāđāļŠāļĩāļĒāļāļāļāļāļāļāļąāļāļāļēāļāļāļāļāđāļāļāļĒāđ Hybrid Work
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ubuntu.pkgs.org/24.04/ubuntu-universe-amd64/slim_1.3.6-5.3build3_amd64.deb.html
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Earn Your RAG-ing Rights With MinIO
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Core Views on AI Safety: When, Why, What, and How
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Font Cartograph CF: download and install for free.
en.bestfonts.pro/font/download/600c045b6a101229c67525c5
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How Do I Terminate Active Resources That I No Longer Need on My AWS Account?
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Document Extraction Is GenAIâs Killer App
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Why Data Debt Is the Next Technical Debt You Need to Worry About
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āļĢāļ§āļĄ 13 āđāļŪāđāļĨāļāđ Kindle āđāļāļāļāļŦāļĄāļēāļĒāļāđāļēāļ§āđāļāļāļēāļĒ 2566
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Unlocking New Horizons: Large Language Models in Financial Services
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Alternatives To Airflow Exist! Â :)
jlgjosue.medium.com/alternatives-to-airflow-exist-bb2739a93b33
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Using Ollama and Ollama Web UI for a Free AI Chatbot Experience: A Guide for Those Hesitant AboutâĶ
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āļāļēāļĢāđāļāđ Terraform āđāļ Azure DevOps CD Pipeline
rachanee.medium.com/%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B9%83%E0%B8%8A%E0%B9%89-terraform-%E0%B9%83%E0%B8%99-azure-devops-cd-pipeline-d7de471d7902
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āļāļ§āđāļēāļāļ°āđāļāđ App āļāļĩāđ āļāļ KBTG āļāđāļāļāļāđāļēāļāļĩāđāļāđāļēāļāļāļĢāļŦāļąāļāļāđ
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āļāļķāļāļ§āļīāļāļē Docker Image & Container
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cobusgreyling.medium.com/time-aware-adaptive-rag-ta-are-11aafda9e9e7
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The Ultimate Quickstart Guide For Getting Started With Tana
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āļŠāļĢāđāļēāļāļŠāļĄāļĄāļāļīāļāļēāļāļāđāļ§āļĒāđāļ āļāļąāļāļŠāļīāļāđāļāļāđāļ§āļĒāļŠāļĄāļāļ
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Multi-Agent Orchestration & Conversations using Autogen, CrewAI and LangGraph
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āļŠāļĢāļļāļāļ§āļīāļāļĩ Deploy FastAPI āļāļāļ Python āļāļ Ubuntu
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Local RAG From Scratch
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skanda-vivek.medium.com/deploying-open-source-llms-as-apis-ec026e2187bc
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Synthetic Data: Behind the Impressive Performance of Phi-3
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Best practices for LLM optimization for call and message compliance: prompt engineering, RAG, andâĶ
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