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SUMMARY:AI\, ML and Computer Vision Meetup
DESCRIPTION:***Please Use Source Link Below to Confirm Event Details***\nJoin our virtual Meetup to hear talks from experts on cutting-edge topics across AI\, ML\, and computer vision. The seminar explores Visual Anomaly Detection (VAD) fundamentals\, core challenges\, and recent advancements leveraging vision-language models and multimodal large language models (MLLMs). The event is designed for researchers and practitioners interested in AI-driven inspection and next-generation multimodal approaches. \nOriginal Event: AI\, ML and Computer Vision Meetup
URL:https://sacitcentral.com/event/ai-ml-and-computer-vision-meetup/
LOCATION:Online via Zoom
ATTACH;FMTTYPE=image/jpeg:https://sacitcentral.com/wp-content/uploads/2026/01/event-75322-featured.jpg
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DTSTART;TZID=America/Los_Angeles:20260210T090000
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DTSTAMP:20260526T020210
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LAST-MODIFIED:20260103T051717Z
UID:75325-1770714000-1770717600@sacitcentral.com
SUMMARY:Build a Voice-Enabled AI Agent in Minutes
DESCRIPTION:***Please Use Source Link Below to Confirm Event Details***\nJoin us and learn how to build a production‑ready\, voice‑enabled AI agent with GitHub Copilot and Microsoft Foundry\, showcased through a hands‑on demo. Upgrade a Python podcast‑editing app using NVIDIA Parakeet for high‑accuracy local ASR and NVIDIA Nemotron on Azure for concise summaries\, titles\, and structured outputs. We’ll share proven patterns for model selection\, evaluation\, chaining\, orchestration\, responsible guardrails\, and automated DevOps deployment—plus the developer metrics that matter (latency\, throughput\, errors\, memory and GPU usage)—so you leave with a reusable blueprint for real applications. \nOriginal Event: Build a Voice-Enabled AI Agent in Minutes
URL:https://sacitcentral.com/event/build-a-voice-enabled-ai-agent-in-minutes/
LOCATION:Online event
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DTSTART;TZID=America/Los_Angeles:20260226T090000
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UID:75345-1772096400-1772100000@sacitcentral.com
SUMMARY:Data-Driven Apps with RAG with LangChain4j
DESCRIPTION:***Please Use Source Link Below to Confirm Event Details***\nBuild a complete Retrieval-Augmented Generation system that chunks documents\, creates semantic embeddings\, and finds relevant context for every question. Watch your AI answer questions about your own files with source citations and confidence scores\, grounded in facts rather than hallucinations. \nOriginal Event: Data-Driven Apps with RAG with LangChain4j
URL:https://sacitcentral.com/event/data-driven-apps-with-rag-with-langchain4j/
LOCATION:Online event
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