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Similarity vs. Distance, illustrated using circles⭕️ by hand✍️ ~ Cornelius (Cornelius Adejoro), my PhD student, is creating a new short video series on RAG and AI Agents. Each video covers one concept or technique. Here is our first pilot video for feedback!

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Tom Yeh

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19,858 görüntüleme • 1 yıl önce •via X (Twitter)

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Join the "RAG and AI Agent Developers" community!

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@specialcornel Great video! Looking forward to seeing more.

Benzer Videolar

In this short video, I explain the concept of RAG (Retrieval-Augmented Generation) in a simple and easy-to-understand way. I hope it helps! Let me know your thoughts. The material is based on Prof. Tom Yeh's 'AI by Hand' resources.
3:45

In this short video, I explain the concept of RAG (Retrieval-Augmented Generation) in a simple and easy-to-understand way. I hope it helps! Let me know your thoughts. The material is based on Prof. Tom Yeh's 'AI by Hand' resources.

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Cornelius Music Video ”夢寝見 / Yumenemi” Watch now on Youtube! #コーネリアス #小山田圭吾 #cornelius #keigooyamada @eatyourownears
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I created a full AI short film based on my hand-drawn storyboard! This free workflow is perfect for pre-visualization for movie productions, precise concept art, AI movies or creating panels for graphic novels. Here's how it works👇
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[Transformer] by Hand✍️📺 5-minute Video Tutorial Anna Rahn made this short video to explain the Transformer exercise for my Computer Vision course last spring. In 5 minutes, she demonstrates the key calculations of the Transformer by hand with pen and paper! Anna is a fantastic student. I am lucky to have her in my lab!
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[Transformer] by Hand✍️📺 5-minute Video Tutorial Anna Rahn made this short video to explain the Transformer exercise for my Computer Vision course last spring. In 5 minutes, she demonstrates the key calculations of the Transformer by hand with pen and paper! Anna is a fantastic student. I am lucky to have her in my lab!

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A short video on how to use the free site for creating Ai video/Animation
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🚨 FIRST REAL $SUI AI PROJECT IS HERE Bluwhale is going live as the first legit AI protocol on $SUI. Win a BluWhale node and a future free mint by dropping a funny comment under the YouTube video, not on X. My new PFP is the whale 🐋 YouTube video here 👇👇👇
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🚨 FIRST REAL $SUI AI PROJECT IS HERE Bluwhale is going live as the first legit AI protocol on $SUI. Win a BluWhale node and a future free mint by dropping a funny comment under the YouTube video, not on X. My new PFP is the whale 🐋 YouTube video here 👇👇👇

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P-video by Pruna AI is here. 10¢ for 10 second video, done in < 10 seconds, with native audio. The video below was made using P-video. And it's free for the first 24 hours!
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P-video by Pruna AI is here. 10¢ for 10 second video, done in < 10 seconds, with native audio. The video below was made using P-video. And it's free for the first 24 hours!

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Cornelius K. Ronoh Nimekuja na evidence ya video.
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Cornelius K. Ronoh Nimekuja na evidence ya video.

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"Hello. I'm Cornelius Talmadge. My family brought me here on Monday, but I broke free and went on a bit of a bender!" "Wait a minute. If you're Cornelius Talmadge, then who's-"
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Our newest AI Short Film “PAPER JAM”! Each keyframe was animated by hand based on AI generated 3D models. "Rendered" using Flux + regional Loras in ComfyUI and interpolated using Kling AI
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New short course on advanced retrieval for RAG (retrieval augmented generation)! RAG fetches relevant documents to give context to an LLM. In Advanced Retrieval for AI with Chroma, taught by Chroma founder anton 🇺🇸, you’ll learn: (i) Query expansion using an LLM to rewrite and improve a query, by either generating either additional relevant queries or a hypothetical answer to the query. (ii) Reranking using a cross-encoder - a model trained to measure similarity between two inputs presented simultaneously. Reranking reorders retrieved documents based on the cross-encoder similarity measure. (iii) Constructing and training an Embedding Adaptor, which is a model that adapts the embedding values to be more relevant to your use case. Each of these techniques can help you build much better RAG systems. Please sign up for the course here:
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New short course on advanced retrieval for RAG (retrieval augmented generation)! RAG fetches relevant documents to give context to an LLM. In Advanced Retrieval for AI with Chroma, taught by Chroma founder anton 🇺🇸, you’ll learn: (i) Query expansion using an LLM to rewrite and improve a query, by either generating either additional relevant queries or a hypothetical answer to the query. (ii) Reranking using a cross-encoder - a model trained to measure similarity between two inputs presented simultaneously. Reranking reorders retrieved documents based on the cross-encoder similarity measure. (iii) Constructing and training an Embedding Adaptor, which is a model that adapts the embedding values to be more relevant to your use case. Each of these techniques can help you build much better RAG systems. Please sign up for the course here:

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My Complete Jinx Guide is out now! This is my first video guide and I would really appreciate any feedback on the video. ▶️
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My Complete Jinx Guide is out now! This is my first video guide and I would really appreciate any feedback on the video. ▶️

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NEW QUICK CATCH METHOD USING ONE HAND! first found by u/Jomiph on Reddit and GooblyMeat on YouTube, this is a new bug(?) meaning you can now quick catch using one hand! (be warned however, feeding berries in gyms and battling gyms is affected by this)

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Today, we’re excited to announce the general availability of the Contextual AI Platform. This is the first enterprise platform designed for building specialized RAG agents to support expert knowledge work. What is a specialized RAG agent? First, a general-purpose AI agent is one designed to automate simple daily tasks like scheduling a meeting or responding to an email. On the other hand, a specialized RAG agent is one designed to augment subject-matter experts performing complex domain-specific work. The Contextual AI Platform allows you to create these agents easily and achieve SOTA accuracy right out of the box. Check out what the Contextual AI Platform can do.
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Today, we’re excited to announce the general availability of the Contextual AI Platform. This is the first enterprise platform designed for building specialized RAG agents to support expert knowledge work. What is a specialized RAG agent? First, a general-purpose AI agent is one designed to automate simple daily tasks like scheduling a meeting or responding to an email. On the other hand, a specialized RAG agent is one designed to augment subject-matter experts performing complex domain-specific work. The Contextual AI Platform allows you to create these agents easily and achieve SOTA accuracy right out of the box. Check out what the Contextual AI Platform can do.

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2:37

I'm excited to share my talk on building Agentic RAG systems at last week's event with Arize AI and Google! 🥳 My talk covered: 1. The differences between Vanilla RAG and Agentic RAG 2. The agent ecosystem and how you can build agents today 3. How Weaviate AI Database is building agents with Generative Feedback Loops (GFLs) This snippet presents the multi-agent paradigm for Agentic RAG. I hope you find this talk interesting and would love to know what you think! The slide deck and full video links are below.

Erika Shorten

61,317 görüntüleme • 1 yıl önce