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.Weaviate AI Database is an AI-native vector database that allows you to store data objects and vector embeddings from your favorite machine learning models while scaling seamlessly into billions of data objects. AWS and NVIDIA work together in an ecosystem to deliver cost performance and efficiency for Weaviate. Weaviate...

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1,472,993 views • 15 days ago •via X (Twitter)

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.Snorkel AI helps organizations leverage their own data and expertise to build high-quality, specialized AI systems orders of magnitude faster than fully manual approaches. The company drives value in partnership with AWS and NVIDIA to help their customers. Available in AWS Marketplace, Snorkel’s AI Data Development platform enables enterprises to turn their proprietary data and domain knowledge into expert evaluation and training data, with options for in house data development or white glove dataset delivery.
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.Snorkel AI helps organizations leverage their own data and expertise to build high-quality, specialized AI systems orders of magnitude faster than fully manual approaches. The company drives value in partnership with AWS and NVIDIA to help their customers. Available in AWS Marketplace, Snorkel’s AI Data Development platform enables enterprises to turn their proprietary data and domain knowledge into expert evaluation and training data, with options for in house data development or white glove dataset delivery.

AWS Startups

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New short course: Building Multimodal Search and RAG", by Weaviate AI Database's Sebastia(N_) Witalec ✊🏽✊🏾✊🏿. Contrastive learning is used to train models to map vectors into an embedding space by pulling similar concepts closer together and pushing dissimilar concepts away from each other. This technique is also used to train multimodal embedding models that capture semantic similarity across different modalities like text, images, and audio. These multimodal embeddings can be used to build multimodal search and RAG systems. In this course, you'll learn how contrastive learning works, and how to add multimodality to RAG – so your models can draw on diverse, relevant context to answer questions. For example, a query about a financial report might synthesize information from text snippets, graphs, tables, and slides. You will also learn how visual instruction tuning lets you integrate image understanding into language models, and build a multi-vector recommender system using Weaviate’s open-source vector database. Please sign up here:
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New short course: Building Multimodal Search and RAG", by Weaviate AI Database's Sebastia(N_) Witalec ✊🏽✊🏾✊🏿. Contrastive learning is used to train models to map vectors into an embedding space by pulling similar concepts closer together and pushing dissimilar concepts away from each other. This technique is also used to train multimodal embedding models that capture semantic similarity across different modalities like text, images, and audio. These multimodal embeddings can be used to build multimodal search and RAG systems. In this course, you'll learn how contrastive learning works, and how to add multimodality to RAG – so your models can draw on diverse, relevant context to answer questions. For example, a query about a financial report might synthesize information from text snippets, graphs, tables, and slides. You will also learn how visual instruction tuning lets you integrate image understanding into language models, and build a multi-vector recommender system using Weaviate’s open-source vector database. Please sign up here:

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$AMZN AWS launched Amazon Quick which is a desktop AI assistant that works across your apps and data to surface what matters and take action. This is agentic AI turning the inbox into an archive and becoming the layer that prioritizes and handles the busywork.
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Erika Shorten

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Last week at NVIDIA GTC, the AWS 2026 AI Pitch Competition offered 6 early-stage AI companies the opportunity to compete for up to $25,000 in AWS credits, dedicated mentoring support from AWS and NVIDIA (through their Inception program), and exposure to senior leaders from AWS, NVIDIA, and top-tier VC firms. Startups Keyframe Labs, Kuvia, @NomadicML, Tynapse, Saptiva, and Bindwell pitched to a panel of judges, presenting their technical and business models to the audience that gathered at the AWS booth. Nomadic took first place, followed by Kuvia in second and Bindwell in third. Each founder brought their A-game to the table, and we're excited to continue supporting them as they grow!
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How to Train Your AI NFT (Introducing TolyAI) On-chain Clone We gathered Toly's Twitter activity from 2023 to 2025 and used it to create our SANA AI NFT. This allows you to ask questions and get answers that reflect Toly's Twitter style. The data is stored in a vector database, with the indexes secured on-chain via Metaplex Core APP DATA. We've made this agent openly available for everyone to use. Soon, anyone will be able to train their own AI NFT and store it on-chain. Toly Agent: Core Data: Dataset:
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Amazon Web Services

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.Zammoai built an Azure managed application on Microsoft Marketplace for faster time to value with one-click deployment in customer tenants, secure data control, and rapid scaling of AI agent solutions. Learn more:
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ColPali is changing the game for PDF retrieval by eliminating the need for OCR and chunking methods 🚀 Inspired by ColBERT’s success with text, ColPali splits an image of a document into patches, which are then processed through a vision LLM called PaliGemma. The embeddings for each patch retain contextual information, similarly to text embeddings in methods like ColBERT. During retrieval, user queries are embedded in the same space, and then compared to document patches using the MaxSim operator. ColPali recipe POC Weaviate AI Database: ColPali paper: As always, shoutout to the awesome Daniel Williams for the help! 💙

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AWS DevOps Agent is now generally available. Your always-available operations teammate that autonomously investigates incidents the moment an alert comes in, reducing mean time to resolution from hours to minutes across AWS, multicloud, and on-prem environments. Get proactive recommendations that prevent future incidents and strengthen system resilience based on patterns across historical incidents.
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AWS DevOps Agent is now generally available. Your always-available operations teammate that autonomously investigates incidents the moment an alert comes in, reducing mean time to resolution from hours to minutes across AWS, multicloud, and on-prem environments. Get proactive recommendations that prevent future incidents and strengthen system resilience based on patterns across historical incidents.

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