Snowflake has unveiled its large language model (#LLM) called Snowflake Arctic tailored for enterprise use. This open #AI model, described as "enterprise-grade," is designed to handle complex enterprise tasks and has outperformed industry benchmarks in areas like SQL code generation and instruction following. #SnowflakeArctic will be provided with an Apache 2.0 license, enabling unrestricted personal, research, and commercial usage. Available for immediate use, Arctic can be utilized for serverless inference within Snowflake Cortex, a managed service offering machine learning and AI solutions in the Data Cloud. Additionally, the model will be accessible on various platforms such as Amazon Web Services (AWS), Microsoft Azure, NVIDIA API catalog, and more. Snowflake is also offering code templates and flexible training options to facilitate the customization of Arctic using preferred frameworks. Alongside Arctic LLM, Snowflake introduces Arctic #embed, a series of text embedding models, to its lineup. Follow Amanda Newman to stay up to date with technology. https://lnkd.in/dM-F5cFy
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🚀 Exciting Innovation in Search AI! 🚀 Search AI Lake and Elastic Cloud Serverless are here! A cloud-native architecture for real-time, low-latency search. 🌐 - Organizations will benefit from: Seamless Search: Search AI Lake can dive into vast amounts of unstructured data without needing metadata or tables, making it ideal for AI training, security, and observability workloads. - Scalability: By decoupling storage from compute, Elastic promises enormous scalability, making this tool perfect for training large language models (LLMs). - Advanced Search Capabilities: Supports traditional, vector, hybrid, and faceted search, enhancing applications like GenAI training and Retrieval Augmented Generation (RAG). - Interoperability: Uses the Elastic Common Schema (ECS) format and the Elasticsearch Query Language, enabling federated searches across diverse data sources. - Real-Time Processing: Built on the robust foundation of ElasticSearch, known for its real-time data processing and open-source roots. 👉 Learn more in @techzine article here: https://gag.gl/CogELL Join the conversation and share your thoughts on how this innovation could impact your data strategies! 💬 #DataInnovation #SearchTechnology #AITraining #BigData #ElasticSearch #GenAI #TechNews
Search AI Lake from Elastic makes diving into enormous 'data lakes' easier
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Unleash the Power of #LargeLanguageModels! 🚀 Text and images are just the beginning. Dive into the future by creating videos and groundbreaking solutions! 👁️🎥 Check out this mind-blowing article from Outerbounds for an example that will fuel your creative fire! 🔥✨ #InnovationUnleashed https://lnkd.in/dASKNDJc #generatieveai #llm #largelanguagemodels #generativevideo #gpu #metaflow #genai #ai #googlecloud #aws #azure #gcpcloud #mlops #llmops #ScalingGenAI #stablediffusion #stablevideodiffusion
Lights, GenAI, Action: Building Systems with Generative Video | Outerbounds
outerbounds.com
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Build an image similarity search application using Azure AI Vision and Azure Cosmos DB for PostgreSQL. Vector search, multi-modal embeddings APIs, and pgvector extension. Search for paintings based on image or text. https://lnkd.in/dBd5DWNb
Generate embeddings with the Azure AI Vision multi-modal embeddings API
techcommunity.microsoft.com
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AI and .NET: Exploring the AI samples repo and the model evaluation sample #azure #microsoft
AI and .NET: Exploring the AI samples repo and the model evaluation sample
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Ever wondered how to conquer the AI landscape like a true Spartan 🏹 Unleash your inner warrior with our latest blog post about #RAG on N23 Studio In this blog, we’ll dive into what RAG is, how it works, it's incredible applications, and how you can quickly deploy a #RAG application using tools like #Ray, LangChain, and Hugging Face on @Google Kubernetes Engine #GKE and Cloud SQL. https://lnkd.in/gJ3Pt7in #AILearning #N23Studio #GenerativeAI #WomenWriters
The Revolution is Here: And RAG is Leading the Troops
medium.com
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2024 will see a huge wave of #GenAI applications going into production, and these new apps must offer great search performance. Sharing our exciting price/perf news for #Azure AI Search to help our customers meet the moment! Users will now see up to: - 11x increase in vector index size - 6x increase in total storage - 2x improvement in indexing and query throughput
Announcing updates to Azure AI Search to help organizations build and scale generative AI applications | Microsoft Azure Blog
https://azure.microsoft.com/en-us/blog
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Announcing .NET Conf: Focus on AI – August 20th 2024 Following are the sessions planned: 1. Getting Started with AI in Your .NET Applications 2. Better Together: .NET Aspire and Semantic Kernel 3. Interactive AI with Blazor and .NET 4. Navigating the World of AI Models in .NET: From Local Development to the Cloud 5. RAG on Your Data with .NET, AI, and Azure SQL 6. Integrating Semantic Search Capabilities with .NET and Azure: Milvus Vector Database 7. H&R Block: Lessons Learned from Applying Generative AI to Apps with .NET and Azure #dotnet #azure #ai #sql #aimodels
Announcing .NET Conf: Focus on AI - August 20th 2024 - .NET Blog
https://devblogs.microsoft.com/dotnet
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Databricks' new large language models, databricks/dbrx-base and databricks/dbrx-instruct are already in the Microsoft Azure AI Model Catalog! DBRX stands as a pioneering Mixture-of-Experts (MoE) model, crafted atop the innovations of the MegaBlocks research and open-source initiative from Databricks. This design propels the model to achieve remarkable speed in tokens per second, setting a precedent for future state-of-the-art open-source models to adopt MoE architectures. With 132B parameters, of which 36B are activated for any given input, training on a vast corpus of 12T tokens sourced from meticulously selected data, and support for up to 32K tokens in context length, DBRX demonstrates great capabilities. #Microsoft #Azure #MicrosoftAzure #AI #GenerativeAI #Databricks #LLM
Elevating AI with Databricks on Azure: Introducing the Latest Large Language Models
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Here is our latest Generative AI blogpost "Dive deep into vector data stores using Amazon Bedrock Knowledge Bases" to understand why vector databases are important and how Amazon Bedrock makes it easy to implement your Retrieval Augmented Generation (RAG) use cases by providing options for managing various Vector Databases using common set of APIs: https://lnkd.in/gM_sGNbP It was a great collaboration team (Vishwa Gaurav Gupta, Ginni Malik, Abhishek Madan, Isaac Privitera) !! #genAI, #aws, #awscloud,
Dive deep into vector data stores using Amazon Bedrock Knowledge Bases | Amazon Web Services
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Exciting news for developers! Azure AI Search and LlamaIndex have teamed up to bring you a comprehensive RAG framework and state-of-the-art retrieval system. The collaboration enables developers to build better applications with advanced retrieval-augmented generation (RAG). Check out the link to learn more about Advanced RAG with Azure AI Search and LlamaIndex. #AI #Azure #Search #RAG #Development #MSFTadvocate
Advanced RAG with Azure AI Search and LlamaIndex
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