Roy Budhaditya

Open Source models are on the rise and getting better every day. Snowflake has recently released five models in various sizes on Hugging Face, which is great news for anyone looking to leverage AI through RAG or a semantic search service. If you're interested in leveraging the latest developments in AI, this is definitely worth checking out. #AI #opensource #Snowflake #HuggingFace #RAG #semanticsearch

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A cool use of the “contribution analysis” ML model to answer the “why” kind of business questions. Combined with Gen AI, it enables quick insights for any enterprise.

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If you are thinking of creating GenAI applications on Amazon Web Services (AWS) and are thinking of a vector database offering. Please checkout our ISV Solutions via AWS Marketplace : DataStax, Redis, Neo4j and several others depending on your use-case. Amit V. Singh explains in this blog on the various offerings that we have and happy to engage with customers and Partners for more in-depth conversations around this. https://lnkd.in/gMcBAEpJ Ian Mercer, Subodh Kumar, Allan H. P. Lee, Greg Scanlan

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It gives us great pleasure to announce that Apache Spark in BigQuery is now officially available in Private Preview. This feature expands BigQuery’s processing capabilities by offering Apache Spark as an OSS processing engine under a unified control plane (admin, monitoring, billing, security, governance). It is the first step in delivering on the Unified Data Platform vision and was a key announcement at Next ‘24 #googlecloud #bigquery #spark

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Check out this Q&A with Capital One’s Head of AI Product, @Aparna Sinha, where she shares advice on building enterprise AI/ML capabilities. The conversation touches on the importance of product management in AI, Capital One’s AI/ML priorities, advice for those looking to break into the industry and so much more! Read it now on the Capital One tech blog

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Interesting thoughts from Junta N. about #AI use cases in #insurance.

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Serverless task for Python, Java, and Scala UDF/Stored Procs in #Snowflake Preview https://lnkd.in/gEtcQ5t9 #datalake #snowflake #newfeatures

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🚀 Exciting day at Snowflake Data Cloud World Tour Mumbai 2024! ❄️ I had the privilege of attending the Snowflake Data Cloud World Tour in Mumbai, and here are some key takeaways from insightful sessions on the future of data and AI: 📊 Open Table Formats & Iceberg Support Exploring integration possibilities with Apache Iceberg and Polaris Discussions on ACID compliance, performance optimization, and data evolution 🛡️ Snowflake Horizon Unveiling a vision for unified data governance and security across clouds Concepts for simplifying management of data and apps from a centralized interface 🤖 Generative AI & LLMs Introduction to the Snowflake Arctic family of Large Language Models (LLMs) Exploring Snowflake Cortex as a pathway to democratize AI Emphasis on the "AI to Data, not Data to AI" approach for enterprises 🔒 Data Governance & Security Highlighting the importance of unified security and compliance measures Showcasing potential applications of Dynamic Data Masking for data protection 💻 Snowpark Container Service & ML API Demonstrations of running AI and full-stack apps within the Snowflake ecosystem Exploring possibilities for direct ML model execution and predictions 🔗 Native Apps & Data Sharing Discussing streamlined approaches to building and sharing data applications Insights into enhancing operational collaborations through data sharing 📄 Document AI & Unstructured Data Previewing tools aimed at extracting insights from unstructured data The event showcased Snowflake's vision for innovation, open standards, and efficient data management. It was fascinating to see the proposed solutions for various data challenges, from governance to AI implementation. Kudos to the speakers, including Sanjay Deshmukh Vijayant Rai Rahul Jain 🇮🇳 Kamesh Sampath and Sumeet Tandure Excited to contemplate how these concepts might shape our future data strategies! #SnowflakeWorldTour #DataCloud #AI #DataGovernance #Innovation

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When managing Snowflake at scale, it can be difficult to balance cost and performance. Capital One Slingshot makes it easier, building on tools we created internally to help our own teams streamline provisioning, optimize workloads and reduce query inefficiencies. See how Slingshot can help you maximize your #Snowflake investment. https://bit.ly/3YyE4zk

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Contextual Retrieval from Anthropic increases RAG retrieval accuracy. Combining that with re-ranking will improve retrieval accuracy significantly. Contextual Retrieval uses Contextual Embeddings and Contextual BM25. Contextual Embeddings add contextual information and Contextual BM25 uses lexical matching. In essence it performs a hybrid search that combines semantic search and lexical search to provide comprehensive search results. It is also possible to do with lower costs, thanks to Claude's prompt caching. Read more about this here https://lnkd.in/gjavM3gD

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Big news for the AI community! Databricks has developed DBRX, a new open Large Language Model that surpasses models like GPT-3.5 and competes with Gemini 1.0 Pro. DBRX uses a sophisticated mixture-of-experts architecture that boosts both inference and training speeds while being more efficient than traditional dense models. This model is already integrated into Databricks’ GenAI-powered products and is available for access on Hugging Face. Enterprises can now develop their own MoE foundation models using Databricks tools and NVIDIA hardware, showcasing the powerful capabilities available for AI development. Read more about DBRX and its impressive capabilities on Databricks' blog: #ai #LLM #databricks #dbrx #genai

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Capital One Slingshot helps you optimize Snowflake in several ways, like warehouse recommendations. It saves you time by rightsizing warehouses and optimizing compute with data-driven suggestions based on historical usage and warehouse metadata. And you’ll love how Slingshot shows the work so you can understand and evaluate each recommendation in detail. https://bit.ly/3ANlg7H

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We just refreshed our performance benchmark showing that Mixpanel is up to 7x faster than data warehouse funnel queries. People often ask how we compare to traditional BI tools. While SQL will always have its place, using BI tools for analytics is going to feel more and more like continuing to use the fax machine when email came out. Keep using the warehouse for what it’s meant for: storing and processing business data. With Mirror and our new Warehouse Connectors, bring your trusted data into Mixpanel to automate your reporting and experience true interactive self-serve analytics. https://lnkd.in/dnNawYWa

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HIGHLY recommend this real-world use case of operationalizing ML pipelines with INVISTA a Koch Industries subsidiary. Feature Engineering ✅ Model Training ✅ Model Registry ✅ Orchestration via DAGs (Snowflake Task API) ✅ #MLOps #datasceince #dataengineering #snowflake

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Introducing Databricks Apps – a new way to build internal data + AI applications! Build custom data visualizations, AI applications, and self-service analytics directly on Databricks!

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Serverless compute for Databricks Notebooks, Workflows, and Delta Live Tables is now available! Check out my blog post on how to get started using Databricks Serverless Compute with Azure Data Factory pipelines 🚀 New templates to launch Databricks Serverless compute are also available directly through the Azure Data Factory Template Gallery. https://lnkd.in/ePYSrFc8

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If you'll be at the #DataAISummit, join Ashok Singamaneni and myself (Scott Haines) as we teach you the ropes of building "Effective Lakehouse Streaming with Delta Lake and Friends". https://lnkd.in/gqmcJmRC We'll be teaching lessons learned (the hard way), and showing how streaming-first is the correct fit for "most" if not all your workflows. Learn to leverage #DeltaLake like an expert, and we'll introduce you to some effortless patterns for making your streaming journey a breeze. You'll also hear from Ashok Singamaneni as we talk about how to leverage painless workflow orchestration with #brickflow, and how to build data trust-networks using #sparkexpectations. #spark #deltalake #sparkexpectations #brickflow #nike #oss #dataai

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In this blog, me and my colleagues Venkata Kampana, Muhammad qazafi discuss how Amazon Web Services (AWS) Bedrock enables Q&A of complex financial documents https://lnkd.in/eGEN3rR9

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