Sandipan Bhaumik 🌱

Ola Krutrim , India’s first AI unicorn, recently launched its LLM, Krutrim-7B-chat. This new model is trained in 10 Indian languages and is available on Databricks Marketplace. It can generate text in Hindi, English, Tamil, Telugu, Marathi, Malayalam, Gujarati, Bengali, and Kannada. This is the first of several India-specific models trained by Ola Krutrim. It has been trained on a massive dataset of Indic languages— “Krutrim delivers text infused with Indian sensibilities and cultural awareness.” Check out the model here. The announcement came to light at the Data Intelligence Day in Mumbai on May 10, 2024, by Gautam Bhargava, VP & Head of AI Engineering at Krutrim. “We’re excited to be at the forefront of building foundational LLMs trained on Indian languages to better serve our customers in India. We have been working very closely with the Databricks team to pre-train and finetune our foundational LLM,” said Bhargava. He added, “We are confident that Krutrim, our base model, will be able to provide high-quality responses in Indian languages and dialects.” According to Bhargava, Krutrim was trained using Databricks Mosaic AI Training’s GPU orchestration and system optimisations, enabling state-of-the-art generative AI solutions for customers globally. The model is now available on the Databricks Marketplace.

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Gemini in BigQuery changes the game for data engineers and analysts! More productivity ✔️ Improved query performance ✔️ Optimized costs throughout the analytics lifecycle—from ingestion and pipeline creation to deriving insights with AI ✔️ #GoogleCloudNext

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🇮🇳 How does Skyflow help drive DPDP compliance in India 🇮🇳? 🇮🇳 How does Skyflow protect data in LLMs? 🇮🇳 And in Snowflake ❄️? And Databricks 🧱? 🇮🇳 Check out our story in India’s leading tech publication YourStory Journal 🇮🇳 Link in comments.

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Watch Sir Martin Sorrell, CEO of S4 Capital, take on The Pack: https://lnkd.in/dbJz69-T He talks about the revolution AI is driving in advertising and media, the skills you need, and even his favourite biscuits 🍪. #GoogleCloudThePack is a new 🎥 series taking on the big topics in smart data & AI, security, sovereignty and sustainability.

📅 *Today* - Tuesday, October 22nd, 2024 11:00 AM PT [▶][▶] 👨‍💻👨‍💻Join Abhishek Narain and Wilson Lee for "Unlocking AI at Scale with Data Factory in Microsoft Fabric"! 📊 Efficiently managing high-volume, complex data is critical for building scalable AI solutions. Data Factory in Microsoft Fabric streamlines the process of ingesting, transforming, and orchestrating data, making it easier to prepare and integrate diverse data sources for AI applications 🔬Join this session to explore how Data Factory can help automate data workflows, enabling seamless data preparation for AI models. Learn how to design scalable data pipelines, automate data transformation, and optimize data integration, all within the Microsoft Fabric ecosystem. This is your chance to unlock the full potential of AI using Data Factory!. 🚀🔥Don’t miss this opportunity to learn and do more with AI in Microsoft Fabric. Register now for the Microsoft Fabric & AI Learning Hackathon and livestream series! Check out the "Microsoft Fabric & AI Learning Hackathon" on Devpost: https://lnkd.in/gwSAyWhE See the full "Microsoft Fabric & AI Learning Hackathon" livestream schedule on the MS Reactor: https://aka.ms/fabrichack Watch today's livestream event on-demand on YouTube: https://lnkd.in/gbN9qFTr

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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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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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After speaking to 100+ data teams recently a clear pattern has emerged in the modern data stack:   Databricks is leading with its optimised Apache Spark runtime, accelerating data processing by up to 50%. Its collaborative workspace is becoming the go-to for data engineering and ML tasks. Snowflake's decoupled compute and storage architecture is reducing warehouse costs by 80%, making data migrations a 2 day job rather than a month-long ordeal.    Amazon Glue is filling a critical gap with its serverless ETL service. Its visual interface is democratising data preparation, though some find it limiting for complex, custom workflows. Microsoft's Azure Synapse is tying it all together, offering a unified platform for big data and warehousing with on-demand SQL pools.    The key insight? Each platform has its strengths and limitations, necessitating a combination of different technologies for optimal results.   This multi-platform approach may be transient – the real challenge lies in simplifying this complexity for the next wave of data innovation.   What's your experience with these platforms? Are you seeing similar trends in your data architecture? Let's talk. :)   #datalake #datawarehouse #databricks #amazon #microsoft #snowflake #etl #dataingestion #snowflake

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In an exclusive conversation with Debanagana Ghosh, moneycontrol.com, Oracle's #AI engineer Saurabh Netravalkar highlights the growing impact of #dataanalytics in sports, aiding teams in #performance optimization and #strategicplanning and how well he is balancing his love for #cricket and #technology Oracle. #AI #Dataanalytics #worklifebalance #CloudWorld https://lnkd.in/gpATnhJZ

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Newly published in Google Cloud's Architecture Framework 🏗️ this new AI/ML perspective provides a roadmap for designing, building, and managing workloads on Google Cloud. 🤖 It covers best practices for achieving operational excellence, security, reliability, cost optimization, and performance optimization. 🎯 Who should read this? 🤔 Decision-makers 👔 Architects 📐 Administrators 💻 Developers 🧑‍💻 Operators 🛠️ Key takeaways: Learn how to design and build AI/ML workloads that meet your business goals. 💼 Understand the principles of operational excellence, security, reliability, cost optimization, and performance optimization in the context of AI/ML. 💡 Get practical recommendations for implementing these principles on Google Cloud. ☁️ #AI #ML #GoogleCloud #CloudArchitecture #OperationalExcellence #Security #Reliability #CostOptimization #PerformanceOptimization

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NEW BLOG: ⚡ Confessions of a Spark Convert ⚡ The industry is moving on from compute-storage coupled architectures, are you? 🤔 https://lnkd.in/gWrr23Ci #spark #deltalake #fabric #databricks #lakehouse

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Join me for an insightful session on May 10th, 2024, where I'll be sharing how Games24x7 has leveraged Databricks to simplify the creation and deployment of ML models. I'll discuss our approach to automating MLOps pipelines and developing a solution supporting practitioners and managers throughout the ML lifecycle. From data preprocessing to model training, deployment, and monitoring, we'll explore how automation and AI can streamline these processes, freeing up time for experimentation and innovation. Looking forward to having you join us for this engaging discussion! #ML #AI #Databricks #Games24x7 Registration link: https://lnkd.in/gNTvMw_D

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Gemini in BigQuery changes the game for data engineers and analysts! More productivity ✔️ Improved query performance ✔️ Optimized costs throughout the analytics lifecycle—from ingestion and pipeline creation to deriving insights with AI ✔️ #GoogleCloudNext

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Latest blog on how to connect Oracle Autonomous Data Warehouse (ADW) to Apache Superset using the python-oracledb thick client on an Oracle Cloud Infrastructure (OCI) compute instance. Connection between Oracle ADW and Apache Superset can be quite the maze, given the scattered pieces of information out there. This step-by-step guide brings all the necessary details together in one place, making it much easier for you to set up and start exploring your data without much hassle. Thanks to @christopher jones (https://github.com/cjbj). His insights have been helpful for this. https://lnkd.in/g6h5Fi5u #Superset #PythonOracledb #OracleCloud

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This article is a must read for you if you are a Data analytics enthusiast, it's immaterial if you are using Databricks or Snowflake, focussing on governance, security or QI, if you are interested in open table formats, if you are looking for open source alternatives or if you are looking for on-premise options - Happy reading 😀 https://lnkd.in/g4zpJwQy

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Learn more about how Gemini in BigQuery helps bring the power of AI to your Data Warehouse! https://lnkd.in/d9digzES

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This guy is delivering at a pace unheard of. Cloud migration in a week is a new benchmark. And most importantly, he has set a precedent for all Indian companies to move to cloud by Indian cos. In just a few crores cost of migration https://lnkd.in/dJPZx4ZW *A quick snapshot of Cloud market* Cloud computing has $300bn annual revenues. Globally, the top 3 players capture 2/3 of the market. 2023 revenues below: Amazon AWS - $90bn Microsoft Azure (Intelligent Cloud) - $88bn Google GCP - $33bn The top revenue drivers for these companies are not AI/ML but Computing & Storage - which is purely infra and commoditized i.e your traditional hard disk. Let's appreciate a startup founder who has the guts to stand against these global giants. Krutrim Ola #Cloud #India #BhavishAggarwal

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