Affan Dar

Thats the exact explanation I gave to a group of investors last week. (… it’s just Precision/Recall, attributes vectorization as “embedding”, K-Nearest Neighbor, User Search Intent, DAG, ML algorithms, etc all over again …). LOL and they asked what’s new this time around. And I was like not much, ML is still the backbone, and AI is the inference and actions based on the model. It works better when there is a feedback loop in a closed system. But the current state of the art like ChatGPT is based on scraping the Internet (garbage in, garbage out). Kinda like early search engines. What is a better analogy is that NVIDIA/Snowflake etc are selling tools, aka pickaxes to prospectors. The gold is up to you to find. And the opportunity right now is to monetize industry specific (healthcare, travel, financial services) clean data to build models with (aka a treasure map for the prospectors). From an enterprise perspective, what’s out there today aka generative AI isn’t very useful. Too much hype. To build useful engines will require an effort similar to search revolution 2 decades ago. From

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Pleased to share that Amazon Elastic Kubernetes Service (EKS) support in Amazon SageMaker HyperPod is available today for customers. SageMaker HyperPod has become a go-to solution for AI startups and enterprises to efficiently train and deploy large scale models. With today’s launch, organizations can reduce training time by up to 40% and strengthen resilience through deep health checks, automated node recovery, and job auto-resume capabilities. Here’s a great guide on how your team can get started with Amazon EKS support in Amazon SageMaker HyperPod.  https://lnkd.in/g8xj9RAi

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A super clear, straight forward example of how to do cost effective RAG using LangChain for your document pipeline and Groq for compute resources. The code demonstrates how to speed up RAG and reduce costs using quantized embeddings (reducing 32 bit values to 8) Nice job Sahibpreet Singh! https://lnkd.in/gf5QMCKK

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Oracle today announced the general availability of HeatWave #GenAI, including in-database LLMs, an automated in-database vector store, and the ability to have human-like contextual conversations in natural language. https://lnkd.in/gK-Q44gc

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New Episode: 260: Amazon Dispatches AWS CEO Adam Selipsky with Prime 2-day delivery Episode 260 of The Cloud Pod podcast, bringing you all the latest news from Cloud and AI including AWS, Azure, Google, OCI, GPT-4.o, C7i-flex, AWS CEO Changes and Amazon Polly #aws #gcp #azure #cloud #cloudpodcast #podcast

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A really nice read from Sai Maddali on the benefits of Tiered Storage with Amazon MSK. https://lnkd.in/gGNJ5nyt #ApacheKafka #Kafka #AWS #MSK #tieredstorage #streaming #storage

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One of the most powerful capabilities that Redshift is launching today, Amazon Redshift now supports incremental refresh for Materialized Views (MVs) on data lake tables. With IVM on Data Lake MVs users can now combine the strengths of data lake and high performance of warehouses.

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Hear from Sachin Gupta, VP and GM, Infrastructure and Solution Group, Google Cloud to learn customer-proven strategies for AI-powered innovation and modernization, leveraging the best of public cloud, edge, sovereign, and cross-cloud infrastructure and services. See how leaders are achieving real business outcomes faster and more cost-effectively in industries like retail, healthcare, and even the most stringent regulated industries. Plus, see how Gemini is dramatically simplifying and reimagining cloud as we know it.

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What it looks like to responsibly deliver educator value using Generative AI -- ensuring reliability and trust -- while moving rapidly and iteratively https://lnkd.in/egUdnV6w

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🚀 Exciting News Db2 Users! 🚀 ⌚ Amazon Web Services (AWS) has introduced on-demand Db2 licenses through AWS Marketplace! 🕺 This innovative solution enables Db2 users to procure database licenses for RDS Db2 workloads with ease. #AWS #AmazonRDS #DB2 #DatabaseManagement #Innovation #CloudComputing #TechNews #AWSUpdates

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When I speak to customers on AI, they often ask where do you even start? This was a great conversation of matching a project to the AI resources. We also dive a bit into what it takes to build an AI Cloud

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Learn the ins and outs of data latency with this expert guide from Oracle. https://lnkd.in/gnQJdJgS

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Large Language Models (#LLMs) are evolving rapidly, and the demand for running them at scale is skyrocketing. #Ollama is stepping up to meet this need with its official container image on Docker Hub, excelling in local #deployments. However, there’s a catch for containerized environments: downloading #models requires the ollama serve command to be running within the #container. This extra step complicates automated deployments via #CI #CD #pipelines, making seamless model access challenging. To take your #model to production, it needs to be #container-ready—a feature Ollama has yet to fully support. The gap in #AIOps for smooth deployments gets blurred with the inference services available as an easy way to take it to production. Goal is to overcome obstacles and deliver solutions 😉 so here is to get you started on having your (O)#llama #production ready in a private #deployment from your #local to #cloud all in #oneshot . Enjoy Medium: https://lnkd.in/g9jqBQ8d dev.to: https://lnkd.in/gi_gGwam #AI #LLM #Ollama #llama3 #phi3 #mistral #S6overlay #AIOps #CI #CD #oneshot #container #docker #podmanEnjoy

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When working with Amazon MSK, developers are interested in accessing the service locally. This allows developers to test their application with a Kafka cluster that has the same configuration as production and provides an identical infrastructure to the actual environment without needing to run Kafka locally. This post presents a practical approach to accessing your Amazon MSK environment for development purposes through a bastion host using a Secure Shell (SSH) tunnel (a commonly used secure connection method). Whether you’re working with Amazon MSK Serverless, where public access is unavailable, or with provisioned MSK clusters that are intentionally kept private, this post guides you through the steps to establish a secure connection and seamlessly integrate your local development environment with your MSK resources. https://lnkd.in/g4yiF3yH #MSK #serverless #ApacheKafka #testing

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Looking forward to this talk with Todd Brannon and Chris O'Brien. As the speed of generative AI adoption continues to grow, we'll look at what IT teams need to know in supporting these new workloads in their environment. Don't miss this one! #generativeAI #AImanagement #AIatscale

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Check out this great article by Kara Saucerman! It talks about CETO, a high-performance gateway serving as the front-end for Microsoft AI services. It leverages YARP (Yet Another Reverse Proxy) and the latest version of .NET.

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AlloyDB provides 2x better price-performance than self-managed PostgreSQL. See how in this article from Sridhar Ranganathan and Shesh Ranganath.

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