🚀 𝐄𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 𝐭𝐡𝐞 𝐓𝐫𝐮𝐞 𝐂𝐨𝐬𝐭𝐬 𝐨𝐟 𝐇𝐨𝐬𝐭𝐢𝐧𝐠 𝐋𝐋𝐌𝐬 🚀 As AI continues to shape industries, the decision to host Large Language Models (LLMs) vs. using API-based solutions becomes crucial. In our latest article, we’ve conducted a comprehensive comparison of major platforms such as AWS EC2, SageMaker, Bedrock, Hugging Face, and more. 📊 We break down: - Monthly hosting costs for different LLM sizes - The advantages of on-demand vs. reserved instances - Token-based pricing models - Insights on hosting vs. API consumption 𝘙𝘦𝘢𝘥 𝘵𝘩𝘦 𝘧𝘶𝘭𝘭 𝘢𝘳𝘵𝘪𝘤𝘭𝘦 𝘩𝘦𝘳𝘦 𝘢𝘯𝘥 𝘭𝘦𝘢𝘳𝘯 𝘩𝘰𝘸 𝘵𝘰 𝘰𝘱𝘵𝘪𝘮𝘪𝘻𝘦 𝘺𝘰𝘶𝘳 𝘓𝘓𝘔 𝘩𝘰𝘴𝘵𝘪𝘯𝘨 𝘤𝘰𝘴𝘵𝘴. #AI #CloudComputing #LLMHosting #MachineLearning #DataScience #AWS #CostOptimization
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Many customers need to change backgrounds in large image batches. Amazon Bedrock and AWS Step Functions offer an automated background removal workflow. #aws #awscloud #cloud #amazonbedrock #amazontitan #artificialintelligence #awsstepfunctions #generativeai #intermediate200 #technicalhowto
Automate the process to change image backgrounds using Amazon Bedrock and AWS Step Functions
aws.amazon.com
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Technologist | Speaker | O'Reilly Author | AWS Serverless Hero | Team Topologies Advocate
✨Assess the need. Break down into pieces. Decouple. Deploy each piece.✨ 🗒As I read about how Capital One migrated its ML model to serverless, their approach quickly resonated with the best practices many promote in the serverless community. It's a beautifully written article about- 🔸the problem 🔸the options 🔸the solution 🔸lessons learned 🔸best practices ❤️It's not often that I smile while reading an article, but somehow, I simply loved this one! ❓It also answers a common question: Do Machine Learning (ML) models qualify as a viable use case for serverless? https://lnkd.in/ecHdM9gD #AWS #Serverless #TheServerlessBook #machinelearning #ML #models #AI #cloud #cloudcomputing #architecture #software #finance
Serverless ML: Lessons from Capital One
medium.com
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Amazon announces general availability of Bedrock Custom Model Import. This allows customers to import and use customized models with foundation models through a unified API. #aws #awscloud #cloud #amazonbedrock #announcements #artificialintelligence #generativeai
Amazon Bedrock Custom Model Import now generally available
aws.amazon.com
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From Amazon Q Business and AI Agents to new cloud storage and Amazon Bedrock tools, Mark Haranas breaks down the 10 coolest new Amazon Web Services (AWS) products launched in 2024 so far. AWS Partners #AWS #GenAI
AWS' 10 Hottest New Products And Tools Of 2024 (So Far)
crn.com
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This post shows how to accelerate pre-training of large language models by scaling up to 128 trn1.32xlarge nodes, using a 2-7B Llama model as an example. It shares best practices for efficient, stable training of LLMs on AWS Trainium with 100+ nodes, and recovering from failures. #aws #awscloud #cloud #amazonec2 #awsneuron #awstrainium #bestpractices #technicalhowto #distributedtraining #neuron
End-to-end LLM training on instance clusters with over 100 nodes using AWS Trainium
aws.amazon.com
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🚨 NEW BLOG ALERT 🚨 Learn how to perform continued pre-training of #Llama models using Pipeline Parallelism and Tensor Parallelism on #SageMaker with AWS #Trainium instances. With up to 50% cost-to-train savings over comparable training optimized EC2 instances, this blog is a must-read for anyone interested in #MachineLearning and #DeepLearning. Check out the link below to learn more! Link: https://lnkd.in/gi4pDUQz #AWS #SageMaker #NeuronDistributedLibrary #PipelineParallelism #TensorParallelism
Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker | Amazon Web Services
aws.amazon.com
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Creating efficient AWS Config rules has never been easier. Dive into the latest advancements in cloud automation and streamline your compliance efforts effortlessly. Stay ahead of the curve and embrace the power of AI-driven innovation! https://lnkd.in/dKSeMYs5 #AWS #CloudComputing #AI #Automation #AWSConfig
Create AWS Config rules efficiently with Generative AI | Amazon Web Services
aws.amazon.com
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Happy to share my latest Medium blog post, "𝐌𝐚𝐬𝐭𝐞𝐫𝐢𝐧𝐠 𝐀𝐖𝐒 𝐈𝐧𝐟𝐞𝐫𝐞𝐧𝐭𝐢𝐚: 𝐀 𝐆𝐮𝐢𝐝𝐞 𝐭𝐨 𝐂𝐨𝐦𝐩𝐢𝐥𝐢𝐧𝐠 𝐚𝐧𝐝 𝐃𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐚 𝐂𝐮𝐬𝐭𝐨𝐦𝐢𝐳𝐞𝐝 𝐋𝐥𝐚𝐦𝐚2–7𝐛 𝐌𝐨𝐝𝐞𝐥". 🔎 Explore how to use AWS Inferentia instances to compile and deploy your own custom models! 🔗 https://lnkd.in/e5PCJMYG ☁️ Thanks to our partner Amazon Web Services (AWS) and Patricia Narváez Cienfuegos for making the work on innovative technologies possible! I'd love to hear your thoughts and feedback in the comments. #AWS #Inferentia #CustomModels #LLM #llama2 #FinOps
Mastering AWS Inferentia: A Guide to Compiling and Deploying a Customized Llama2–7b Model
medium.com
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Exciting updates from AWS this week! Dive into the latest on AI21 Labs, Jamba Instruct in Amazon Bedrock, Amazon WorkSpaces Pools, and more in the weekly roundup. Stay ahead in the tech game with AWS! #Mantalus #AWS #AmazonWebServices #Blogs Explore further here: https://lnkd.in/eHhaChUT
AWS Weekly Roundup: AI21 Labs’ Jamba-Instruct in Amazon Bedrock, Amazon WorkSpaces Pools, and more (July 1, 2024) | Amazon Web Services
aws.amazon.com
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Accelerate Your Journey to Production with RAG: Deploying Augmented Generation Applications on GKE, Cloud SQL, and pgvector
RAG quickstart with Ray, LangChain, and HuggingFace | Google Cloud Blog
cloud.google.com
Co-Founder of Altrosyn and DIrector at CDTECH | Inventor | Manufacturer
2moThe shift towards serverless architectures for LLM hosting will likely accelerate, driven by advancements in technologies like Function-as-a-Service . Imagine a future where LLMs are seamlessly integrated into real-time applications, dynamically scaling based on demand. How might this paradigm shift impact the design and deployment of ethical safeguards within these dynamic systems?