Pavan Kumar Rao Navule’s Post

Amazon Bedrock now supports compressed embeddings from Cohere Embed! 💡 Cohere Embed, a top text embedding model, is widely known for enhancing RAG & semantic search systems. The int8 and binary compressed embeddings now available empower developers and businesses to create more efficient #generativeAI applications without sacrificing performance. Explore more at: https://go.aws/4eBniXm #AWS ☁️

Go batch or go home. ☁️⚡️💻 https://go.aws/3ZcMgaD #AmazonBedrock Batch Inference is now generally available in all #AWS regions. Use batch inference to run multiple inference requests asynchronously & improve the performance of model inference on large datasets. Amazon Bedrock offers select foundation models for batch inference at 50% of on-demand inference pricing.

Amazon Web Services (AWS) now offers sticky session routing on #Amazon #SageMaker Inference, enhancing performance and user experience for #GenerativeAI applications. Key benefits: • Improved latency by reusing processed information • Better handling of large data payloads • Seamless interactive experiences • Enables state-aware AI applications Available in all regions where SageMaker is present, this update empowers developers to create more responsive and efficient AI-powered applications. https://lnkd.in/dQnG-v7Y #AWS #AmazonSageMaker #MachineLearning #CloudComputing #AIInference #ArtificialIntelligence

Llama 3.3 70B represents a significant breakthrough in model efficiency and performance optimization. This new model delivers output quality comparable to Llama 3.1 405B while requiring only a fraction of the computational resources. According to Meta, this efficiency gain translates to nearly five times more cost-effective inference operations. https://lnkd.in/d678VBAV #llama3.3 #aws #sagemaker #llm

SageMaker now offers faster autoscaling via a new set of metrics based on concurrent number of requests sent to a SageMaker Endpoint! See the blogpost for a code example that you can following along with, as well as benchmarking done that showed 6x improvement in latency associated with identifying a need to engage auto-scaling! #aws #sagemaker #mlops

The best part about the new Llama 3.1 family of models is that you can fine tune them on AWS Trainium chips. These are more energy and cost efficient chips and with great performance purpose built for the training and fine tuning tasks. #aws #Llama3.1 #sagemakerjumpstart https://lnkd.in/d6S5Gdae

I’m excited to share one of the Amazon Web Services (AWS) courses I have enjoyed the most: Foundations of Prompt Engineering, and the best part? It’s free. https://lnkd.in/e8QgdFz7 If you’re familiar with Generative AI and looking to enhance the quality of your results, this is the perfect course for you. #AWS #PromptEngineering #GenerativeAI #LifelongLearning #FreeCourse

#StickySession #routing on Amazon Web Services (AWS) #SageMaker Inference helps you improve the #performance and #userExperience of #generative #AI applications by leveraging previously processed #information #AWS #StickySession #Datascience #MachineLearning #GenAI ANZ Tech Talks Learn more about it over here - https://lnkd.in/g7R87jhy

Boost your machine learning model's performance and efficiency with Amazon SageMaker! 🚀 Learn how hyperparameter tuning, pruning, quantization, and other optimization techniques can improve efficiency, reduce costs, and boost performance. Explore SageMaker's powerful tools to scale your ML projects seamlessly. https://lnkd.in/gJwGv4K7 #MachineLearning #AWS #SageMaker #ModelOptimization #DataScience