Secure RAG applications using prompt engineering on Amazon Bedrock

By Admin 27/08/2024

AWS Machine Learning Blog The proliferation of large language models (LLMs) in enterprise IT environments presents new challenges and opportunities in security, responsible artificial intelligence (AI), privacy, and prompt engineering. The risks associated with LLM use, such as biased outputs, privacy breaches, and security vulnerabilities, must be mitigated. To address these challenges, organizations must proactively […]Continue reading

Accelerate Mixtral 8x7B pre-training with expert parallelism on Amazon SageMaker

By Admin 23/05/2024

AWS Machine Learning Blog Mixture of Experts (MoE) architectures for large language models (LLMs) have recently gained popularity due to their ability to increase model capacity and computational efficiency compared to fully dense models. By utilizing sparse expert subnetworks that process different subsets of tokens, MoE models can effectively increase the number of parameters while […]Continue reading

Transform customer engagement with no-code LLM fine-tuning using Amazon SageMaker Canvas and SageMaker JumpStart

By Admin 10/05/2024

AWS Machine Learning Blog Fine-tuning large language models (LLMs) creates tailored customer experiences that align with a brand’s unique voice. Amazon SageMaker Canvas and Amazon SageMaker JumpStart democratize this process, offering no-code solutions and pre-trained models that enable businesses to fine-tune LLMs without deep technical expertise, helping organizations move faster with fewer technical resources. SageMaker […]Continue reading

Information extraction with LLMs using Amazon SageMaker JumpStart

By Admin 07/05/2024

AWS Machine Learning Blog Large language models (LLMs) have unlocked new possibilities for extracting information from unstructured text data. Although much of the current excitement is around LLMs for generative AI tasks, many of the key use cases that you might want to solve have not fundamentally changed. Tasks such as routing support tickets, recognizing […]Continue reading

Revolutionize Customer Satisfaction with tailored reward models for your business on Amazon SageMaker

By Admin 02/05/2024

AWS Machine Learning Blog As more powerful large language models (LLMs) are used to perform a variety of tasks with greater accuracy, the number of applications and services that are being built with generative artificial intelligence (AI) is also growing. With great power comes responsibility, and organizations want to make sure that these LLMs produce […]Continue reading

Natural language boosts LLM performance in coding, planning, and robotics

By Admin 01/05/2024

MIT News – Artificial intelligence Large language models (LLMs) are becoming increasingly useful for programming and robotics tasks, but for more complicated reasoning problems, the gap between these systems and humans looms large. Without the ability to learn new concepts like humans do, these systems fail to form good abstractions — essentially, high-level representations of […]Continue reading

Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker

By Admin 01/05/2024

AWS Machine Learning Blog Large language models (LLMs) are making a significant impact in the realm of artificial intelligence (AI). Their impressive generative abilities have led to widespread adoption across various sectors and use cases, including content generation, sentiment analysis, chatbot development, and virtual assistant technology. Llama2 by Meta is an example of an LLM […]Continue reading

Efficient continual pre-training LLMs for financial domains

By Admin 28/03/2024

AWS Machine Learning Blog Large language models (LLMs) are generally trained on large publicly available datasets that are domain agnostic. For example, Meta’s Llama models are trained on datasets such as CommonCrawl, C4, Wikipedia, and ArXiv. These datasets encompass a broad range of topics and domains. Although the resulting models yield amazingly good results for […]Continue reading

Techniques and approaches for monitoring large language models on AWS

By Admin 26/02/2024

AWS Machine Learning Blog Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis. However, as these models continue to grow in size and complexity, monitoring their performance and behavior has become increasingly challenging. Monitoring the performance and behavior of LLMs […]Continue reading

Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium

By Admin 12/12/2023

AWS Machine Learning Blog Large language models (or LLMs) have become a topic of daily conversations. Their quick adoption is evident by the amount of time required to reach a 100 million users, which has gone from “4.5yrs by facebook” to an all-time low of mere “2 months by ChatGPT.” A generative pre-trained transformer (GPT) […]Continue reading