AWS Machine Learning Blog In the drive to remain competitive, businesses today are turning to AI to help them minimize cost and maximize efficiency. It’s incumbent on them to find the most suitable AI model—the one that will help them achieve more while spending less. For many businesses, the migration from OpenAI’s model family to […]Continue reading

Apple Machine Learning Research Large Language Models (LLMs) have transformed natural language processing, but face significant challenges in widespread deployment due to their high runtime cost. In this paper, we introduce SeedLM, a novel post-training compression method that uses seeds of a pseudo-random generator to encode and compress model weights. Specifically, for each block of […]Continue reading

Apple Machine Learning Research Large Language Models (LLMs) have transformed natural language processing, but face significant challenges in widespread deployment due to their high runtime cost. In this paper, we introduce SeedLM, a novel post-training compression method that uses seeds of a pseudo-random generator to encode and compress model weights. Specifically, for each block of […]Continue reading

AWS Machine Learning Blog Large language models (LLMs) can be used to perform natural language processing (NLP) tasks ranging from simple dialogues and information retrieval tasks, to more complex reasoning tasks such as summarization and decision-making. Prompt engineering and supervised fine-tuning, which use instructions and examples demonstrating the desired task, can make LLMs better at […]Continue reading

AWS Machine Learning Blog Large language models (LLMs) can be used to perform natural language processing (NLP) tasks ranging from simple dialogues and information retrieval tasks, to more complex reasoning tasks such as summarization and decision-making. Prompt engineering and supervised fine-tuning, which use instructions and examples demonstrating the desired task, can make LLMs better at […]Continue reading