AWS Machine Learning Blog This blog post is co-written with Pradeep Prabhakaran from Cohere. Today, we are excited to announce that Cohere Command R and R+ foundation models are available through Amazon SageMaker JumpStart to deploy and run inference. Command R/R+ are the state-of-the-art retrieval augmented generation (RAG)-optimized models designed to tackle enterprise-grade workloads. In this post, […]Continue reading
AWS Machine Learning Blog This is a guest post by Mark McQuade, Malikeh Ehghaghi, and Shamane Siri from Arcee. In recent years, large language models (LLMs) have gained attention for their effectiveness, leading various industries to adapt general LLMs to their data for improved results, making efficient training and hardware availability crucial. At Arcee, we […]Continue reading
AWS Machine Learning Blog This is a guest post co-written with the leadership team of Iambic Therapeutics. Iambic Therapeutics is a drug discovery startup with a mission to create innovative AI-driven technologies to bring better medicines to cancer patients, faster. Our advanced generative and predictive artificial intelligence (AI) tools enable us to search the vast […]Continue reading
AWS Machine Learning Blog This post is co-authored by Jackie Rocca, VP of Product, AI at Slack Slack is where work happens. It’s the AI-powered platform for work that connects people, conversations, apps, and systems together in one place. With the newly launched Slack AI—a trusted, native, generative artificial intelligence (AI) experience available directly in […]Continue reading
AWS Machine Learning Blog This blog post is co-written with Caroline Chung from Veoneer. Veoneer is a global automotive electronics company and a world leader in automotive electronic safety systems. They offer best-in-class restraint control systems and have delivered over 1 billion electronic control units and crash sensors to car manufacturers globally. The company continues […]Continue reading
AWS Machine Learning Blog This is a guest post co-authored by Shravan Kumar and Avirat S from Gramener. Gramener, a Straive company, contributes to sustainable development by focusing on agriculture, forestry, water management, and renewable energy. By providing authorities with the tools and insights they need to make informed decisions about environmental and social impact, […]Continue reading
AWS Machine Learning Blog This is a guest post co-written with Tamir Rubinsky and Aviad Aranias from Nielsen Sports. Nielsen Sports shapes the world’s media and content as a global leader in audience insights, data, and analytics. Through our understanding of people and their behaviors across all channels and platforms, we empower our clients with […]Continue reading
AWS Machine Learning Blog This is a guest post co-written with Michael Feil at Gradient. Evaluating the performance of large language models (LLMs) is an important step of the pre-training and fine-tuning process before deployment. The faster and more frequent you’re able to validate performance, the higher the chances you’ll be able to improve the […]Continue reading
AWS Machine Learning Blog This blog post is co-written with Hwalsuk Lee at Upstage. Today, we’re excited to announce that the Solar foundation model developed by Upstage is now available for customers using Amazon SageMaker JumpStart. Solar is a large language model (LLM) 100% pre-trained with Amazon SageMaker that outperforms and uses its compact size […]Continue reading
AWS Machine Learning Blog This is a guest post co-written with Meta’s PyTorch team and is a continuation of Part 1 of this series, where we demonstrate the performance and ease of running PyTorch 2.0 on AWS. Machine learning (ML) research has proven that large language models (LLMs) trained with significantly large datasets result in […]Continue reading
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