SageMaker

In: Artificial Intelligence

This post is co-written with Meta’s PyTorch team. In today’s rapidly evolving AI landscape, businesses are constantly seeking ways to use advanced large language models (LLMs) for their specific needs. Although foundation models (FMs) offer impressive out-of-the-box capabilities, true competitive advantage often lies in deep model customization through fine-tuning. However,Continue Reading

In: Artificial Intelligence

The clustered regularly interspaced short palindromic repeat (CRISPR) technology holds the promise to revolutionize gene editing technologies, which is transformative to the way we understand and treat diseases. This technique is based in a natural mechanism found in bacteria that allows a protein coupled to a single guide RNA (gRNA)Continue Reading

In: Artificial Intelligence

Thomson Reuters, a global content and technology-driven company, has been using artificial intelligence and machine learning (AI/ML) in its professional information products for decades. The introduction of generative AI provides another opportunity for Thomson Reuters to work with customers and advance how they do their work, helping professionals draw insightsContinue Reading

In: Artificial Intelligence

This post is co-written with Francisco Azuaje from Genomics England. Genomics England analyzes sequenced genomes for The National Health Service (NHS) in the United Kingdom, and then equips researchers to use data to advance biological research. As part of its goal to help people live longer, healthier lives, Genomics EnglandContinue Reading

In: Artificial Intelligence

Large language models (LLMs) have remarkable capabilities. Nevertheless, using them in customer-facing applications often requires tailoring their responses to align with your organization’s values and brand identity. In this post, we demonstrate how to use direct preference optimization (DPO), a technique that allows you to fine-tune an LLM with humanContinue Reading

In: Artificial Intelligence

Generative artificial intelligence (AI) models have become increasingly popular and powerful, enabling a wide range of applications such as text generation, summarization, question answering, and code generation. However, despite their impressive capabilities, these models often struggle with domain-specific tasks or use cases due to their general training data. To addressContinue Reading