The Berkeley Artificial Intelligence Research Blog We introduce Anthology, a method for conditioning LLMs to representative, consistent, and diverse virtual personas by generating and utilizing naturalistic backstories with rich details of individual values and experience. What does it mean for large language models (LLMs) to be trained on massive text corpora, collectively produced by millions […]Continue reading

The Berkeley Artificial Intelligence Research Blog Sample language model responses to different varieties of English and native speaker reactions. ChatGPT does amazingly well at communicating with people in English. But whose English? Only 15% of ChatGPT users are from the US, where Standard American English is the default. But the model is also commonly used […]Continue reading

The Berkeley Artificial Intelligence Research Blog When we began studying jailbreak evaluations, we found a fascinating paper claiming that you could jailbreak frontier LLMs simply by translating forbidden prompts into obscure languages. Excited by this result, we attempted to reproduce it and found something unexpected. The paper in question claimed an impressive 43% success rate […]Continue reading

The Berkeley Artificial Intelligence Research Blog Humans excel at processing vast arrays of visual information, a skill that is crucial for achieving artificial general intelligence (AGI). Over the decades, AI researchers have developed Visual Question Answering (VQA) systems to interpret scenes within single images and answer related questions. While recent advancements in foundation models have […]Continue reading

AWS Machine Learning Blog This post is co-written with Xavier Vizcaino, Diego Martín Montoro, and Jordi Sánchez Ferrer from Applus+ Idiada. In 2021, Applus+ IDIADA, a global partner to the automotive industry with over 30 years of experience supporting customers in product development activities through design, engineering, testing, and homologation services, established the Digital Solutions […]Continue reading

AWS Machine Learning Blog Troubleshooting infrastructure as code (IaC) errors often consumes valuable time and resources. Developers can spend multiple cycles searching for solutions across forums, troubleshooting repetitive issues, or trying to identify the root cause. These delays can lead to missed security errors or compliance violations, especially in complex, multi-account environments. This post demonstrates […]Continue reading

AWS Machine Learning Blog This blog post is co-written with Gene Arnold from Alation. To build a generative AI-based conversational application integrated with relevant data sources, an enterprise needs to invest time, money, and people. First, you would need build connectors to the data sources. Next you need to index this data to make it […]Continue reading

AWS Machine Learning Blog Today, we’re excited to announce that Mistral-Small-24B-Instruct-2501—a twenty-four billion parameter large language model (LLM) from Mistral AI that’s optimized for low latency text generation tasks—is available for customers through Amazon SageMaker JumpStart and Amazon Bedrock Marketplace. Amazon Bedrock Marketplace is a new capability in Amazon Bedrock that developers can use to discover, test, […]Continue reading

AWS Machine Learning Blog This post was written with Dian Xu and Joel Hawkins of Rocket Companies. Rocket Companies is a Detroit-based FinTech company with a mission to “Help Everyone Home”. With the current housing shortage and affordability concerns, Rocket simplifies the homeownership process through an intuitive and AI-driven experience. This comprehensive framework streamlines every […]Continue reading