Month: June 2024

The history of Rust at Meta goes all the way back to 2016, when we first started using it for source control. Today, it has been widely embraced at Meta and is one of our primary supported server-side languages (along with C++, Python, and Hack). But that doesn’t mean there weren’t any growing pains. Aida… Continue reading The key to a happy Rust/C++ relationship

In our “Engineering Energizers” Q&A series, we explore the innovative minds shaping the future of Salesforce engineering. Today, we meet Erwin Karbasi, who leads the development of the Salesforce Central Evaluation Framework (SF Eval), a revolutionary internal tool used by Salesforce engineers to assess the performance of generative AI models. Explore how SF Eval addresses… Continue reading The Future of AI Testing: Salesforce’s Next Gen Framework for AI Model Performance

We’re sharing how we streamline system reliability investigations using a new AI-assisted root cause analysis system. The system uses a combination of heuristic-based retrieval and large language model-based ranking to speed up root cause identification during investigations. Our testing has shown this new system achieves 42% accuracy in identifying root causes for investigations at their… Continue reading Leveraging AI for efficient incident response

In our “Engineering Energizers” Q&A series, we explore the paths of engineering leaders who have attained significant accomplishments in their respective fields. Today, we spotlight Armita Peymandoust, Senior Vice President of Software Engineering at Salesforce, who spearheads the development of Einstein Copilot, a conversational AI assistant for CRM that integrates data, metadata, prompts, and workflows… Continue reading How Einstein Copilot Sharpens Large Language Model Outputs and Redefines AI Data Testing

We’re introducing parameter vulnerability factor (PVF), a novel metric for understanding and measuring AI systems’ vulnerability against silent data corruptions (SDCs) in model parameters. PVF can be tailored to different AI models and tasks, adapted to different hardware faults, and even extended to the training phase of AI models. We’re sharing results of our own… Continue reading PVF: A novel metric for understanding AI systems’ vulnerability against SDCs in model parameters

In this special edition of “Engineering Energizers,” we’re celebrating Salesforce’s 25th anniversary by showcasing 25 key productivity tools favored by leading engineers at Salesforce across India, the U.S., Israel, and Argentina. Explore the essential tools these experts rely on to enhance their productivity, tackle complex problems, and elevate innovation. 1. SLACK — A productivity platform… Continue reading 25 Productivity Tools that Power Salesforce Engineering Teams

At Meta, we support real-time communication (RTC) for billions of people through our apps, including WhatsApp, Instagram, and Messenger.  We are working to make RTC accessible by providing a high-quality experience for everyone – even those who might not have the fastest connections or the latest phones. As more and more people have relied on… Continue reading MLow: Meta’s low bitrate audio codec

As we continue to focus our AI research and development on solving increasingly complex problems, one of the most significant and challenging shifts we’ve experienced is the sheer scale of computation required to train large language models (LLMs). Traditionally, our AI model training has involved a training massive number of models that required a comparatively… Continue reading How Meta trains large language models at scale