In this blog, we’ll dive into the challenges of AI personalization, why current systems fall short, and how PersonaBench helps bridge the gap—paving the way for smarter, more reliable AI assistants.
AI-powered solutions like Salesforce CRM are revolutionizing customer engagement, streamlining workflows, and providing deeper insights into customer needs. However, with the rise of large language models (LLMs), new security challenges have emerged. One…
Today's investments in digital automation are laying the groundwork for a future where agents and robots converge in ways that reshape how work gets done.
Developers face unique challenges when retrieving code snippets, such as understanding syntax, control flow, and variable dependencies. Enter SFR-Embedding-Code, a groundbreaking family of code embedding models that aims to address these challenges and revolutionize how we retrieve and generate code.
We present TACO, a family of multi-modal large action models designed to improve performance on complex questions that require multiple capabilities and demand multi-step solutions.
To address the challenges in generating multimodal instruction data, we developed ProVision, a scalable, programmatic framework that employs scene graphs and human-written programs to systematically synthesize vision-centric instruction data.
From new open source models to evaluation frameworks, our AI Research team has been moving the needle in AI. Take a look at some of our 2024 highlights.
Salesforce's trusted AI architecture for red teaming leverages automation to scale ethical AI testing, utilizing a tool called fuzzai to simulate diverse adversarial scenarios and enhance model robustness. By automating adversarial prompt generation and response validation, fuzzai helps secure AI interactions while reducing human exposure to harmful content.