
Silvio Savarese
author title Executive Vice President and Chief Scientist, Salesforce AI ResearchSilvio Savarese is the Executive Vice President and Chief Scientist of Salesforce AI Research, as well as an Adjunct Faculty of Computer Science at Stanford University, where he served as an Associate Professor with tenure until winter 2021. At Salesforce, he shapes the scientific direction and long-term AI strategy by aligning research and innovation efforts with Salesforce’s mission and objectives. He leads the AI Research organization, including AI for C360 and CRM, AI for Trust, AI for developer productivity, and operational efficiency.

The year was 2013. In a state-of-the-art kitchen laboratory in Stanford University’s Robotics Center, surrounded by the whir of servo motors and the aroma of brewing coffee, I observed our latest prototype attempt…
The recent launch of Agentforce marks a pivotal moment in orienting Salesforce and our customers’ businesses toward an AI-empowered future. In this emerging landscape, augmented by a network of AI agents, the role…
AI agents and assistants have the ability to take action on a user’s behalf, but each serves a distinct purpose.
Simply put, AI Assistants are built to be personalized, while AI Agents are built to be shared (and scaled)—and both techniques promise extraordinary opportunities across the enterprise.

TL;DR: We introduce INDICT, a novel framework that empowers Large Language Models (LLMs) with Internal Dialogues of Critiques for both safety and helpfulness guidance. The internal dialogue is a dual cooperative system between…
LLM benchmarks evaluate how accurately a generative AI model performs, but most benchmarks overlook the kinds of real-world tasks an LLM would perform in an enterprise setting.
For many of our customers, excessive scale sometimes does more harm than good.
In the kind of production environment our customers operate in, models are just the start.