AI research is advancing at an unparalleled pace, from innovations in NLP to computer vision and everything in between. However, these technologies can often feel out of reach for most customers who are looking to derive business value from AI. This talk will cover best practices and frameworks to close the gap between AI research and customer success based on learnings from Salesforce Einstein. We will discuss the challenges of adopting AI at scale and provide recommendations for different stages of the product life cycle.
Zineb Laraki (Z), Deep Learning Senior Product Management at Salesforce, and her team make deep learning capabilities accessible to customers as well as Salesforce internal teams. The focus is to lower the barrier to leverage models for unstructured data (text, image, voice) to solve customer pain points; to streamline and automate mundane and repetitive Sales, Service or Marketing workflows so people can focus on higher-value more full-filling work. Zineb's team consists of the Salesforce Research team that is working on advancing the field of AI and Applied Research/Engineering that helps close the gap between the latest breakthroughs and bringing products to market for customers that solve complex problems but abstract the complexity.
Zineb holds a BS and MS from Stanford University in Symbolic Systems which focuses on computers and minds (artificial and natural systems that use symbols to communicate and to represent information), human-computer interaction, cognitive science (studying human intelligence, natural language and the brain as computational processes), artificial intelligence as well as a concentration in Design Thinking. Zineb is driven by a desire to help change the world for the better.