To celebrate International Women's Day, GDG SF collaborates with GDG Silicon Valley as well as Google Women Techmakers and IEEE Women in Engineering on an event located at Hacker Dojo (855 Maude Ave, Mountain View, CA 94043) on 3/11 from 6-8 PM PST.
*The topic covered will surround AI, Security in AI, along with UX insights within the space.*
These interactive sessions will let you dive deep into various AI topics across your stack. The door will open at 6 PM PST. Meet your Co-hosts: Amber Wang, lead women in AI of Cerebralvally.ai, building the AI community, and Karen Horovitz, Silicon Alliances Partner Manager, Chair of IEEE. This event is open to the public and all genders who support women and women in technology/engineering.
About the Speakers:
Mrinal Karvir is Intel's Cloud Software Engineering Manager and Vice Chair of IEEE SCV WIE. With the recent strides in Generative AI to create new content, ChatGPT has taken the world by storm. Yet there are daily reports of AI harm. Thus, it is more important than ever before to start discussions on Responsible AI. In this talk, Mrinal will discuss the principles of Responsible AI and why they matter with case studies.
Gloria Felicia, COO + cofounder of speedify.ai, will discuss the UX side of AI, how people interact with AI, and how to get started with AI frameworks. For the longest time, people have interacted with AI in many formats: voice, chatbot, image, text, and video... do we know which one is most effective? Do we have stats around these different types of interaction? As an expert in UX Research in charge of the operations of an AI Startup that focuses on re-defining the future of work by augmenting workflow with AI, Glo will discuss this topic in depth.
Nasibeh Nasiri, Software Performance Engineer at Meta, will talk about the AI hardware and software landscape along with other cool concepts surrounding the incorporation of AI in the hardware world. Nasibeh will guide us through NLP Best Practices in this talk and technical hands-on workshop. Natural Language Processing (NLP) is vital to the progress of Large Language Models (LLM).