In this podcast episode, Stefania Druga, a research scientist on the Bard (now Gemini) team at Google, shares insights into her work on developing multi-modal AI applications. She explains how Bard, a large language model, is trained on a massive amount of internet data, enabling it to understand and generate text, summarize content, and interact with images.
Druga discusses the potential of Bard to revolutionize various sectors by providing personalized assistance, from generating recipes based on fridge contents to creating visualizations for data.
Her work highlights the advancements in AI technology, emphasizing the importance of multimodal capabilities that extend beyond text to include images and potentially other data forms, pushing the boundaries of AI's application in everyday life.
Stefania Druga Quotes
📊 Data Set Sizes: "You can think of what does it mean to scrape the entire internet and that's pretty much it, right? So all the data that was ever created digitally and has the right permissions."
⚙️ “These AI assistants are becoming now embedded in not only standalone application like Bard and ChatGPT, but also in a variety of products. So they can become embedded in your calendar to help with smart planning”
📚 “Having AI literacy, learning how to ask questions from this chatbots, robots, AI models, and also learning how to make a critical use of them”
🚀 “And I realized in 2016 that AI, voice assistants, machine learning are going to be huge. So I started thinking of how do we teach the next generation? And that's how I started working on Cognimates and launched a platform.”
Resources Mentioned:
Fast.ai: Making neural nets uncool again: https://fast.ai
LangChain: Build context-aware, reasoning applications with LangChain’s flexible abstractions and AI-first toolkit: https://www.langchain.com
Check out Stefania’s publications: https://stefania11.github.io
Cognimates, Stefania’s coding education project started at MIT Media Lab: https://cognimates.me/home/
Stefania Druga Bio:
Stefania Druga is a Research Scientist at Google Bard AI. She was a principal researcher at the Center of Applied AI Research at the University of Chicago. She graduated with a PhD in Creative AI Literacies at the University of Washington and a master of science at MIT. During her PhD, she did several research internships at Google X, Microsoft Research, and Fixie.ai focusing on Large Language Models applications for developer tools, programming languages, and data science applications. She loves trail running and drawing with robots.
Connect with Stefania on LinkedIn: / drugastefania
Stefania Drug on Twitter: / stefania_druga
Google Bard/Gemini: https://gemini.google.com/
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