Bridging AI and Science: The Impact of Machine Learning on Material Innovation with Joe Spisak of Meta

In the latest episode of Gradient Dissent, we hear from Joseph Spisak, Product Director, Generative AI @Meta, to explore the boundless impacts of AI and its expansive role in reshaping various sectors. We delve into the intricacies of models like GPT and Llama2, their influence on user experiences, and AI's groundbreaking contributions to fields like biology, material science, and green hydrogen production through the Open Catalyst Project. The episode also examines AI's practical business applications, from document summarization to intelligent note-taking, addressing the ethical complexities of AI deployment. We wrap up with a discussion on the significance of open-source AI development, community collaboration, and AI democratization. Tune in for valuable insights into the expansive world of AI, relevant to developers, business leaders, and tech enthusiasts.We discuss:0:00 Intro0:32 Joe is Back at Meta3:28 What Does Meta Get Out Of Putting Out LLMs?8:24 Measuring The Quality Of LLMs10:55 How Do You Pick The Sizes Of Models16:45 Advice On Choosing Which Model To Start With24:57 The Secret Sauce In The Training26:17 What Is Being Worked On Now33:00 The Safety Mechanisms In Llama 237:00 The Datasets Llama 2 Is Trained On38:00 On Multilingual Capabilities & Tone43:30 On The Biggest Applications Of Llama 247:25 On Why The Best Teams Are Built By Users54:01 The Culture Differences Of Meta vs Open Source57:39 The AI Learning Alliance1:01:34 Where To Learn About Machine Learning1:05:10 Why AI For Science Is Under-rated1:11:36 What Are The Biggest Issues With Real-World ApplicationsThanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation.#OCR #DeepLearning #AI #Modeling #ML