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 Intro
• 0:32 Joe is Back at Meta
• 3:28 What Does Meta Get Out Of Putting Out LLMs?
• 8:24 Measuring The Quality Of LLMs
• 10:55 How Do You Pick The Sizes Of Models
• 16:45 Advice On Choosing Which Model To Start With
• 24:57 The Secret Sauce In The Training
• 26:17 What Is Being Worked On Now
• 33:00 The Safety Mechanisms In Llama 2
• 37:00 The Datasets Llama 2 Is Trained On
• 38:00 On Multilingual Capabilities & Tone
• 43:30 On The Biggest Applications Of Llama 2
• 47:25 On Why The Best Teams Are Built By Users
• 54:01 The Culture Differences Of Meta vs Open Source
• 57:39 The AI Learning Alliance
• 1:01:34 Where To Learn About Machine Learning
• 1:05:10 Why AI For Science Is Under-rated
• 1:11:36 What Are The Biggest Issues With Real-World Applications

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#OCR #DeepLearning #AI #Modeling #ML