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Meta's OpenCatalyst | RT-2 Speaking Robot | Adversarial Prompts
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Meta's OpenCatalyst | RT-2 Speaking Robot | Adversarial Prompts

AI Daily | 7.28.23

In this episode of AI Daily with your hosts Conner, Ethan, and Farb. They kick off the episode discussing Meta's OpenCatalyst, a groundbreaking model developed with Carnegie Mellon University that simulates over a hundred million catalyst combinations, accelerating advancements in material science and renewable energy. They then move to explore Google DeepMind's RT-2 Speaking Robot, a unique vision, language, and action model that learns from web images and texts to perform real-world actions, promising a new era of autonomous robotics. Finally, they delve into the intriguing concept of Adversarial Prompts, discussing a recent study by a team at Carnegie Mellon that used LLaMA to generate prompts adversarial to popular models like GPT-4, raising important questions about the robustness and safety of these models.

Quick Points:

1️⃣ Meta’s OpenCatalyst

  • Meta and Carnegie Mellon University develop OpenCatalyst, simulating 100+ million catalyst combinations.

  • This tool enables rapid simulations, enhancing chemical process research.

  • It is highly applicable to renewable energy and material sciences.

2️⃣ RT-2 Speaking Robot

  • Google DeepMind unveils the RT-2 Speaking Robot, a vision-language-action model.

  • Trained on web images and texts, it can perform untrained real-world actions.

  • This model represents a significant leap in the realm of autonomous robotics.

3️⃣ Adversarial Prompts

  • A Carnegie Mellon team uses LLaMA to generate adversarial prompts against leading models.

  • This discovery exposes potential weaknesses in popular AI models like GPT-4.

  • Raises important questions about AI model robustness and safety.

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AI Daily
AI Daily
The go-to podcast to stay ahead of the curve when it comes to the rapidly changing world of AI. Join us for insights and interviews on the most useful AI tools and how to leverage them to drive your goals forward.