At Meta, AI is pervasive and critical to the proliferation of our products for billions of users worldwide. Meta AI’s Manohar Paluri shares a simple but effective framework for pushing the frontiers in AI research, while advancing technology that is impactful to the product end game.
Watch this session to gain insights on:
- The structure for developing AI applications including scaling ML models
- Adopting a multi-modal understanding
- Pairing tools and human intelligence to accelerate AI
- Power of human intelligence to improve AI
Here are 3 key takeaways from the session:
- Annotation is not a single-step process. It is an iterative step. While it may seem simple, the fact is that throughout the iterative process additional problem formulation is unearthed. Thinking about data and annotations should be as much as the models.
- Today, a large number of AI models are being deployed and have a significant impact on society. One needs to start thinking about how to deploy the models responsibly and ensure it takes the right decisions and has a positive impact on society.
- It’s really important to build a well-rounded cross-functional team that understands not just the technical aspects but also the outcomes it is achieving and how it’s integrated into people’s lives.
