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SC

Scott Clark

05/23/25

@ a16z

The complexity of AI systems is increasing, making it essential to understand how behaviors propagate through interconnected models.

Video

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Building AI Systems You Can Trust

@ a16z

05/23/25

Related Takeaways

SC

Scott Clark

05/23/25

@ a16z

As AI systems become more complex, understanding their behavior requires a holistic view that considers all interactions and outputs.

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Anthropic Cast

03/27/25

@ Anthropic

Understanding how AI models think can lead to safer and more reliable systems, similar to how neuroscience improves health outcomes.

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a16z Cast

05/23/25

@ a16z

Understanding the distribution of AI model behavior over time is essential for diagnosing performance issues and ensuring consistent outputs.

LF

Lex Fridman Cast

02/03/25

@ Lex Fridman

The preparation and understanding of what AI can do is becoming increasingly important as open models continue to emerge, regardless of attempts to stop them.

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Anthropic Cast

03/27/25

@ Anthropic

New methods have been developed to observe an AI model's internal thought processes and how concepts are interconnected to form logical circuits.

YC

Y Combinator Cast

10/18/24

@ Y Combinator

Building a system that effectively utilizes AI agents requires careful orchestration and cannot be achieved merely by increasing model size.

SA

Sam Altman

04/12/25

@ TED

The iterative process of deploying AI systems, gathering feedback, and learning is crucial for building safe systems as we advance into more complex AI.

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a16z Cast

04/03/25

@ a16z

It's crucial to understand the complexities of working with AI systems, including the need to manage issues like hallucinations and model evaluations effectively.

SC

Sequoia Capital Cast

02/25/25

@ Sequoia Capital

Reinforcement learning on top of models will be critical for building the most powerful AI agents, as it allows for better adaptability and performance in complex tasks.