The circuits work in AI is impressive, showing that models can reason and understand complex relationships in data.

AI models are not programmed; they are trained, allowing them to develop their own strategies for problem-solving.

AI models are not just about knowledge and synthesis; they can perform tasks like scrolling and clicking in browsers.

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

Current AI, including models like GPT-4, does not exhibit true intelligence; it makes mistakes that humans wouldn't, such as confidently stating incorrect numerical comparisons.

There's a specialization in AI models, where reasoning models that require more compute time are becoming popular for tasks like math and coding, while for consumer products, latency and intelligence per cost are prioritized.

AI models are valuable because they can interpolate between vague questions and provide tailored responses, even when data is messy.

AI models are valuable because they can interpolate between vague questions and provide tailored responses, even when data is messy.

AI systems can be tricked, similar to humans, and as we advance in unsupervised learning, we may develop systems that achieve a level of conceptual understanding.