Today, OpenAI introduced a Function Call API so we're going to dive into a much more structured and efficient way of handling output parsing when interacting with OpenAI. This method leverages the robustness of the Pydantic library in tandem with the recent improvements in OpenAI's API.

Historically, dealing with output parsing, especially with JSON responses, has been fraught with complexities. Ensuring the extracted data adheres to a specific schema or matches certain function calls often involves writing intricate and cumbersome error-checking code. Add to this the vagaries of AI and you often end up reasking and hoping it does a better job.

However, Pydantic, a Python library that provides data validation through Python type annotations, comes to the rescue! And when combined with OpenAI's new function call capabilities, it allows us to handle output parsing in a much more structured and reliable way with a much better d

Overview: Andrew Huberman, a professor of neurobiology and ophthalmology at Stanford School of Medicine, introduces the topic of dopamine and its relation to motivation, desire, craving, satisfaction, wellbeing, and addiction. He promises to dispel common myths about dopamine and provide tools for leveraging it to sustain energy, drive, and motivation.

Overview: Andrew Huberman discusses common myths about dopamine and how it actually works. He covers the biology and psychology of dopamine as well as neural circuits and dopamine schedules. He explains how various things like food, drugs, caffeine, pornography, and plant-based compounds can change our baseline levels of dopamine.

Overview: Harry introduces Kathy and her background in finance.

Kathy's Background

• Kathy was introduced to Capital Group at the tender age of 20.
• She was fascinated by economics and the way the world was going to work in the future.
• She has been running from indexed based investing and benchmarks in the traditional Asset Management world.