To get involved in AI, starting with online courses like those on Coursera or Stanford's accessible classes is recommended, along with practical exercises using frameworks like TensorFlow.

Deep neural networks are driving significant changes in technology, and it's important to stay informed about advancements in this field.

Training AI models is an exciting field with much potential for progress, and it's essential to involve more people in shaping AI's future.

DeepMind's work on reinforcement learning, particularly with AlphaGo and AlphaZero, has shown that algorithmic advancements can lead to substantial improvements in AI performance, often requiring far less training than traditional methods.

After two decades in AI, I've witnessed the transition from AI winters to the rise of deep learning, which has opened up new possibilities in various applications.

DeepSeek has a shocking $5 million training cost, highlighting the disparity in resources available to different entities for developing AI models.

It's important for children to understand the basics before using AI tools to extend their capabilities.

The promise of AI lies in making high-quality resources available to everyone, regardless of their background or social position.

Using local documentation for APIs improves the accuracy of AI implementations. I download the documentation and instruct the AI to read it before proceeding with coding.