Learning from Large Language Models: Training Your Brain

Recent advances in artificial intelligence (AI) have led to models like GPT that can process vast amounts of data and generate remarkably human-like text. While AI systems learn from huge datasets, we can also benefit from applying principles of large-scale learning. This article explores how the training process behind sophisticated AI can inform our own learning and personal growth.

Like AI models, our learning relies on data intake from diverse sources. For AI systems, the "food" is massive text corpora. For us, it can include books, lectures, videos, conversations and lived experiences. While the scale differs, both AI and we build understanding through exposure to quality information.

The power of data in learning is twofold:

1. Volume of Data: With a large volume of data, there is more information to learn from. This increases the chances of encountering a wide range of ideas and perspectives, fostering a more comprehensive understanding.
2. Variety of Data: Variety in data exposes the learner to different contexts and applications of the knowledge, which strengthens understanding and allows for better generalization to new situations.

When it comes to applying the AI learning process to human learning, we need to consider some of the key elements in this process.

The first step in learning from large datasets is repeated exposure. Just as AI models train on vast datasets multiple times, we can benefit from repeatedly engaging with educational material.

• Repetition with Variation: To prevent rote learning, it's crucial to vary the way in which we revisit material. This could involve mixing up the order of topics or employing different learning strategies, such as active recall and spaced repetition.
• Contextual Learning: Each time we revisit material, we can focus on a different aspect or context. This aids in developing a deeper, more nuanced understanding.

One of the ways that AI models like GPT-4 learn is by predicting what comes next. This can be a powerful tool for human learning too.

• Active Engagement: By predicting outcomes or next steps, we become active participants in our learning process. This leads to better retention and understanding.
• Immediate Feedback: When our predictions are incorrect, we should it feed it back and help us identify gaps in our knowledge and adjust our learning strategies accordingly.

Like AI models that are trained on carefully curated datasets, humans learn better when material is organized and sequenced appropriately.

• Ensure foundational knowledge is established before moving to more advanced concepts. Build up complexity gradually.
• Structure topics logically with clear connections between concepts.
• Revisit fundamentals regularly as an anchoring point when learning new material.

Leverage knowledge from one domain when learning something new. Transferable skills like critical thinking can aid learning in diverse contexts.

• Draw parallels between new concepts and existing knowledge.
• Identify reusable frameworks, strategies, and principles that could be applied in the new domain.

Rohan wanted to improve his Spanish conversational skills. He applied principles from large language models:

• Used a variety of resources - books, podcasts, movies, exchange programs. This provided diverse Spanish language data.
• Reviewed fundamentals regularly - grammar structures, vocabulary. Built complexity over time.
• Practiced predicting responses in conversations. Used feedback to improve.
• Transferred reading strategies from his native English when learning Spanish
• Listened and read Spanish content repeatedly in different contexts.

By incorporating techniques like repetition, prediction, curriculum learning and transfer learning, Rohan was able to significantly improve his Spanish conversation ability.

Learning, like any other skill, requires practice. With consistency and the right strategies, we can train our brains to become better learners, continually improving our ability to understand and apply new information.

"The capacity to learn is a gift; the ability to learn is a skill; the willingness to learn is a choice." — Brian Herbert, author of "Dune: House Atreides."