The emergence of large language models has allowed us to create a conversational partner that we couldn't build before, enhancing the user experience.

Large language models can significantly improve healthcare by providing access to a wealth of knowledge, potentially changing the way rare conditions are treated.

In medical diagnostics, models can demonstrate impressive reasoning capabilities, mapping symptoms to correct medical cases effectively.

AI has transformed our business, enabling us to offer conversation practice through large language models, which was previously impossible without human interaction.

When developing a new large language model product, it's essential to iterate on prompts to find what works best for your specific use case.

Developers can fine-tune models using a variety of data sources, such as company chat logs or marketing communications, to adjust tone and style for their specific needs. Fine-tuning a large language model involves capturing feedback data from production usage, which helps improve the model based on real customer interactions.

While there are significant potential benefits to large language models, we must tread carefully due to the ethical minefield they present.

Using large language models as prototyping tools can be effective; they allow for rapid development and testing of ideas before creating more specialized models tailored to specific tasks.

English is becoming the new assembly language for large language models, meaning that effective communication with AI requires structuring language correctly, even if syntax is less critical than before.