The session focuses on the process of creating custom large language models (LLMs) while sharing tips and insights from real-life experiences. The speaker emphasizes that while pre-existing models like OpenAI offer great capabilities, they can also make mistakes, making a case for developing personalized models that better serve specific business needs. He encourages utilizing reliable resources from reputable tech companies and advises an understanding that the journey involves complexities that could be quite challenging. The overall aim is to inspire attendees towards an informed approach to LLM development.
It's essential to understand that creating your own large language model can provide insights specific to your business needs, despite the perceived reliability of established models.
Embarking on building your own LLM requires a realistic approach to cost, time, and potential challenges, which could certainly be painful at times.
Using resources from major players like Microsoft, Hugging Face, and GitHub can facilitate the process of developing an LLM tailored to your specific requirements.
Itâs crucial to realize that while OpenAI and others are powerful, they can still make mistakes; sometimes your unique context warrants building a custom solution.
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