Ottosson further points out that GPT technology is slow and often produces eccentric outcomes, which can be a hindrance to user experience and acceptance. He suggests that while GPT has tremendous potential and can enhance productivity, it is not a universal solution for all business problems. He advises businesses to allow their employees to use GPT through interfaces that ensure data security and ethical compliance, rather than rushing into GPT projects.
Key takeaways:
- GPT (Generative Pre-trained Transformer) is a foundational technology, not an off-the-shelf solution, and requires deep understanding and substantial resources for effective implementation.
- Training GPT on proprietary data is not as simple as it seems, involving resource-intensive challenges, data quality questions, and compliance considerations.
- GPT faces significant challenges such as latency and limitations, and the difficulty of removing weird output, which can hinder its seamless transition into production.
- While GPT is a remarkable technological advancement, it is not a universal solution for all business problems. Businesses should approach GPT realistically and ensure data security and ethical compliance when using it.