AI's strength lies in scaling human expertise, not in replacing it. Instead of using AI for tasks one is bad at, it's more effective to leverage AI to amplify one's strengths. By training AI on proprietary data and expertise, individuals and organizations can achieve superior outcomes compared to general AI models.
Leveraging AI for Strengths
• 00:00:00 AI should be used to amplify existing strengths and expertise rather than focusing on compensating for weaknesses. Instead of using AI to become an expert in areas one is not skilled in, it's more beneficial to train AI on one's existing expertise to achieve better results. The speaker highlights this counterintuitive approach to AI, suggesting that it is often misapplied.
AI Training on Proprietary Data
• 00:01:29 AI models learn patterns from the data they are trained on, and general AI models are trained on publicly available information, leading to average outputs. By feeding AI proprietary data and specific expertise, users can create a unique 'bubble' where the AI learns specific patterns. This allows the AI to generate outputs that are superior to the general AI model's average outputs, as it's based on specialized, high-quality data.