Key insights

• ⚙️ Custom GPT allows for creating custom instructions and blending them together to achieve a desired outcome.
• 🛠️ Using LLMS to do prompt engineering, Obtaining custom instructions from a custom GPT called code co-pilot, Blending custom instructions to create a hybrid of custom GPTs, Importance of prompt engineering for customizing GPT output
• 🔍 Exploring different prompt structures, Observing similarities in prompt structures from different individuals, Some prompt structures are straightforward, Adjustments may be needed for certain prompt structures
• 📊 Using prompting and chain prompting to improve Excel formulas instructions, Evaluating differences between model-generated and original instructions, Utilizing cosine similarity to compare and refine outputs
• 🔗 The AI can compare the similarity of two pieces of text using cosine similarity analysis, Breadcrumbing is a strategy of asking small requests that add up to the final outcome
• ⚖️ Similarity score of 745 indicates exact match, 0 means not even close, Use similarity scores to build your own custom GPT, Explore GPTs in the store and create a bespoke solution, Combine multiple GPTs for a unique solution

Q&A

• How can similarity scores be used to create custom GPT solutions?

  Similarity scores can be used to build personalized GPT solutions, where a high score indicates an exact match, while a lower score indicates lesser similarity. These scores can be utilized to explore GPTs in the store and combine them to create bespoke solutions.

• How does AI analyze text similarity and what is breadcrumbing in this context?

  AI can compare the similarity of two pieces of text using cosine similarity analysis. Additionally, breadcrumbing is a strategy involving asking small requests that add up to the final outcome in the context of AI interaction.

• What is the process of refining instructions using prompting and chain prompting?

  Prompting and chain prompting can be used to refine instructions, such as Excel formulas, through a model. One can evaluate the differences between model-generated and original instructions, and utilize cosine similarity to compare outputs and make further refinements.

• How can prompt structures be explored for customizing GPT output?

  One can explore different prompt structures to understand the process of prompt generation. It is possible to observe similarities in prompt structures from different individuals, and while some prompt structures are straightforward, others may require adjustments for customization.

• What is custom GPT and how can it be used to create custom instructions?

  Custom GPT allows for creating personalized instructions and blending them to achieve specific outcomes. Prompt engineering can be leveraged to customize the GPT output, and custom instructions can be obtained from a custom GPT like code co-pilot and blended to create a hybrid of custom GPTs.

• 00:00 Learn how to clone or emulate custom instructions for GPT in the GPT Store without being a prompter. Use markdown for easy categorization and readability of instructions.
• 01:06 Custom GPT allows for creating custom instructions and blending them together to achieve a desired outcome. Prompt engineering can be leveraged to customize GPT output.
• 02:15 Exploring different prompt structures to understand the process of prompt generation. Similarities in prompt structures from different individuals can be observed. Some prompt structures are straightforward while others may require adjustments.
• 03:21 A demonstration of using prompting and chain prompting to refine Excel formulas instructions through a model, evaluating the differences, and using cosine similarity to compare outputs.
• 04:43 The AI can be used for comparing the similarity of two pieces of text using cosine similarity analysis. Breadcrumbing is a strategy of asking small requests that add up to the final outcome.
• 06:00 You can use similarity scores to create your own custom GPT, explore GPTs in the store, and build a bespoke solution using existing GPTs.