In my experience, ChatGPT-4 exhibits an impressive ability to align with user intent. However, sometimes, when presented with explicit constraints (e.g. "use only the following characters: Arthur and his mom; DO NOT introduce any new characters"), the model seems to adhere to
PROMPT ENGINEERING
-
Training Fine-Tuning LLMs Production New Video Series
By
–
This is the third iteration of my new video series for our free course "Training & Fine-Tuning LLMs for Production" https://
learn.activeloop.ai/courses/llms In this one, we dive into unlocking the full potential of large language models (LLMs). I also have an exciting announcement to share with -
Pro Tips for Improving AI Responses and Performance
By
–
New video: Pro Tips for Improving AI Responses and Performance: How to tune your Language Models! Learn more in the video: https://
youtu.be/fylqJ3E4mwQ #ai #llm #llms #languagemodel #gpt #llama #chatgpt #whatsai -
DALLE3 Image Generation Randomness and Seed Behavior Analysis
By
–
Yes, though I'm not sure how much of this is true though. I don't see too much randomness between dalle3 conversations. Same prompt often gives same image.
Which could mean GPT is picking the same random seed. Or there might be a user based seed. I don't know. -
Prompt Engineering Mitigates AI Bias and Misinformation in App Commercialization
By
–
AI systems can unintentionally perpetuate biases or misinformation, challenging app commercialization. Prompt engineering can mitigate these issues cost-effectively, enhancing AI output control for a reliable landscape.
-
Iterative Token-Thought Loop Architecture for LLMs
By
–
Hmm what if you did token->thought1->token->thought2->token->thought3->token->thought4->token->thought1->token->thought2… ?
-
Are Thought Tokens Different Pause Tokens in LLMs?
By
–
Are thought1, thought2, thought3… actually different tokens? Or all copies of the same pause token?
-
Productivity Gains from LLMs: Share Your Favorite Prompts
By
–
How much would you estimate your productivity gains from using LLMs in your work/study? Tell us your favorite prompts for your current tasks! We might discover some very cool gems!
-
Error in code generated from a mathematical formula
By
–
The formula below is from one of several recent viral threads demoing one-step math screenshot → code in ChatGPT, where the generated code is wrong. In reality, it takes several rounds of careful feedback just to correctly transcribe that formula to LaTeX:
-
Limitations of one-step math to code in ChatGPT
By
–
One-step math → code in ChatGPT is a fun demo, but not reliable. To do it for real, you likely have to:
– Transcribe the formula to LaTeX; verify; correct
– Have it explain any notation you don't know
– Generate code with verbose translation comments
– Read those comments