4. Make a facebook messenger as a single html file. GPT-4o does this in 6 seconds(!): pic.twitter.com/qsOdMXtpnx
— God of Prompt (@godofprompt) 5 décembre 2024
4. Make a facebook messenger as a single html file. GPT-4o does this in 6 seconds(!):
LLMS
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Using GPT-4o to generate a Facebook Messenger clone
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Using GPT-4o to Perform Technical Chart Analysis
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3. Copy a chart and make GPT-4o do technical analysis on it: pic.twitter.com/jNnOKxIAGy
— God of Prompt (@godofprompt) 5 décembre 20243. Copy a chart and make GPT-4o do technical analysis on it:
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Automating Figma design generation using GPT-4o
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2. The future that is happening.
— God of Prompt (@godofprompt) 5 décembre 2024
Automation powered by GPT-4o generates Figma designs based on PRD. pic.twitter.com/pxuSF0ocNN2. The future that is happening. Automation powered by GPT-4o generates Figma designs based on PRD.
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10 Ways to Use ChatGPT for Increased Productivity
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ChatGPT will be the most powerful AI tool in 2024. But most people don’t know the best ways to use it. Here are 10 ways ChatGPT can 10x your productivity:
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Not All Tokens Are Essential for Language Model Pretraining
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Not All Tokens Are What You Need for Pretraining Zhenghao Lin, Zhibin Gou, Yeyun Gong, Xiao Liu, yelong shen, Ruochen Xu, Chen Lin, Yujiu Yang, Jian Jiao, Nan Duan, Weizhu Chen https://
openreview.net/pdf?id=0NMzBwq
aAJ
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Normalization and Token Counting in AI Model Evaluation
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Isn't the point of normalization to control for the number of tokens (i.e. using mean rather than sum), so these 20% variations should be accounted for with acc_norm. I figured that's why most people use acc_norm these days!
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Token Optimization and Model Performance Improvements Debate
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Well, if you're willing to debate token equivalence I think that's a fair approach! The code itself hasn't changed and HellaSwag score is significantly higher given the same number of steps. It's not only fewer tokens on disk but they are "better" tokens too, IMHO +40% total.
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Token Density Impact on Validation Metrics in Model Training
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Nope, it wouldn't be the same; that's the catch! Because the token density is about 20% higher when the same text is processed, the validation metric ends up being around 4.18. Making the train/val boundary at exactly the same word is possible, but it won't change the mismatch.
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The Importance of Prompt Writing for AI Interaction
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The most important thing to use ChatGPT: Prompt writing people need to learn it.
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NVIDIA GPU Performance: Utilization vs. Saturation
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Understanding NVIDIA GPU Performance: Utilization vs. Saturation (2023) https://
bit.ly/3Bd0mis
#AI #MachineLearning #DeepLearning #LLMs #DataScience