Understanding the Potential & Limitations of GPT-3 & Large Language Models🤖🧠

This comprehensive document delves into the intricacies of large language models, with a keen focus on the revolutionary GPT-3. As with any new technology, it is imperative to understand the origins of the model, through published papers or technical reports. Multi-modal in nature, GPT-3 stands out for its ability to process text, images, and voice, showcasing human-level performance in academic and professional benchmarks. With post-training alignment being a key variable that enhances its capabilities, GPT-3 has the potential to revolutionize various applications, including software code prediction.
However, while the next version, GPT-4, promises to improve on multiple-choice questions, human evaluation, and coding tasks, the limitations of large language models in terms of hallucinations and internal factual evaluation by category cannot be ignored.
This document serves as a guide to understanding the capabilities and limitations of large language models, providing valuable insights that are essential to their utilization.
--TIMESTAPMS--
00:00 Introduction
00:57 What is GPT?
1:28 What is GPT 4?
3:43 How Large Language Models Behave?
4:22 Bechmark of Large Language Models
5:00 Capabilities & Limitations
5:57 Predictable Scaling
6:19 Loss Prediction
6:44 Scaling of Capabilities on Human Evaluation
8:05 OpenAI Codebase Next Word Prediction
10:05 Exam Results by GPT 3.5 Performance
10:52 Performance of GPT 4 on Academic Benchmark
12:19 GPT-4 3-Shot Accuracy on MMLU across languages
13:00 Example of GPT-4 visual input
13:19 Internal Factual Evaluation by Category
14:21 Example of GPT-4 giving correct and incorrect responses on TruthfulQA
14:27 Risks & mitigations
14:48 Disallowed Prompts
15:03 Model-Assisted Safety Pipeline
15:25 Improvements on Safety Metrics
16:00 Incorrect Behavior Rate on Disallowed and Sensitive Content
16:12 Conclusion
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I am a HealthTech expert who believes that technology, especially AI, can enhance human lives by saving lives and preserving limbs. I am a Founders' Founder who shares his journey of founder highs and lows to help others learn. As an Angel Investor, I invest in early-stage startups.
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[@beatriz0helena]

Hi, I am a neuro resident trainee and am immensely grateful for your channel. I am trying to get myself up-to-speed with understanding Large Language Models. there's a dearth of formal instruction unfortunately in the current the medical/residency education system on these topics, so thank you for filling in on this gap. As mentioned around 2:40 of video, if you could make a video on how transformers work that would be most appreciated.

[@junaidkaliamd]

Hi there! Thank you so much for your kind words and support. I'm delighted to hear that you find the content helpful in your neuro residency training. You can watch this video that delves into the workings of transformers. You can check it out here: ua-cam.com/video/bCz4OMemCcA/v-deo.html
Feel free to let me know if there are any specific aspects you'd like me to cover in future videos. Best of luck with your training, and thanks again for being part of our community!