Can Generative AI Reason like Humans?
Generated with AI ? August 3, 2024 at 12:31 p.m.

Can Generative AI Reason like Humans?

Keywords: #AI #GenAI #ChatGPT #copilot #gemini #architecture #azure

Generative AI (Gen AI) has taken the world by storm. One might wonder if it can reason like humans and answer "why" questions on data, find root cause to the problems and render an opinionated analysis.

In my "non rigorous" research, I find three camps:

1. (Towards) No [1,2,3,6,9]: Fundamentally, they are deep neural networks and generally good at predicting next word in a sequence (with an authoritative language). This may give an illusion of reasoning and authenticity.

2. (Towards) Yes [4,7,10]: Neural networks are generally considered a black box. With undisclosed specifics in the closed source models, is there any secret sauce?

3. Depends [5, 8]: on the training data and methods.

What are your thoughts?

References

[1] Can LLMs Reason & Plan? (Talk @Google_DeepMind LLM Reasoning Seminar) ( youtube.com )

[2] What’s wrong with LLM and what should be built instead?

[3] CHATGPT DOESN'T REASON! (Top scientist bombshell) ( youtube.com )

[4] Large Language Models and The End of Programming - CS50 Tech Talk with Dr. Matt Welsh - YouTube

[5] Reasoning Using Large Language Models ( youtube.com )

[6] AI is a Lie - Cutting Through the Hype ( youtube.com )

[7] Ilya: the AI scientist shaping the world ( youtube.com )

[8] Can LLMs reason? | Yann LeCun and Lex Fridman ( youtube.com )

[9] The Turing Lectures: The future of generative AI ( youtube.com )

[10] The moment we stopped understanding AI [AlexNet] ( youtube.com )

I am an independent contractor who works on multiple Gen/AI and cloud projects across North America. I also participated in the Startup School of Y-Combinator in 2019. These are my own views and I use AI to co-produce the contents.

Godwin Josh

Co-Founder of Altrosyn and DIrector at CDTECH | Inventor | Manufacturer

3 个月

The confluence of #GeAnAI, #hChatPGPT, and #Copilot heralds a paradigm shift in software development, democratizing access to sophisticated AI-powered tools. Your exploration of #Geminis's architecture within the context of #Azure is particularly insightful, highlighting the potential for scalable and robust solutions. Given your focus on model interpretability, how do you envision leveraging techniques like attention visualization to enhance user trust and understanding in #Gemini's decision-making processes, especially when applied to complex tasks like code generation?

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