In this video, I explore the new o1 model and compare its capabilities to GPT-4, focusing on how each model excels in different areas such as broad reasoning and specialized STEM applications. I’ll break down key differences between these models, including their token limits and optimal use cases, giving you a clearer understanding of how to leverage them for your own projects. Additionally, I’ll walk you through the o1 Google Colab Workbook, which includes pre-configured Python scripts designed for hands-on experimentation. Whether you’re an AI researcher, developer, or simply curious about the latest AI advancements, this video provides an in-depth look at how to get started with o1.
Download the o1 Google Colab Workbook + Python Files: https://bit.ly/3AYjyjo
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About Me:
I’m Mark, a Data Science Manager by day and owner of Prompt Advisers by night, bringing over a decade of experience in AI to help you maximize the potential of applied AI. At Prompt Advisers, we focus on innovative AI solutions tailored to your needs.
My Mission:
To help you navigate the AI landscape confidently by providing practical knowledge, tools, and support to achieve your AI goals.
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0:00 – Introduction to LLM issues
0:16 – 01 model introspective improvements
0:41 – Comparison of GPT-4.0 and 01 preview
0:58 – Chain of thought vs. new approach
1:27 – 01 preview vs. 01 mini
2:08 – Reasoning tokens and solution refinement
3:23 – Solution refinement and security
4:31 – New prompting approach
5:57 – Markdown and prompt hygiene
6:59 – Side-by-side comparison begins
7:30 – Car sales statistics question
9:16 – Glucose formula and Collatz conjecture
10:19 – Deeper reasoning steps in 01 preview
11:46 – Testing SEO prompt generation
12:23 – OpenAI vs. Anthropic comparison
13:32 – Data analysis test
15:00 – Word count accuracy test
16:36 – Google Collab and model calling
17:21 – Testing large output limitations
19:08 – Conclusion and further testing”
