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OpenAI o1 model coding performance is mindblowing. Today, I built a famous "Chrome Dinosaur Game" in less than 5 minutes. I added a new functionality where the dinosaur bends instead of jumping to avoid birds.

251,465 次观看 • 1 年前 •via X (Twitter)

11 条评论

Raina (⁠◕⁠ᴗ⁠◕⁠✿⁠) 的头像
Raina (⁠◕⁠ᴗ⁠◕⁠✿⁠)1 年前

that's mega dope, however regarding the dino game, i'm sorry to tell you that the dinosaur has been able to bend for many years now, with the down arrow :p

Haider. 的头像
Haider.1 年前

really? I haven't played the game for like many years, but I saw a video and thought bend could be cool.

TypeSteady 的头像
TypeSteady1 年前

Your perception is that it’s built a game it’s basically stolen code from trained knowledge and knows how to put the code in the right place, not so freaky if you know …

Haider. 的头像
Haider.1 年前

That is one of the most childish comment I have ever read.

Pablo Huichalaf 的头像
Pablo Huichalaf1 年前

i feel that is better than sonnet, i have seen some benchmarks and sonnet is still the best, but the feeling is different.

Haider. 的头像
Haider.1 年前

sonnet is also very good for code but the current o1 models is way better.

Amankeldin 的头像
Amankeldin1 年前

Bemd function already been , isn't it

Sebastian Castillo 的头像
Sebastian Castillo1 年前

Your mind blows when a memory fetches a string? I mean well yeah… flip flops are amazing.

The College Contemporary 的头像
The College Contemporary1 年前

Is this really better than what we could already do? Chatbots could be used to make simple games since like 2022, right?

Curry_TW 的头像
Curry_TW1 年前

Can you use the o1 model? Or are you referring to o1-mini? o1 preview? Which one are you referring to?

Haider. 的头像
Haider.1 年前

o1-preview is best for coding

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OpenAI just announced API access to o1 (advanced reasoning model) yesterday. I'm delighted to announce today a new short course, Reasoning with o1, built with OpenAI, and taught by Colin Jarvis, Head of AI Solutions at OpenAI, to show you how to use this effectively! Unlike previous language models which generate output directly, o1 “thinks before it responds,” and generates many reasoning tokens before returning a more thoughtful and accurate response. It is great at complex reasoning -- including planning for agentic workflows, coding, and domain-specific reasoning in STEM fields like law. But how you should use it is quite different from other LLMs. I think o1 will be a game changer for many AI applications; and in this course, you'll learn how to use it effectively. In detail, you’ll: - Learn to recognize what tasks o1 is suited for, and when to use a smaller model, or combine o1 with a smaller model - Understand the new principles of prompting reasoning models: Be simple and direct; no explicit chain-of-thought required; use structure; show rather than tell - Implement multi-step orchestration in which o1 plans, and hands tasks over to gpt-4o-mini to execute specific steps; this illustrates a design pattern to optimize intelligence (accuracy) and cost - Use o1 for a coding task to build a new application, edit existing code, and test performance by running a coding competition between o1-mini and GPT 4o - Use o1 for image understanding and learn how it performs better with a "hierarchy of reasoning," in which it incurs the latency and cost upfront, preprocessing the image and indexing it with rich details so it can be used for Q&A later - Learn a technique called meta-prompting, in which you use o1 to improve your prompts. Using a customer support evaluation set, you'll iteratively use o1 to modify a prompt to improve performance You'll also learn about how OpenAI used reinforcement learning to produce a model that uses "test-time compute" to improve performance. I think you'll find this course enjoyable and valuable. Please sign up for it here:

Andrew Ng

357,592 次观看 • 1 年前