OpenAI’s new “deep-thinking” o1 model crushes coding benchmarks

Fireship
13 Sept 202405:47

TLDROpenAI's new model, 01, surpasses previous AI benchmarks in coding and complex reasoning tasks. While it's not AGI, 01's deep-thinking approach and reinforcement learning capabilities show significant improvements in coding challenges and problem-solving. Despite skepticism, 01's potential is vast, but it remains an AI tool rather than a gamechanger. The video explores 01's performance, its 'chain of thought' process, and the implications for the future of AI.

Takeaways

  • 😱 OpenAI has released a new model named '01', which is a significant leap in deep thinking and reasoning models.
  • 🚀 '01' has achieved massive gains in accuracy, particularly in PhD-level physics, math, and formal logic benchmarks.
  • 🏆 In coding abilities, '01' has shown remarkable improvement, breaking gold medal standards at the International Olympiad and Informatics.
  • 🤖 The model is not yet AGI (Artificial General Intelligence) and is not referred to as GPT-5.
  • 🔒 OpenAI has kept many details about '01' confidential, maintaining a sense of mystery around its capabilities.
  • 💡 '01' uses reinforcement learning to perform complex reasoning, simulating a thought process before providing answers.
  • 💼 OpenAI has been collaborating with Cognition Labs, which aims to replace programmers with AI.
  • 📈 There's skepticism about the true capabilities of '01', with some suggesting the benchmarks might be exaggerated for funding purposes.
  • 💻 '01' has demonstrated the ability to create complex programs with fewer errors compared to previous models.
  • 🤑 The model's advanced features come at a cost, with OpenAI potentially offering a premium plan for access to the full capabilities of '01'.

Q & A

  • What is the significance of the new model '01' released by OpenAI?

    -The '01' model by OpenAI is a state-of-the-art model that represents a new paradigm of deep thinking or reasoning models. It has shown significant improvements over previous benchmarks in math, coding, and PhD-level science.

  • How does the '01' model perform in coding tasks?

    -The '01' model demonstrated a remarkable improvement in coding tasks. At the International Olympiad and Informatics, it broke the gold medal submission when allowed 10,000 submissions per problem, and its codeForces ELO rating increased from the 11th percentile to the 93rd percentile.

  • What is the role of Cognition Labs in the development of the '01' model?

    -Cognition Labs has been secretly working with OpenAI. They aim to replace programmers with AI models like '01', which has shown a significant increase in problem-solving ability, going from solving 25% of problems with GPT-4 to 75% with '01'.

  • What is the difference between '01 mini', '01 preview', and '01 regular'?

    -These are different versions of the '01' model with varying levels of access and capabilities. '01 mini' and '01 preview' are accessible to the general public, while '01 regular' is more advanced and currently restricted, with hints of a potential $2,000 Premium Plus plan for access.

  • How does the '01' model utilize reinforcement learning?

    -The '01' model uses reinforcement learning to perform complex reasoning. It produces a chain of thought before presenting an answer, allowing it to refine its steps and backtrack when necessary, which helps in producing complex solutions with fewer errors.

  • What are 'reasoning tokens' and how do they contribute to the '01' model's performance?

    -Reasoning tokens are outputs that help the '01' model refine its steps and backtrack when necessary during the problem-solving process. They contribute to the model's performance by allowing it to think through problems more thoroughly and provide more accurate solutions.

  • How does the '01' model handle the task of creating a playable snake game?

    -The '01' model was able to create a playable snake game in a single shot, showcasing its advanced capabilities in coding and problem-solving compared to previous models.

  • What is the 'Chain of Thought' feature of the '01' model, and how is it different from previous models?

    -The 'Chain of Thought' feature allows the '01' model to think through problems by considering various aspects and constraints before providing a response. This is different from previous models as it involves a more deliberate and structured approach to problem-solving.

  • How does the '01' model compare to Google's AlphaProof and AlphaCoder in terms of math and coding competitions?

    -While Google's AlphaProof and AlphaCoder have been dominating math and coding competitions using reinforcement learning, the '01' model is the first of its kind to become generally available to the public, offering a new level of accessibility and potential for AI in these fields.

  • What are the limitations of the '01' model as highlighted in the script?

    -Despite its advancements, the '01' model still has limitations. It is not truly intelligent and can produce buggy outputs. Additionally, it is not fundamentally game-changing but rather an improvement over GPT-4 with the ability to recursively prompt itself.

Outlines

00:00

🤖 AI's New Frontier: GPT-1's Groundbreaking Capabilities

The paragraph discusses the skepticism and subsequent surprise regarding the release of OpenAI's new AI model, GPT-1, which has surpassed expectations in its capabilities. GPT-1 is not just another AI model; it represents a paradigm shift with significant improvements in reasoning, math, coding, and science. Despite initial doubts, GPT-1's performance in benchmarks, especially in coding challenges, has been remarkable, suggesting a potential revolution in AI. The paragraph also touches on the collaboration between OpenAI and Cognition Labs, hinting at the model's application in replacing programmers. However, it also raises questions about the model's true intelligence and the hype surrounding it, suggesting that while GPT-1 is a significant step forward, it may not be as transformative as some claim.

05:02

🔍 Debunking Hype: The Reality of GPT-1's Intelligence

This paragraph delves into the practical testing of GPT-1's capabilities by comparing it with GPT-4 in a coding challenge. While GPT-4 showed limitations and required multiple prompts to produce a working code, GPT-1 was able to compile and follow game requirements more accurately. However, despite initial success, GPT-1's output was buggy and led to infinite loops and UI issues. The paragraph concludes by questioning the true intelligence of GPT-1, suggesting that it may not be as advanced as it seems and that its capabilities might be overstated. It also humorously compares the AI's impact to that of the car on horses, implying that while AI may be evolving, it's not yet at a stage to replace human programmers.

Mindmap

Keywords

💡Deep-thinking model

A 'deep-thinking model' refers to an advanced artificial intelligence model capable of complex reasoning and problem-solving. In the context of the video, OpenAI's 'o1' model is described as a 'deep-thinking' model because it demonstrates significant improvements in tasks requiring logical reasoning, such as math, coding, and advanced scientific problems. The model's ability to 'think' through a problem before providing a solution is highlighted as a key feature, setting it apart from previous AI models.

💡Benchmarks

Benchmarks are standardized tests or measurements used to evaluate the performance of systems, in this case, AI models. The video discusses how the o1 model 'crushes' or significantly outperforms previous benchmarks in coding, math, and PhD-level science. These benchmarks serve as a comparative metric to illustrate the model's capabilities and advancements over its predecessors, such as GPT-4.

💡Reinforcement learning

Reinforcement learning is a type of machine learning where an agent learns to make decisions by taking actions in an environment to maximize some notion of cumulative reward. In the video, it is mentioned that the o1 model uses reinforcement learning to perform complex reasoning. This involves the model generating a 'chain of thought' before presenting an answer, which is a novel approach that allows for more refined and accurate responses.

💡Reasoning tokens

Reasoning tokens are outputs generated by AI models during the problem-solving process that help refine the model's steps and backtrack when necessary. The video explains that the o1 model produces these tokens, which are part of its 'deep-thinking' process. They allow the model to work through complex solutions with fewer errors, although this process requires more time and computational resources.

💡GPT (Generative Pre-trained Transformer)

GPT stands for Generative Pre-trained Transformer, which is a type of deep learning model that is trained on large amounts of data to generate human-like text. The video discusses the evolution of GPT models, leading up to the o1 model. Each new version of GPT is designed to be more advanced, with improved capabilities in language understanding and generation.

💡Coding ability

The video emphasizes the o1 model's enhanced 'coding ability,' showcasing its performance at the International Olympiad and Informatics. The model's ability to solve coding problems with high accuracy is a significant advancement, indicating that AI is becoming increasingly capable in areas traditionally dominated by human expertise.

💡Chain of Thought

The 'Chain of Thought' is a concept introduced in the video to describe the process by which the o1 model approaches problem-solving. It involves the model considering various aspects of a problem, such as input and output shapes, programming language constraints, and other relevant factors, before providing a solution. This method is intended to mimic human thought processes and lead to more accurate and comprehensive results.

💡Hallucinations

In the context of AI, 'hallucinations' refer to the model generating incorrect or nonsensical outputs. The video mentions that the o1 model produces fewer 'hallucinations' due to its 'deep-thinking' approach and the use of reasoning tokens. This term is used to highlight the model's improved accuracy and reliability compared to previous AI models.

💡Cognition Labs

Cognition Labs is mentioned in the video as a company that has been working with OpenAI to develop AI models capable of replacing programmers. The collaboration between OpenAI and Cognition Labs is an example of how AI technology is being advanced and applied in real-world scenarios, potentially transforming industries and job roles.

💡AGI (Artificial General Intelligence)

AGI, or Artificial General Intelligence, refers to an AI system that possesses the ability to understand or learn any intellectual task that a human being can do. The video clarifies that the o1 model, despite its advancements, is not AGI. This distinction is important as it sets expectations for the capabilities and limitations of current AI technology.

Highlights

OpenAI releases a new state-of-the-art model named 01, a 'deep-thinking' model that surpasses previous benchmarks.

The 01 model is not just another basic GPT; it represents a new paradigm of AI capable of deep reasoning.

01 achieves significant gains in accuracy, especially in PhD-level physics and multitask language understanding.

In coding abilities, 01 shows a remarkable improvement, breaking gold medal standards at the International Olympiad and informatics.

The model's performance in coding is enhanced by its ability to solve 75% of problems, a stark contrast to GPT 4's 25%.

OpenAI's 01 model is not yet ASI, AGI, or GPT 5, indicating it's not a fully sentient AI but a significant step forward.

OpenAI's commitment to openness is contrasted by keeping the model's details closed off to the public.

Three new models are introduced: 01 mini, 01 preview, and 01 regular, with the latter still restricted.

The 01 model uses reinforcement learning to perform complex reasoning, producing a chain of thought before providing answers.

Reasoning tokens are outputs that help the model refine its steps and backtrack, leading to complex solutions.

The deep-thinking approach requires more time, computing power, and money, with a cost of $60 per 1 million tokens.

Examples of 01's capabilities include creating a playable snake game and solving a nonogram puzzle.

The model can also reliably answer complex questions, such as the number of 'S's in 'strawberry'.

Google's Alpha proof and Alpha coder have been dominating math and coding competitions using similar reinforcement learning techniques.

01's chain of thought is not shown to end users, even though they pay for the reasoning tokens.

In a test, 01 was able to compile a game request immediately, following the game requirements closely.

Despite initial success, 01's game creation had bugs, including infinite loops and a poor UI.

The model is not truly intelligent, but the chain of thought approach holds significant potential.

01 is compared to a car in 1910, suggesting that while it's not a gamechanger, it represents a shift in AI capabilities.

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