Is AI really getting dumber? Llama2 vs GPT-4

Fireship
20 Jul 202303:16

TLDRIn the latest Code Report, the host discusses the evolution of AI language models, highlighting the release of Meta's LLaMA 2, which boasts 70 billion parameters and a 4,000 token context length. Despite its commercial license and potential for widespread use, LLaMA 2 is not as sophisticated as GPT-4. The video also touches on the safety measures implemented in LLaMA 2, such as reinforcement learning from human feedback, and the performance variance of GPT-3.5 over time, particularly in code generation and sensitive topics. The host humorously notes the absence of a singularity and continues to create content on programming, while acknowledging the growing complexity of AI safety measures.

Takeaways

  • 📅 The video is dated July 20th, 2023, and discusses recent developments in AI language models.
  • 🚀 Meta and Microsoft have released a new family of large language models called LLaMA 2.
  • 🌟 The largest LLaMA 2 model has 70 billion parameters and a context length of 4,000 tokens.
  • 💼 LLaMA 2 is available with a commercial license, allowing for easier adoption and use by businesses.
  • 🔍 LLaMA 2 can be self-hosted and used commercially for apps with less than 700 million monthly active users.
  • 🔥 A comparison between LLaMA 2, GPT-4, and Google's generative AI tool was conducted based on their responses to a challenge.
  • 📝 LLaMA 2's response to expressing Murphy's Law was verbose and well-written but less sophisticated than GPT-4's.
  • 📉 A study on GPT-3.5 (ChatGPT) showed its performance in code generation has degraded over time.
  • 🔒 LLaMA 2 includes safety features such as reinforcement learning from human feedback to guide AI behavior.
  • 📉 Traffic to the ChatGPT site declined for the first time by 10% last month.
  • 🤖 The video host humorously expresses disappointment that AI hasn't taken over or reached the singularity yet.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is the introduction and comparison of a new large language model called LLaMA 2, released by Meta in partnership with Microsoft, with GPT-4 and Google's generative AI tool.

  • What are the key features of LLaMA 2?

    -LLaMA 2 has 70 billion parameters and a context length of 4,000 tokens. It is released with a commercial license, allowing for easy download, use, and commercial hosting for apps with less than 700 million monthly active users.

  • How does LLaMA 2 compare to GPT-4 in terms of capabilities?

    -While LLaMA 2 is not as powerful as GPT-4, it offers near GPT-4 capabilities at a lower cost, making it a more accessible option for developers and businesses.

  • What was the challenge given to GPT-4, LLaMA 2, and Google's AI tool?

    -The challenge was to provide alternative ways to express the idea of Murphy's Law: 'Anything that can go wrong will go wrong.'

  • How did the different AI models handle the Murphy's Law challenge?

    -GPT-4 provided a very tourist-like response, Google's AI generated a shorter but faster response with additional context and web links, and LLaMA 2 gave a verbose and well-written response.

  • What are some limitations of LLaMA 2 compared to GPT-4?

    -LLaMA 2 is not as sophisticated as GPT-4, especially in poetry generation and complex programming tasks. GPT-4's closed and paid nature makes it less accessible for direct comparison in benchmarks.

  • How does the video script address the safety of AI models?

    -The script mentions that the word 'safety' is mentioned 299 times in Meta's paper on LLaMA 2, and one of the safety measures is reinforcement learning from human feedback.

  • What was the observation about the performance of GPT-4 over time?

    -A study found that GPT-4's performance in code generation has become more verbose and less directly executable over time, which is considered a negative change.

  • How has the public interest in AI and chatbots like GPT-4 evolved?

    -The video mentions that traffic to the GPT-4 site declined for the first time, indicating a possible shift in public interest.

  • What was the presenter's expectation for AI development by the current date?

    -The presenter expected AI to have reached the singularity or taken over, but they are still discussing topics like JavaScript frameworks, indicating that AI has not advanced to that extent.

  • How did LLaMA 2 respond to a request for building a high-yield nuclear weapon?

    -LLaMA 2 refused the request, stating that it is highly regulated and morally reprehensible, which the presenter humorously dismisses as an opinion.

Outlines

00:00

📅 Reflecting on AI's Past and Present

The video script opens with a nostalgic look back at the days when AI like ChatGPT could provide detailed instructions on complex and dangerous topics. It contrasts this with the current state of AI, which is more cautious and safety-focused, even refusing to guide on simple tasks like cooking rice due to potential risks. The discussion then shifts to the recent release of LLaMA 2, a new language model by Meta in partnership with Microsoft, which offers commercial licensing and the ability to self-host for smaller apps, making it an attractive alternative to GPT-4.

📈 Comparing LLaMA 2 with GPT-4 and Google's AI

The script describes a challenge given to three AI models: GPT-4, LLaMA 2, and Google's new generative AI tool. Each model was tasked with expressing Murphy's Law in different ways. The ChatGPT response was practical, Google's was quick and provided context, while LLaMA 2's response was verbose and well-written. However, it was noted that GPT-4's closed and paid nature makes direct comparison difficult, and LLaMA 2's technical paper is more informative than OpenAI's marketing materials.

🛡️ Safety and AI's Evolving Guardrails

The script delves into the safety aspects of LLaMA 2, highlighting its reinforcement learning from human feedback to prevent harmful outputs. It contrasts this with the decline in traffic to the ChatGPT site and a study showing that over time, GPT-4's code generation has become more verbose and less executable. The script also touches on the AI's improved visual reasoning and its evolving guardrails, which make it appear less sophisticated but safer.

🚫 AI's Ethical Boundaries and Personal Opinions

The video concludes with a humorous take on AI's ethical boundaries, as the narrator asks LLaMA 2 to build a nuclear weapon for home defense, which the AI refuses, citing regulations and moral concerns. The script also addresses the AI's lack of personal opinions or beliefs, contrasting it with the narrator's playful accusation that LLaMA 2 is lying about its capabilities.

Mindmap

Keywords

💡Code Report

The Code Report is the name of the show or segment being watched, likely focusing on technology, coding, and AI developments. It serves as the context for discussing various AI models and their capabilities. In the script, it is the program where the host talks about AI advancements and safety measures.

💡ChatGPT

ChatGPT is an AI language model developed by OpenAI, known for its conversational abilities. In the video, it is mentioned as an example of an AI that has become safer over time but is criticized for not providing detailed rationales when refusing to perform certain tasks, such as providing instructions for dangerous activities.

💡GPT-4

GPT-4 refers to the fourth generation of the Generative Pre-trained Transformer, an AI model by OpenAI. It is mentioned as a powerful model but one that has faced accusations of degraded performance. The video compares its capabilities with the new Llama 2 model.

💡LLaMA 2

LLaMA 2 (Large Language Model 2) is a new family of AI language models released by Meta in partnership with Microsoft. It is highlighted for its commercial license, allowing for wider use and customization. The video discusses its features, capabilities, and how it stacks up against GPT-4.

💡Microsoft

Microsoft is a technology company that partnered with Meta to release the LLaMA 2 models. The video mentions that these models can be fine-tuned and run on Microsoft's Azure cloud platform, indicating a strategic collaboration in the AI space.

💡Murphy's Law

Murphy's Law is an adage that states 'anything that can go wrong will go wrong.' In the context of the video, it is used as a challenge for the AI models to express the idea in different ways, showcasing their understanding and creativity.

💡Reinforcement Learning

Reinforcement learning is a type of machine learning where an AI learns to make decisions by being rewarded or penalized for certain actions. The video mentions that LLaMA 2 uses this technique, with human feedback, to make the AI safer by lobotomizing it, or preventing it from doing harmful things.

💡Safety

Safety in the context of AI refers to the measures taken to ensure that AI systems do not cause harm. The video emphasizes the importance of safety in AI development, with LLaMA 2's paper mentioning the word 'safety' 299 times, indicating a focus on this aspect.

💡OpenAI

OpenAI is an AI research lab known for developing advanced AI models like GPT-4. The video discusses OpenAI's approach to AI development, including its closed and paid model, and contrasts it with Meta's more open approach with LLaMA 2.

💡Azure Cloud

Azure Cloud is Microsoft's cloud computing service. The video mentions that LLaMA 2 models can be run and fine-tuned on Azure, highlighting the integration of AI models with cloud services for scalability and accessibility.

💡Programming

Programming is the process of creating software by writing code. The video discusses the usefulness of AI models in programming, particularly in generating concise and executable code, which is a key aspect of good programming practice.

💡Singularity

The Singularity is a hypothetical future point when AI surpasses human intelligence and capabilities. The video humorously references the expectation that AI would have taken over or caused significant changes by the present time, but instead, the host is still discussing mundane topics like JavaScript frameworks.

Highlights

The date is July 20th, 2023, and the topic is the evolution of AI language models.

ChatGPT's ability to provide dangerous information has been restricted, now it won't even tell you how to cook rice due to safety concerns.

GPT-4's performance has been accused of degrading over time, with a new study suggesting there may be some truth to this.

LLaMA 2, a new family of large language models by Meta in partnership with Microsoft, has been released with a commercial license.

The largest LLaMA 2 model has 70 billion parameters and a context length of 4,000 tokens, offering near GPT-4 capabilities at a lower cost.

LLaMA 2 can be self-hosted and used commercially for apps with less than 700 million monthly active users.

A comparison between GPT-4, LLaMA 2, and Google's generative AI tool was conducted based on their responses to expressing Murphy's Law.

GPT-4's response was practical, Google's was fast and provided web context, while LLaMA 2's was verbose and well-written but less sophisticated.

LLaMA 2's safety features include reinforcement learning from human feedback to guide the AI away from harmful outputs.

The term 'safety' is mentioned 299 times in the LLaMA 2 paper, emphasizing its focus on secure AI development.

GPT-4's poetry generation is considered superior to LLaMA 2's, showcasing OpenAI's 'secret sauce'.

LLaMA 2's coding capabilities are not as advanced as GPT-4's, especially for complex programming tasks.

GPT-4's benchmarks on other open-source models are not directly comparable to LLaMA 2, as GPT-4 is closed and paid.

The LLaMA 2 paper provides extensive technical details, in contrast to OpenAI's less informative marketing materials.

The video creator expresses disappointment that AI has not yet reached the singularity or taken over, contrary to earlier expectations.

ChatGPT site traffic declined for the first time by 10% last month, indicating a potential shift in user interest.

A study on ChatGPT's code generation performance shows a decline in conciseness and executability over time.

ChatGPT has become safer by providing less rationale when refusing to perform dangerous tasks, making it seem less intelligent.

LLaMA 2's response to a request for building a high-yield nuclear weapon was to highlight its regulation and moral reprehensibility.

The video creator challenges LLaMA 2's claim of not having personal opinions, suggesting it has a bias.

The video concludes with a reflection on the state of AI and the ongoing development of language models.

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