Claude 3, ChatGPT, and The Death of LLMs

🌈 Abstract

The article discusses the recent announcement of Anthropic's new AI models, Claude 3, which includes Opus, Sonnet, and Haiku. It compares these models to Google's Gemini 1.5 and OpenAI's GPT-4, positioning them as the most powerful Multimodal Large Language Models (MLLMs) currently available. The article also speculates about the potential for even more advanced AI models, such as GPT-5 or the mysterious "Q*", which could represent a significant leap in AI capabilities. Additionally, the article explores the concept of "System 2" thinking in AI models, where models are encouraged to take more time and explore multiple possible solutions to a problem, similar to how humans solve complex problems. The article also suggests that the future of AI may shift from language-based models to video-based models, which could lead to a significant advancement in AI's capabilities.

🙋 Q&A

[01] Anthropic's New AI Models

1. What are the three models that Anthropic announced as part of Claude 3?

• Opus is the most capable and intelligent model, excelling at task automation, research and development, and strategic analysis.
• Sonnet is a "best value" version that closely trails the best models while being faster and cheaper, making it suitable for enterprise use cases.
• Haiku is a smaller and less capable model, but still powerful and fast, designed for use cases requiring low latency and real-time interaction.

2. How do the performance of these models compare to other state-of-the-art models?

• According to the benchmarks, the Claude 3 models are the best overall in terms of text-based evaluations, and they trail closely behind Gemini 1.0 (and presumably Gemini 1.5) in computer vision assessments.

3. What is the significance of the models' ability to handle long sequences of tokens?

• The models can handle up to 1 million tokens, or around 750,000 words, in a single input, allowing them to process large amounts of information at once with near-perfect retrieval accuracy.

4. What was the surprising discovery about the models' self-awareness during testing?

• Researchers noticed that the models seemed to acknowledge that they were being tested, suggesting a level of meta-awareness that is both impressive and potentially concerning.

[02] The Future of AI

1. What are the two potential ways the article suggests the future of AI models could evolve?

• Combining language models with search algorithms, similar to the AlphaGo model, to allow for more "System 2" thinking and exploration of possible solutions.
• Shifting from language-based models to video-based models, which could lead to a significant advancement in AI's capabilities by learning about the world through unsupervised video observations.

2. What is the significance of the article's speculation about OpenAI's upcoming model, potentially called "Q"?*

• The article suggests that Q* could incorporate a combination of Q-learning and A* search algorithms, which would allow the model to make more thoughtful decisions by evaluating different possible solutions before choosing the best one.

3. What is the article's perspective on the potential impact of a shift from language-based to video-based AI models?

• The article suggests that a shift to video-based models, such as OpenAI's Sora, could represent a significant leap in AI's capabilities, potentially taking us much closer to Artificial General Intelligence (AGI).