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The test compares the new Chat GP01 preview model from OpenAI against Chat GPT-4 using ten prompts. A custom GPT incorporates Chain of Thought prompting, designed to mirror Chat GPT-1's strengths. The evaluation examines performance in tasks like counting letters, answering logical questions, and coding challenges. Results indicate that Chat GP01 consistently outperformed GPT-4 and the custom models in various tasks, particularly in reasoning and coding accuracy. All models showed some improvements, but Chat GP01 emerged as the leading AI in the testing scenarios provided.
Introducing a comparison between Chat GP01 and Chat GPT-4 across ten prompts.
First task evaluates letter counting, with all models identifying three Rs in 'strawberry.'
Chat GP01 determined the marble was on the table, outperforming Chat GPT-4.
Coding test reveals Chat GP01 providing advanced chess game functionality.
Chat GP01 demonstrates significant progress, especially in coding tests.
The consistent performance of Chat GP01 across tasks indicates a potential evolution in AI behavioral modeling. Incorporating Chain of Thought prompting suggests an intentional alignment with human reasoning patterns, crucial for developing trust in AI interactions. As observed, the comparative performance showcases not just advancements in AI capabilities, but also highlights the importance of task complexity in evaluating AI intelligence.
The implications of AI performance, particularly in tasks involving logical reasoning, raise questions about accountability and functionality in real-world applications. With Chat GP01 outpacing previous models, it underscores the urgency for ethical governance as more advanced AI systems become integrated into daily operations. Ensuring transparent AI that aligns with societal norms will be critical as performance and capabilities expand.
It's applied to improve clarity and accuracy in responses.
The GPT-4 model exhibited this while discussing mango cultivars.
Both GPT models discussed are examples of LLMs.
OpenAI is known for its advancements in large language models, specifically the ChatGPT series mentioned in the video.
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Claude's output in this video highlights its current limitations in coding challenges.
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