GPT-4.5 is an improved version of GPT-4, with enhancements in computational efficiency but not necessarily in predictive capabilities for chemical reactions. While GPT-4 has demonstrated impressive abilities in predicting chemical properties and outcomes through few-shot learning, its performance in predicting the outcomes of unknown chemical reactions is based on its vast knowledge base and inferencing capabilities[1][2]. GPT-4 can predict properties like redox potentials and boiling points using limited data, which is a significant advancement over traditional methods[1][2].
However, GPT-4's accuracy in predicting complex chemical reactions, especially those involving specialized or novel compounds, can be limited by the quality and quantity of its training data[2]. For tasks requiring precise understanding of molecular structures and reaction mechanisms, such as retrosynthesis, traditional machine learning models might still outperform LLMs like GPT-4[5].
GPT-4.5, being more computationally efficient, might facilitate faster processing and analysis of chemical data, but there is no direct evidence that it significantly improves the accuracy of predicting unknown chemical reactions compared to GPT-4. The key factor in improving predictive accuracy would likely be enhancements in the model's knowledge base or the development of more sophisticated prompting strategies, such as the Ordered-and-Structured Chain of Thought (OSCoT) approach, which has shown promising results with GPT-4[4].
In summary, while GPT-4.5 offers improvements in efficiency, its ability to predict the outcomes of unknown chemical reactions more accurately than GPT-4 would depend on advancements in its underlying knowledge or the application of advanced prompting strategies rather than the efficiency improvements alone.
Citations:
[1] https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/647d305dbe16ad5c577b6627/original/prompt-engineering-of-gpt-4-for-chemical-research-what-can-cannot-be-done.pdf
[2] https://ai-scholar.tech/en/articles/large-language-models/prompt-chemical-research
[3] http://arxiv.org/pdf/2311.07361.pdf
[4] https://pmc.ncbi.nlm.nih.gov/articles/PMC10960113/
[5] https://arxiv.org/html/2407.15141v1
[6] https://cdn.openai.com/gpt-4-5-system-card.pdf
[7] https://www.tandfonline.com/doi/full/10.1080/27660400.2023.2260300
[8] https://www.reddit.com/r/singularity/comments/1iqzgmg/chatgpt_45_5_predictions/