Perplexity AI vs ChatGPT for Research - Who wins?

Summary

In this engaging comparison, the speaker evaluates ChatGPT and Perplexity across four key academic tasks: literature search, explaining research papers, data analysis, and academic writing. While ChatGPT excels in data analysis and academic writing, Perplexity outperforms in sourcing peer-reviewed literature and providing summaries. The analysis reveals that each tool has its strengths, with ChatGPT better suited for data tasks and Perplexity for academic searches. Ultimately, the speaker concludes that both tools have their unique advantages, making them complementary resources for researchers.

Takeaways

• 😀 ChatGPT and Perplexity were compared for academic tasks commonly performed by PhD students.
• 📚 Perplexity outperformed ChatGPT in recommending peer-reviewed papers for research projects.
• 🔍 Both platforms were tested on their ability to explain complex research papers.
• 📈 ChatGPT excelled in data analysis, successfully plotting IV curves and calculating efficiencies.
• 🤔 Perplexity attempted to enhance explanations by integrating additional relevant sources.
• ✍️ ChatGPT provided solid support for academic writing but lacked in referencing capabilities.
• 🔗 Perplexity offered some reference suggestions but sometimes misunderstood context.
• ⚖️ The comparison concluded that neither tool is superior overall; each has unique strengths.
• 💡 For literature searches, Perplexity is better, while ChatGPT is more effective for data analysis.
• 🤝 Users may benefit from utilizing both tools depending on their specific academic needs.

Q & A

What are the main tasks compared between ChatGPT and Perplexity?

The main tasks compared are finding literature, explaining research papers, performing data analysis, and writing/editing academic content.

How did ChatGPT perform in finding peer-reviewed papers for hydrogen production?

ChatGPT provided four relevant peer-reviewed papers, which were accurate but limited in number.

What advantage does Perplexity offer when searching for academic literature?

Perplexity can find a greater number of sources (20 in this case) and organizes them into sections with summaries, making it more effective for literature searches.

In what way did ChatGPT explain research papers?

ChatGPT structured its explanations into sections like introduction and results but was somewhat repetitive.

What was Perplexity's approach to explaining research papers?

Perplexity categorized key points and incorporated related research, providing a more comprehensive overview.

How did ChatGPT demonstrate its capabilities in data analysis?

ChatGPT successfully plotted an IV curve from the provided data and calculated the efficiency of the device, presenting interactive graphs.

What limitation did Perplexity have in the data analysis task?

Perplexity offered code for plotting but did not generate the graph itself and failed to calculate efficiency accurately.

What were the strengths of ChatGPT in writing and editing tasks?

ChatGPT improved the academic writing quality but removed references, focusing on enhancing the language used.

How did Perplexity perform in writing and editing tasks?

Perplexity attempted to improve the text and add references but misinterpreted the context, leading to incorrect citations.

What is the overall conclusion about using ChatGPT and Perplexity?

ChatGPT excels in data analysis and scientific writing, while Perplexity is better for literature searches and academic references, making it beneficial to use both depending on the specific need.