Artificial intelligence (AI) has become indispensable for extracting meaningful insights from complex datasets in the ever-evolving realm of data science. YouTube content creator and AI enthusiast Andy Stapleton recently delved into the capabilities of three prominent AI tools—Julius AI, Vizly, and the latest version of ChatGPT. His goal was to determine which tool excels in data analysis and to understand their limitations. Here’s what he discovered.

The Experiment Begins

Stapleton began his experiment with a straightforward dataset: public healthcare data. He input the same data into each AI tool and issued the same prompt: “This is public healthcare data. Provide some insights into what this data shows, including graphs or other visualizations that you think will help.”

Julius AI was the first to be tested. It quickly generated Python code to analyze the dataset, producing visualizations that included the distribution of hospital codes, admission types, severity of illness, and lengths of stay. “Julius AI provided a comprehensive initial analysis,” Stapleton noted. “It’s clear that it’s capable of handling large datasets and generating useful insights efficiently.”

Comparing the Tools

Next, Stapleton tested Vizly with the same dataset and prompt. Vizly produced similar visualizations but offered a unique summary of the public healthcare data analysis. “Vizly chose slightly different parameters for its analysis,” Stapleton observed. “One notable feature was its interactive graphs, which allow users to hover over data points for additional information.”

Finally, Stapleton turned to ChatGPT’s latest version. ChatGPT not only generated visualizations but also provided an analysis plan and interactive graphs. “The interactivity of ChatGPT’s visualizations sets it apart,” Stapleton said. “You can explore the data in a more dynamic way, which is incredibly valuable for deeper analysis.”

Diving Deeper

Stapleton then asked each tool to provide a breakdown of the distribution of hospital stays by duration. All three tools performed admirably, but Vizly’s interactive capabilities again stood out. “Vizly’s graph was the most user-friendly,” Stapleton remarked. “It allowed for zooming and detailed exploration of the data.”

For his next test, Stapleton introduced a more challenging dataset from his PhD research on organic photovoltaic (OPV) devices. This dataset was unstructured, containing metadata and raw data. Julius AI impressed by correctly identifying and plotting the IV curve of the OPV device, despite the complexity of the data. “Julius AI’s ability to self-correct and find the necessary data was impressive,” Stapleton said.

Vizly struggled initially but eventually managed to identify the IV curve data after several attempts. ChatGPT, however, quickly processed the unstructured data and accurately plotted the IV curve, even calculating the efficiency of the OPV device. “ChatGPT’s reasoning capabilities are superior,” Stapleton concluded. “It can handle complex datasets with ease.”

Testing the Limits

To push the boundaries further, Stapleton tested the AI tools with an image of silver nanowires and single-walled carbon nanotubes. Julius AI and Vizly both attempted edge detection but provided varying results. ChatGPT, while unable to directly measure the nanowires’ diameter, offered valuable guidance on using other tools like ImageJ for precise measurement. “ChatGPT’s ability to provide actionable advice is a significant advantage,” Stapleton noted.

Final Thoughts

After extensive testing, Stapleton found that both Julius AI and ChatGPT stood out as the most effective tools for data analysis. “For anyone working with large and complex datasets, Julius AI and ChatGPT are invaluable,” he said. “They complement each other perfectly, making data analysis more accessible and efficient than ever before.”

Stapleton’s deep dive into AI tools for data analysis highlights the transformative potential of these technologies. As AI continues to advance, tools like Julius AI, Vizly, and ChatGPT will play a crucial role in helping researchers, analysts, and businesses unlock new insights from their data.