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2 minute read / Oct 29, 2024 /

My AI Rube Goldberg Machine

In yesterday’s post, I calculated the profitability of public software companies. To calculate these figures, I built a little Rube Goldberg machine.

I didn’t download the data into Excel. Instead, I complexified things by sending the analysis to 4 AIs to see if they would agree.

The inspiration : many companies have used Amazon’s Mechanical Turk to crowdsource tasks, & pick a consensus answer across three workers to improve accuracy.

Why not try this across 4 AI workers instead?

4 robots with flags Prompt : “calculate the average net income margin and cash flow from ops margin from this data set” plus the data set. Note that CFOM isn’t a simple average but requires dividing cash flow from ops by revenue beforehand.

Model NIM, % CFOM, %
Claude 4.99 27.31
Gemini -9.29 16.2
Perplexity -8.67 14.4
ChatGPT - 9.29 1,433.01. / 14.9%
My Analysis -9.29 16.2

Gemini scored top marks for tabulating correctly on both columns. ChatGPT did well with NIM but “forgot” to complete the additional division step, which I corrected with a follow up, but still not the right figure. The other systems missed the mark altogether.

It would be a mistake to draw any broad conclusions from my little experiment.

But in this case, consensus doesn’t yet work as a strategy which means I still need to double check calculations myself.

At some point, AI will mechanize the illusory Mechanical Turk & I’ll restart my Rube Goldberg math machine with confidence.


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