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​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?

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.

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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