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Joined 1 year ago
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Cake day: July 2nd, 2023

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  • When you’re just shy of a three trillion dollar company big jumps are harder. Plus with the stock up 15% for the month and up 56% for the year people’s, once balanced, portfolios are likely already overly committed to Microsoft based on how it’s performed this year. It’s hard to ignore a stock when it’s performing this well, this consistently, but it puts an investor in a precarious position. If you haven’t already invested based on the AI boom this year has brought, this wouldn’t have been a tipping point. It was a plus, but only a small plus comparatively. The shake up of OpenAI has much more potential for a big sell off for Microsoft than a buying frenzy. This was more silver lining on instability of a big bet Microsoft made.



  • The way companies do it is a lot of napkin math. I worked next to a team that built a service to help other companies figure this out (I provided the sample code and docs they share with customers for onboarding). You plug in some basic info, as an example this building used X kilowatt hours of electricity that the power company says is 10% coal and 90% hydro, which, based on a lookup table that means Y tons of CO2 emissions per hour, add X*Y to your total and move onto the next building. It’s not an exact science measuring actual emissions, more looking for ballpark numbers trying to get rough estimates based on what sustainability consortiums agree is the emission rates for certain things/activities/events. It doesn’t matter if your X is slightly more efficient than your neighbors X, because your maintenance guy is better, both will get the “X” rate for emissions based on the agreed upon value for the thing being measured. The idea is to capture as many things/activities/events as possible to get an estimate of emissions, not a measurement.