There was a great comment on Reddit from someone who worked in the meat department that highlighted this comparison with specific examples but alas I am unable to find it.
There was a great comment on Reddit from someone who worked in the meat department that highlighted this comparison with specific examples but alas I am unable to find it.
I've been overly cautious of batteries for several years now, I charge my devices with 1A charger and keep it between 40% to 80% . I now carry a single 18650 cell power bank instead of those 10,000 mAh, 20,000mAh power banks.
I don't sleep with phone, tablet or kindle on bed and I force my partner to do the same to her irritation. Last week her MacBook became spicy overnight and I had to rush to Apple Store morning, the price for battery replacement was more than the price of that MacBook in used market so I had to buy a new MacBook.
I miss the good old days where I could take the battery of the Nokia phone and spin it on the table to see if it's become spicy. I pray to EU gods to please force the manufactures to bring back user replaceable batteries.
It feels like either finding that 2% that's off (or dealing with 2% error) will be the time consuming part in a lot of cases. I mean, this is nothing new with LLMs, but as these use cases encourage users to input more complex tasks, that are more integrated with our personal data (and at times money, as hinted at by all the "do task X and buy me Y" examples), "almost right" seems like it has the potential to cause a lot of headaches. Especially when the 2% error is subtle and buried in step 3 of 46 of some complex agentic flow.
"Hello, yes, I would like to pollute my entire data store" is an insane a sales pitch. Start backing up your data lakes on physical media, there is going to be an outrageous market for low-background data in the future.
semi-related: How many people are going to get killed because of this?
Myths programers believe about cars:
Cars in the same lane always travel in the same direction.
Each street has a name.
Each street has a unique name.
Each street has only one name.
Cars have four wheels.
Cars never move vertically.
Roads never move.
Roads never cross water without bridges.
When two roads cross, the do so at an intersection.
Take any field in human experience and one can make such a list.
All boats float. Ships are bigger than boats. Boats are slower than airplanes. Boats only travel on water.
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This type of cost-benefit analysis (or economic multiplier calculation) is also used to justify public subsidy of sports stadiums and the like. Unfortunately, these analyses always use overly optimistic assumptions, and fall victim to the broken windows fallacy.
What is the right way to frame it? Total cost per passenger mile might be good. The transit systems that move the most people efficiently would do well on that metric.
Sometimes basic science research funding is framed in terms of "this program generated $10 of economic activity for every dollar spent." Social programs sometimes measured this way too. The term for this escapes me at the moment, but I think it would be more useful?
And also,
> We’ll reach out to eligible users in the US and Canada for the Nest Learning Thermostat (4th gen) at a special price: $149.99 [219.99 CAD] (nearly 50% off).
However, we got a Nest from the Oregon Energy trust for $50 I think. So, not a great price.
Gotta juice those numbers before moving on to the next role.