He was complaining about how he had hired his video projector out for a party, and it had come back with one of the lenses missing.
@I_Make_It_All One approach that i have found that works, is to work out how you can make a new tool pay for itself.
After that point, it's yours, free and clear. :)
He was complaining about how he had hired his video projector out for a party, and it had come back with one of the lenses missing.
This was his original reason for buying the machine.
He hadn't thought about it, so he started scribbling down some figures.
He didn't NEED to hire it out again.
He could afford to say No to annoying customers. :D
I'll find ways of making the hardware pay for itself, then after that it's mine to use as i wish. :D
Everything after that is a bonus. :D
Every machine i work on, should be able to pay for itself, and as long as that the time taken to do that, is a fraction of the machine's rated lifespan, then it's a profitable purchase. :D
It'll pay for itself in 24-36 months, but with maintenance, it'll last for 50 years. :D
Once the first 3 years are done, it's free for the next 47 years. :D
How long will it last?
How much does it cost?
How long till i make my original money back?
After that i don't need to hire it out. :D
More from Science
Hard agree. And if this is useful, let me share something that often gets omitted (not by @kakape).
Variants always emerge, & are not good or bad, but expected. The challenge is figuring out which variants are bad, and that can't be done with sequence alone.
You can't just look at a sequence and say, "Aha! A mutation in spike. This must be more transmissible or can evade antibody neutralization." Sure, we can use computational models to try and predict the functional consequence of a given mutation, but models are often wrong.
The virus acquires mutations randomly every time it replicates. Many mutations don't change the virus at all. Others may change it in a way that have no consequences for human transmission or disease. But you can't tell just looking at sequence alone.
In order to determine the functional impact of a mutation, you need to actually do experiments. You can look at some effects in cell culture, but to address questions relating to transmission or disease, you have to use animal models.
The reason people were concerned initially about B.1.1.7 is because of epidemiological evidence showing that it rapidly became dominant in one area. More rapidly that could be explained unless it had some kind of advantage that allowed it to outcompete other circulating variants.
Variants always emerge, & are not good or bad, but expected. The challenge is figuring out which variants are bad, and that can't be done with sequence alone.
Feels like the next thing we're going to need is a ranking system for how concerning "variants of concern\u201d actually are.
— Kai Kupferschmidt (@kakape) January 15, 2021
A lot of constellations of mutations are concerning, but people are lumping together variants with vastly different levels of evidence that we need to worry.
You can't just look at a sequence and say, "Aha! A mutation in spike. This must be more transmissible or can evade antibody neutralization." Sure, we can use computational models to try and predict the functional consequence of a given mutation, but models are often wrong.
The virus acquires mutations randomly every time it replicates. Many mutations don't change the virus at all. Others may change it in a way that have no consequences for human transmission or disease. But you can't tell just looking at sequence alone.
In order to determine the functional impact of a mutation, you need to actually do experiments. You can look at some effects in cell culture, but to address questions relating to transmission or disease, you have to use animal models.
The reason people were concerned initially about B.1.1.7 is because of epidemiological evidence showing that it rapidly became dominant in one area. More rapidly that could be explained unless it had some kind of advantage that allowed it to outcompete other circulating variants.
