34 karma · joined October 19, 2017
From the comment below, it sounds like maybe an Apple-like strategy to build off open source but charge for the resulting product? Either way, I would not feel comfortable recommending this product.
It's not clear if doing this in-house, or closely monitoring the state of the art and then buying a company that develops a winner, is superior.
This is based on the complete abhorrence of "scope creep" mixed with near total surveillance and control over the use of force. Those with that much power should not be able to enforce social mores, even if they reflect the will of the people at the time.
Source: https://en.wikipedia.org/wiki/Voter_turnout_in_the_United_St...
> So now we have driverless cars effectively classified as emergency ambulances - so assuming the CARNOC is paying attention, they then drive the car to the hospital - and have to have a mechanism to contact said hospital
> Imagine the healthcare implications where if someone hasa seizure, ODs, cardiac, etc... what is the response time from the CARNOC, and getting them to a hospital ==> then what types of lawsuits will these companies see? what type of insurance will they require?
The comparison is useful because all of the above scenarios are possible in the Danish rail system.
Would you help me understand why the scene was so important for you?
I've seen about 20 cents per word, making a 2k word longform around $400. Is that somewhat realistic?
For some $N MRR (magic point where you look for scalable channels), N should be large enough that you have a product that your market wants and will pay for, and the market is large enough that you were able to manually scale it to N.
The heuristic is something like "if you can get big enough doing low-efficiency/manual marketing, you've likely gotten close enough to the important things* and can move on to testing scalability".
* things like product/market fit, market size, clear communication, well defined value prop, etc.
https://www.numbeo.com/cost-of-living/compare_cities.jsp?cou...
Nobody I know is a Twilio engineer, but nearly every backend developer I've worked with has, or wants to use, Twilio. There's something old school phreaking about using a computer to control phone systems.
They seem to believe that the market is very broad, occasionally deep (Uber was ~10% of their usage), and super cool. They haven't gotten so big to discard their focus yet playful roots (their hackathon outreach is a great example; that's where I first learned the API).
My point was more about OP's presentation of why they could not participate. It's pretty clear they're an edge case in an edge case industry -- I cannot judge a large company being risk averse when there is no incentive for them to take on the risk.
(That said, if anyone solves cannabis banking, they are going to be a unicorn.)
[0] http://edoceo.com/blog/2017/04/stripe-rubbing-salt-in-the-wo...
I'm happy you found something that works for you, but the certainty you ascribe to causes is not justified by the evidence.
* most people I talk with are only vaguely aware there are issues at Uber, including many drivers, Uber users, and non-Uber users.
A long commute is something he identifies as always a negative. Humans don't seem to adjust to a long commute -- it will always negatively impact the typical person's outlook/affect/happiness.
Taleb's Black Swan concept is that unpredictable events happen more frequently than people expect, and have an outsized impact on the outcomes of a model. Events that are not predictable are not included in the predictive model. Take the frequency of event and exclusion from the model, add in asymmetric results (small changes to input parameters can lead to huge changes in outcome), and that's his theory.
Is that accurate? What are the issues with that?