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nakedgrape

Re:Ask HN: What is your one tech prediction for 2018? on Sunday February 25, 2018 @11:33PM (#16463145)
Startup has been so overused at this point that has totally lost all its appeal. Anybody with a T-shirt with a logo has a startup. I once heard my landlord call her renting two of her spare rooms of her house a startup.

The other buzzwords I'd add in is "engineer" and "lab", though I don't see them going away anytime soon. Everybody's a bloody engineer, and every company is a lab. Grotesque.

Re:Ask HN: What is your one tech prediction for 2018? on Sunday February 25, 2018 @11:30PM (#16463133)
There will be more technology.
Anytime one makes an effort to become a better functioning member of society, provided the ROI works out, s/he's making him/herself more of an asset.

>Socially it has been challenging because of the time commitment. I'm not on the same schedule as everyone else and don’t fit anyone's model of what people do with their lives.

I've noticed the same, though age gap is less pronounced in my case. Different pond, different people, different conduct.

Re:Ask HN: How did you hack your home? on Sunday February 25, 2018 @05:16PM (#16461509)
Often the most overlooked hack.
Re:Canadian software engineers paid peanuts on Sunday February 25, 2018 @05:13PM (#16461498)
Hmm. I've seen these charts often but I have to say I've never met anyone get paid less than eighty. Myself and most of my peers at UBC start at about 90-110k for Google, Fb, Amazon and whatnot (only speaking for Vancouver).

My dad also worked in software back in the day in Toronto and he was also rarely less than 100k.

Lots of good ones on here.

I'm not particularly good at this either, but one thing that has helped occasionally is keeping multiple tasks running concurrently. With software, among other things, it's very easy to settle into a grove where I find myself getting too comfortable in solving particular problem. So to temper this effect, I switch tasks and work on something else every once in a while, kind of like skipping on a lily pads.

A machine learning equivalent is over-fitting. To not overfit is to not feed the brain too much of the same data or otherwise you end up needing to retrain / remove old memory from slots, depending on which metaphor you tend.

Ask HN: Defunct Startup, how to deal with investor, how to wind down?

I ran a US company and due to unforeseen circumstances, I was unable to return the country to raise an additional round of funding and the company collapsed.There is currently one angel investor at $150k, some debt holders ~$10k.I called the investor a year ago and said to him that I want to close down the company -- all the employees have left. We agreed that he'd try to solicit around the...

( Read More... | 1 comment | 2 points | on HN )