If an employer is willing to be abusive to you prior to hiring you, when you have maximum leverage and they are maximally incentivized to play nice, I think that gives you *extremely actionable* signal as to how they'll treat you when you're working there and dependent on them.
For startups employing e.g. engineers: given that your candidates should evaluate you accordingly, be *extra special* careful to operate like professionals with regards to e.g. interviewing, offers, and negotiation.
Not without violating a confidence, but as someone who has been on hiring side of table and is a capitalist, there are *clearly* things you could do which would be "sharp operating, but we're all sharp operators" in some contexts.
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Here's their CFO describing their agreement (which we know from other litigation was never contractualized because, presumably because money launderers hate paper trails):
Bitfinex's CFO was shocked, shocked to learn that the money launderer they engaged to provide money laundering services while I-swear-to-God-this-is-an-actual-quote "we learned to bank like criminals" may have from time to time lied to banks.
"Institutional constraints" means, here, "We were attempting to avoid velocity checks placed by our banking partners to detect fraud and money laundering, which would have detected our fraud and money laundering."
Money at the speed of code, yadda yadda yadda, the Bitcoin economy is surprisingly blasé when several hundred million dollars is in an interstitial state for months.
In a situation never before encountered by a financial institution: the check was not, in fact, in the mail.
If everyone was holding bitcoin on the old x86 in their parents basement, we would be finding a price bottom. The problem is the risk is all pooled at a few brokerages and a network of rotten exchanges with counter party risk that makes AIG circa 2008 look like a good credit.— Greg Wester (@gwestr) November 25, 2018
The benign product is sovereign programmable money, which is historically a niche interest of folks with a relatively clustered set of beliefs about the state, the literary merit of Snow Crash, and the utility of gold to the modern economy.
This product has narrow appeal and, accordingly, is worth about as much as everything else on a 486 sitting in someone's basement is worth.
The other product is investment scams, which have approximately the best product market fit of anything produced by humans. In no age, in no country, in no city, at no level of sophistication do people consistently say "Actually I would prefer not to get money for nothing."
This product needs the exchanges like they need oxygen, because the value of it is directly tied to having payment rails to move real currency into the ecosystem and some jurisdictional and regulatory legerdemain to stay one step ahead of the banhammer.
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Below a list of business/product ideas I had or read about.
They are worthless if they remain ideas and if you don't overcome the challenges in building them, so feel free to copy / tweak / implement them!
Better: use one and make a MVP during the #24hrstartup challenge!
😻 Product Hunt Time
A clock that displays the time it is @ProductHunt
Also displays what you should do and where you should post, at each specific time during your launch
🚧 IndieCrunch - VC free tech news
Techcrunch but only for bootstrapped companies
🎧 Kickstarter for audiobooks
A lot of awesome books are not available as audio.
Crowdfund the money to buy the audio rights + a voice actor
Yahoo, who bought Tumblr years ago, used to have a huge adult presence on the early net. They allowed adult groups and what not.
However, people and bots (just like now) misused the service, and Yahoo were forced to make a choice. They made private the groups (and later closed them down and sold some of it to other companies) and then ended their chatrooms on yahoo messenger...
after a incident with one of the chatrooms vid cams. The damage was done, Yahoo Messenger lost a lot of people - and with the closing of the groups - backpage and Craigslist came more important.
Now backpage is no more and Craigslist is slowly passing away. Tumblr had a semi strong community, but once 2014 came around and both porn, and political bots exploded the quality started to go down,
I really, *really* like SoJ's "would not use again" question, which lets people who've abandoned a tech self-identify. This is noticeable in the graph above with Flow users -- 41% of people who've used Flow say they wouldn't use it again.
React 65% (vs. 60%)
Vue 29% (vs. 24%)
Ember 5% (vs 4%, I was expecting a bigger rise)
But there's a shocker in here: Angular.
npm's survey had Angular at 40% last year and SoJ has it at either:
- 58% (if you include those who don't want to use it again)
- 24% (if you count only those who like it)
Since npm's question didn't ask if they intend to *continue* using it I think that might explain this.
The paper is a good example of lots of elements of good experimental design. They validate their metric by showing lots of variants give consistent results. They tune hyperparamters separately for each condition, check that optimum isn't at the endpoints, and measure sensitivity.
They have separate experiments where the hold fixed # iterations and # epochs, which (as they explain) measure very different things. They avoid confounds, such as batch norm's artificial dependence between batch size and regularization strength.
When the experiments are done carefully enough, the results are remarkably consistent between different datasets and architectures. Qualitatively, MNIST behaves just like ImageNet.
Importantly, they don't find any evidence for a "sharp/flat optima" effect whereby better optimization leads to worse final results. They have a good discussion of experimental artifacts/confounds in past papers where such effects were reported.