A library of snippets
So here’s a really interesting problem that perhaps new technology might be able to help with. The problem is this: how do you have a fair lottery that allows the winner to remain anonymous?
This is a genuine problem. Look at the lucky chap who just won $160 MILLION DOLLARS in a Jamaican lottery. He turned up to collect his CHEQUE (hardly the best way to keep his identity secret – I really doubt it was made out to “cash”) dressed in a cloak and a “Scream” mask for fear of being identified.
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Both houses of the New Jersey state legislature passed the bill Thursday, leaving only Gov. Phil Murphy to decide whether businesses must still accept cash payments.
From Bill outlawing ‘cashless’ businesses passes New Jersey legislators | PhillyVoice.
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“There’s a lot of restaurants and other businesses that want to go cashless,” said John Longstreet, president and CEO of the Pennsylvania Restaurant and Lodging Association. He said he sees an upside to going cashless.
“Because places that handle cash are less safe than those that don’t have cash on hand. Everything is reported directly into the accounting system, taxes are paid. Whereas in a cash society, taxes aren’t always paid,” Longstreet added. “And consumers are getting used to it too. And they’re asking for it.”
From Cashless trend worries lawmakers: “If it’s not discrimination, it’s elitism” – CBS News.
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It’s well understood that shops that accept bitcoin are really trying to segment the market and get a more affluent tech savvy crowd just to come in and shop but they really don’t want to spend bitcoin, they just want those people to enter the premises.”
From Who uses the bitcoin ATMs popping up at delis across the U.S.?.
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A former Walmart executive said shopper theft was a major reason why the company killed Scan & Go, a cashierless-checkout technology, several months after expanding it to more than 100 stores.
From Ex-Walmart exec says theft helped kill Walmart’s cashierless tech – Business Insider.
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It’s not just a deteriorating Moore’s Law. The other driver toward specialized processors is a new set of applications that are not amenable to general-purpose computing. For starters, you have platforms like mobile devices and the internet of things (IoT) that are so demanding with regard to energy efficiency and cost, and are deployed in such large volumes, that they necessitated customized chips even with a relatively robust Moore’s Law in place. Lower-volume applications with even more stringent requirements, such as in military and aviation hardware, are also conducive to special-purpose designs. But the authors believe the real watershed moment for the industry is being enabled by deep learning, an application category that cuts across nearly every computing environment – mobile, desktop, embedded, cloud, and supercomputing.
Deep learning and its preferred hardware platform, GPUs, represent the most visible example of how computing may travel down the path from general-purpose to specialized processors.
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“the main source of electoral fraud in the UK is not personation at the polling station but fraudulently-completed postal ballots, a situation that led one British judge to call it ‘a system that would disgrace a banana republic’.”
From “Voter ID is back, and this time it’s in Woking – 15Mb”.
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“Using a difference-in-differences design on a 1.3-billion-observations panel, we find the laws have no negative effect on registration or turnout, overall or for any group defined by race, gender, age, or party affiliation. These results hold through a large number of specifications and cannot be attributed to mobilization against the laws, measured by campaign contributions and self-reported political engagement. ID requirements have no effect on fraud either – actual or perceived. Overall, our results suggest that efforts to reform voter ID laws may not have much impact on elections.”
From “Strict ID Laws Don’t Stop Voters: Evidence from a U.S. Nationwide Panel – Marginal REVOLUTION”.
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“In the latest research, 29% of adults don’t use any cash for weekly purchases, up from 24% in 2015. Those consumers who claim that they still make all or nearly all purchases for cash fell to 18%, versus 24% in 2015.”
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In line with the Taskforce, we have categorised cryptoassets into three types of tokens;
Exchange tokens: these are not issued or backed by any central authority and are intended and designed to be used as a means of exchange. They are, usually, a decentralised tool for buying and selling goods and services without traditional intermediaries. These tokens are usually outside the perimeter. These are what I like of as “money-like” digital assets and I have expanded my discussion of these in the revised paperback edition of my book “Before Bablyon, Beyond Bitcoin” that will be published in a couple of months.
Security tokens: these are tokens with specific characteristics that mean they meet the definition of a Specified Investment like a share or a debt instrument (described in more detail in Chapter 3) as set out in the RAO, and are within the perimeter. Given the combined demands of investor protection and “system” protection, I think we are some way from seeing these in the mass market but the idea of properly-regulated “ICO” structures has a logic to it.
Utility tokens: these tokens grant holders access to a current or prospective product or service but do not grant holders rights that are the same as those granted by Specified Investments. Although utility tokens are not Specified Investments, they might meet the definition of e-money in certain circumstances (as could other tokens), in which case activities in relation to them may be within the perimeter. I can envisage private currencies (the “IBM Dollar”, for want of a better bumper sticker) that use this technology but I don’t see them becoming e-money because the e-money regulations as they stand effectively describe e-money as being issued against a 100% reserve rather than future delivery, if you see what I mean. I must ask someone more knowledgeable then I am about this distinction.
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Snippings