Posts Tagged ‘networks’
“Cash is king”*…
“The king is dead, long live the king” Nick Routley on the replacement of cash by digital payment…
As credit cards and digital wallets (e.g. Apple Pay, Paytm, Alipay) see increasing adoption around the world, the share of cash being used in transactions is plummeting.
The chart above looks at cash as a share of transaction value in selected countries at three time periods (2019, 2023, and 2027P). Highlighted in red is cash’s projected drop from 2019 to 2027. This data showing the death of cash comes from WorldPay’s Global Payments Report 2024.
The prominence of cash for use in transactions is dropping in every country measured. This includes countries where cash was preferential method of payment in POS transactions.
One clear example is Nigeria. In 2019, over 90% of transaction value was still in cash payments. That number has now fallen to 55% today. Cash is still the leading payment method in Nigeria and a handful of other nations, but current trends indicate this may not be the case for much longer. For now, cash also remains the leading method of payment in various South American and East Asian countries…
All that is solid melts into air: “Charted: The Death of Cash Transactions Around the World,” from @NickRoutley in @VisualCap.
For more: “What is a cashless society, and what does it mean for businesses?“
And for a consideration of the pros and cons: “Should We Become a Cashless Society?“
Also apposite: “Target said that due to ‘extremely low volumes,’ it would no longer take personal checks.”
* Modern saying, summarizing the position in a recession
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As we click, we might recall that it was on this date in 2001 THAT The Code Red worm was released onto the Internet. Targeting Microsoft’s IIS web server, Code Red had a significant effect on the Internet via the speed and efficiency of its spread. Much of this was due to the fact that IIS was often enabled by default on many installations of Windows NT and Windows 2000. But Code Red also affected many other systems with web servers, mostly by way of side-effect, exacerbating the overall impact of the worm.

“Man is not disturbed by events, but by the view he takes of them”*…
From Stripe Partners, a framework for rethinking the way we talk about the AI future…
AI is both a new technology and a new type of technology. It is the first technology that learns and that has the potential to outstrip its makers’ capabilities and develop independently.
As Large Language Models bring to life the realities of AI’s potential to operate at unprecedented, ‘human’ levels of sophistication, projections about its future have gained urgency. The dominant framework being applied to identify AI’s potential futures is 165 years old: Charles Darwin’s theory of evolution.
Darwin’s evolutionary framework is rendered most clearly in Dan Hendycks work for the Center for AI Safety which posits a future where natural selection could cause the most influential future AI agents to have selfish tendencies that might see AI’s favour their own agendas over the safety of humankind.
The choice of Natural Selection as a framework makes sense given AI’s emerging status as a quasi-sentient, highly adaptive technology that can learn and grow. The choice is a response to the limitations inherent in existing models for technological adoption which treat technologies as inert tools that only come to life when used by people.
The risk in applying this lens to AI is that it goes too far in assigning independent agency to AI. Estimates on the timing of the emergence of ‘Artificial General Intelligence’ vary, but spending some time with the current crop of Generative AI platforms confirms the view that AI’s with intelligences that are closer to humans are some way off. In the interim using natural selection as a lens to understand AI positions humans as further out of the developmental loop than is actually the case. Competitive forces whether market or military will shape AI’s development, but these will not be the only forces at play and direct interaction with humans will be the principal driver for AI’s progress in the near term.
A year ago we wrote about the opportunity to reframe the impact of AI on organisations through the lens of Actor Network Theory (ANT). More than a singular theory, ANT describes an approach to studying social and technological systems developed by Bruno Latour, Michel Callon, Madeleine Akrich and John Law in the early 1980s.
ANT posits that the social and natural world is best understood as dynamic networks of humans and nonhuman actors… In our 2023 piece we suggested that ANT, with its focus on framing society and human-technology interactions in terms of dynamic networks where every actor whether human or machine impacts the network, was a useful way of exploring the ways in which AI will impact people, and people will impact AI.
A year on the value of ANT as a framework for exploring AI’s future has become clearer. The critical point when comparing an ANT frame to an evolutionary one is the way in which the ANT framing highlights how AI will progress with and through people’s interactions with it. When viewed as an actor in a network, not a technology in isolation, AI will never be separate from human interventions…
A provocative argument, well worth reading in full: “Why the debate about the future of AI needs less Darwin and more Latour,” from @stripepartners.
Apposite: “Whose risks? Whose benefits?” from Mandy Brown.
* Epictetus
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As we reframe, we might recall that it was on this date in 1946 that an ancestor of today’s AIs, the ENIAC (Electronic Numerical Integrator And Computer), was first demonstrated in operation. (It was announced to the public the following day.) The first general-purpose computer (Turing-complete, digital, and capable of being programmed and re-programmed to solve different problems), ENIAC was begun in 1943, as part of the U.S’s war effort (as a classified military project known as “Project PX“); it was conceived and designed by John Mauchly and Presper Eckert of the University of Pennsylvania, where it was built. The finished machine, composed of 17,468 electronic vacuum tubes, 7,200 crystal diodes, 1,500 relays, 70,000 resistors, 10,000 capacitors and around 5 million hand-soldered joints, weighed more than 27 tons and occupied a 30 x 50 foot room– in its time the largest single electronic apparatus in the world. ENIAC’s basic clock speed was 100,000 cycles per second (or Hertz). Today’s home computers have clock speeds of 3,500,000,000 cycles per second or more.

“Men, it has been well said, think in herds; it will be seen that they go mad in herds, while they only recover their senses slowly, one by one”*…

You’ve probably heard of the wisdom of crowds. The general idea, popularized by James Surowiecki’s book, is that a large group of non-experts can solve problems collectively better than a single expert. As you can imagine, there are a lot of subtleties and complexities to this idea. Nicky Case helps you understand with a game.
Draw networks, run simulations, and learn in the process…
Spend an extremely-fruitful half hour with “The Wisdom and/or Madness of Crowds.”
[via Flowing Data]
Extraordinary Popular Delusions and the Madness of Crowds
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As we contemplate connection, we might compose a birthday rhyme for Torquato Tasso, the 16th Century Italian poet; he was born on this date in 1544. Tasso was a giant in his own time– he died in 1595, a few days before the Pope was to crown him “King of the Poets”– but had fallen out the core of the Western Canon by the end of the 19th century. Still, he resonates in the poems (Spencer, Milton, Byron), plays (Goethe), madrigals (Monteverdi), operas (Lully, Vivaldi, Handel, Haydn, Rossini, Dvorak) , and art work (Tintoretto, the Carracci, Guercino, Pietro da Cortona, Domenichino, Van Dyck, Poussin, Claude Lorrain, Tiepolo, Fragonard, Delacroix) that his life and work inspired.






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