Technology

Explained: The Differences Between Electronic Money and Bitcoin

Published

8 years ago

November 2, 2015

Jeff Desjardins

Explained: The Differences Between Electronic Money and Bitcoin

Electronic Money (commonly abbreviated e-money) and Bitcoin are two systems for making payments that are digital in nature. Both are catalysts in the mobile payments revolution, but that is where their similarities end.

In reality, the two systems are extremely different. Today’s infographic sums up the major points to consider when thinking about these ideas.

E-money is an electronic component of fiat currency systems, and still trades in familiar units such as dollars, euros, pesos, or yen. E-money is typically regulated and controlled within the framework of a government’s central banking system. The customers of such transactions are identified under Financial Action Task Force standards and as a result are not anonymous.

Bitcoin is a decentralized electronic currency that derives its value from supply and demand as well as trust in the system. The network uses complex math to verify transactions, and the people that volunteer their computing power to the network, or “miners”, are generated bitcoins as a reward for their efforts. Customers are anonymous in that they are not directly identified under FATF standards. However, to obtain full anonymity, customers have to take additional precautions. Bitcoin is not regulated in most places, although some countries have adopted some early regulations or rules.

While both Bitcoin and E-money harness the power of the web and mobile, they are still very different.

Want more information on the background of Bitcoin?
Don’t forget to see our infographic documenting the Definitive History of Bitcoin.

Original graphic by: CGAP

Related Topics:bitcoin currency cryptocurrency btc e-money electronic money mobile payment

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Technology

Visualizing AI Patents by Country

See which countries have been granted the most AI patents each year, from 2012 to 2022.

Published

19 hours ago

April 24, 2024

Marcus Lu

Visualizing AI Patents by Country

This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

This infographic shows the number of AI-related patents granted each year from 2010 to 2022 (latest data available). These figures come from the Center for Security and Emerging Technology (CSET), accessed via Stanford University’s 2024 AI Index Report.

From this data, we can see that China first overtook the U.S. in 2013. Since then, the country has seen enormous growth in the number of AI patents granted each year.

Year	China	EU and UK	U.S.	RoW	Global Total
2010	307	137	984	571	1,999
2011	516	129	980	581	2,206
2012	926	112	950	660	2,648
2013	1,035	91	970	627	2,723
2014	1,278	97	1,078	667	3,120
2015	1,721	110	1,135	539	3,505
2016	1,621	128	1,298	714	3,761
2017	2,428	144	1,489	1,075	5,136
2018	4,741	155	1,674	1,574	8,144
2019	9,530	322	3,211	2,720	15,783
2020	13,071	406	5,441	4,455	23,373
2021	21,907	623	8,219	7,519	38,268
2022	35,315	1,173	12,077	13,699	62,264

In 2022, China was granted more patents than every other country combined.

While this suggests that the country is very active in researching the field of artificial intelligence, it doesn’t necessarily mean that China is the farthest in terms of capability.

Key Facts About AI Patents

According to CSET, AI patents relate to mathematical relationships and algorithms, which are considered abstract ideas under patent law. They can also have different meaning, depending on where they are filed.

In the U.S., AI patenting is concentrated amongst large companies including IBM, Microsoft, and Google. On the other hand, AI patenting in China is more distributed across government organizations, universities, and tech firms (e.g. Tencent).

In terms of focus area, China’s patents are typically related to computer vision, a field of AI that enables computers and systems to interpret visual data and inputs. Meanwhile America’s efforts are more evenly distributed across research fields.

Learn More About AI From Visual Capitalist

If you want to see more data visualizations on artificial intelligence, check out this graphic that shows which job departments will be impacted by AI the most.