It has already been three months since I last checked the ICO scene. At the time, I suggested ICOs were probably slowing down. New data seems to confirm this but all points to other trends not detected before. Figure 1 presents the latest data
ending on 31 May. 159 ICOs were successfully completed between March and May raising over 4 billion dollars. The data includes the Telegram wh.ich collected over 1.7 billion dollars in spite of not holding a public ICO phase. Telegram can indeed be seen as a statistical “outlier” making last April the most successful month ever. Note that the number of successful ICOs did not increase overall. March matched February with 57 ICO but was much more skinny regarding resources. April and May are fatter but do not exceed the number of ICOs of the previous
Most cryptocurrencies are now over 60% down from their December 2017 peak. While prices are still quite volatile, the trend for the last five months is decidedly downwards. While some still expect a recovery to the glorious days of last year, others see overvaluation all around accompanied by a financial bubble about to burst. Comparisons to the good old dot-com boom and subsequent crash of 20 years ago are cited as empirical evidence of what is coming.
Indeed, the current blockchain boom has similarities with the previous one. But there are also some fundamental differences springing from by the very nature of what we can call the blockchain economy. The first one is the marriage between technology and finance. Not that in the past the financial sector refused to use new technologies.
Blockchain mining cannot catch a break when it comes to environmental sustainability. This is especially true for Bitcoin mining which seemingly has an insatiable appetite for electricity. A recent paper suggests that by 2020 Bitcoin mining will consume as much energy as Australia. While these estimates are not exempt from criticism, mining does not appear to be best friends with sustainable development, at least not for now. An alternative way to look at this issue is to compare Bitcoin’s mining power use to that of cloud-based providers who have now become well-established tech corporations. Such comparison should be made not only in absolute terms (gigawatts) but also in relative fashion by considering, for example, the total population being served by these platforms and networks.
The post-WWII era can be arguably defined as the golden age of democratic capitalism – at least from the perspective of developed or industrialized countries. Rebuilding Europe and pumping capital into Japan triggered a long economic boom that lasted until the 1980s – notwithstanding the infamous 1973 oil crisis. The fall of the Berlin Wall in 1989 opened new markets to capital investment and recruited new members to the democracy club thus providing a much needed second wind to the then declining golden age. During that same period, democracy, defined narrowly, continuously expanded in developing countries, including those that became independent nations in the 1960/70s. By the end of the last Millennium analysts and observers were openly speaking about the third wave of democratization,
Disruptive. One of the attributes that most use to describe in minimalistic terms the potential impact of new and emerging information and communication technologies (ICTs) in society. While its actual meaning can vary from one person to another, disruption is usually linked to dramatic short-term change where old and obsolete technologies, processes and institutions -not to mention people – will be either replaced or purge altogether, all for the best.
Disruption is thus implicitly connected to the concept of progress, especially to its linear version. Here, progress is seen almost like time is in physics: it always goes forward, and it is impossible to go back and say edit the past. Recent research has challenged the linear conception of progress((See for example Amy Allen’s book, The
Many observers seem to assume blockchain technology is an immovable monolith. While such assumption does help when trying to explain how the technology works to the general public, this is indeed not the case when it comes to describing the actual status of the technology.
Rapid and agile innovation is one of the core traits of blockchains, backed by impressive human talent with substantial financial resources, addressing not only some of its well-known limitations but also enhancing its core functionality. Blockchain technology is evolving rapidly and the best way to take stock, for now, it’s via frequent snapshots. In fact, keeping track of blockchain innovations could quickly become a full-time job. In any event, the monolith is not only moving. It is indeed flying at the speed of light.
Open source is one of the core traits of blockchain technology propelling its rapid adoption and growth. The source code from the most popular platforms such as Bitcoin, Ethereum, and Hyperledger Fabric is freely available for download by anyone who wants to play with the technology. Granted, users wishing to deploy and use these platforms must have the required technical skills. While average Internet users might not have such capabilities, companies and startups can find internal capacity or hie external expertise to run and manage their preferred blockchain platform.
Free and Open Source Software (FOSS) has been around for almost three decades. Back in the late 1990s, a war of sorts between FOSS and proprietary software commenced, attracting lots of media attention and generating plenty
In the previous post, I detailed some issues that could help explain in part the gender-equality STEM paradox.
These can be summarized as follows:
- The Global Gender Gap Index (GGGI) measures gaps not levels. It is thus a relative indicator that takes stock of the gender gap regardless of the level or depth of development.
- The four GGGI subindices cannot be larger than 1. Thus, the GGGI does not factor-in cases where women are ahead of men. This is related to the previous point: the aim is to measure gender gaps, not gender levels.
- As of 2015, UNESCO STEM data is only available for 59 of the 144 countries included in GGGI. That is, almost 60% of the states are missing in the analysis of the gender-equality STEM paradox. Many low-income and lower-middle income countries
ICO data for last February is now available and shown in Figure 1 below.
We can immediately see that both the number of ICOs and the total investment volume has decreased. The latter, which amounted to 1.2 billion USD for the month, is 20 percent less than the total for January this year. The same goes for completed ICOs which decreased 21 percent. Among them, only one ICO surpassed 100 million dollars, reaching 150 million. And it managed to distance itself from the runner-up by a cool 100 million.
Figure 2 confirms the decline in total monthly investment but shows that the median declined only slightly or about 1.2%.
Even so, the median investment per ICO is still above 16 million dollars.((The average is much higher but probably not significant as the statistical distribution
A paper on the subject published a couple of weeks ago in the academic journal Psychological Science attracted plenty of attention thanks to some of its surprising conclusions. Its main finding is that, contrary to all expectations, there is an inverse relation between gender equality and the number of women that graduate in Science, Technology, Engineering and Science (STEM). That is, higher gender-equality is correlated to lower female graduation rates in STEM. And vice-versa. How can this be?
In this post, I will explore the issue in more detail. First, I take a quick glance at the data used by the researchers. I then explore some of the nuances of the WEF’s Global Gender Gap Index (GGGI) used to measure gender equality. I conclude with some possible