Nach der Kommunikationsbranche, der Wirtschaft und der Industrie hat die
Digitalisierung mittlerweile unverkennbar auch das Recht erreicht. Dass
diese Entwicklung nicht mehr aufzuhalten ist, bestreitet eigentlich keiner.
Unklar ist, was genau passieren wird und wie lange es dauern könnte bis
was auch immer, in welcher Form auch immer, eintritt.
When Microsoft presented their new project ELL, the Embedded Learning
Library, to the public at the end of June 2017, the media echo failed to
acknowledge its groundbreaking potential. Only a few tech-focused news
sites referred to the press release and the related github project. This
rather underwhelming public attention is not the result of a misguided
project decision at Microsoft, but the exact opposite.
The Earth is roughly four and a half billion years old. During most of
that time—i.e. over the course of some four billion years—the
geological and biological development on our planet happened unbelievably
slow. How can we possibly form even a faint idea of this unimaginable
process that is the history of the Earth?
If one desires the excitement of taking public transportation on a
frequent basis, one observation is common through the bench: almost
everyone is on the smartphone, checking apps, social media and the news. As
“texting” has become so common in our lives, the importance of
“text” has steadily increased. Understanding text in all its dimensions
is also the basis for conversational AI.
Barely a week passes without the announcement of yet another (seed)
funding round for a startup, which claims to utilize “artificial
intelligence”, “deep learning”, “machine
learning” or “proprietary algorithms”. Algorithms, it
seems, are at the core of almost all ventures these days – is that
really the case?
Visualising data on health and mortality has a most up-to-date ring to
it, as if it had required the rise of big data and computational tools for
something as intricate as visual health statistics to
“Everybody Lies” is the harsh title of Seth Stephens-Davidowitz’s
new book. While it doesn’t provide any feasible recipe to prevent people
from lying, the book helps the reader in one essential realm: to grasp and
conceptualize the power of data and data science. Its key strength: It does
so in a very engaging and accessible way.
81 years of budget data and various categories in three diagrams – the
United States Fiscal Chart from the 1870 US census atlas is a real
blockbuster in the history of data visualisation. The atlas as a whole is
full of interesting graphics and has a widespread reputation as an early
gem of data visualisation.