Data Science

Legal Tech: Wie wird die Digitalisierung des Rechts vonstattengehen? Noch haben wir die Wahl!

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.

idalab seminar #6: Jeremiah Lewis and Edouard Malet from N26

On December 1st 2017, idalab will host a talk by Jeremiah Lewis and Edouard Malet from N26: ‘Lean’ Training Data: An Incremental Approach to Supervised Machine Learning.

The missing link – Will Microsoft’s far-sighted ELL project inspire the IoT era?

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.

Data Trails No. 5 – Snapshots from the history of data visualisation

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?

The Power of Text

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.

Why to be sceptical about the rise of AI startups

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?

Data Trails No. 3 – Snapshots from the history of data visualisation

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 develop.

Summer Book Recommendation: “Everybody Lies”

“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.

Data Trails No. 1 – Snapshots from the history of data visualisation

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.