Basis aller heutigen Künstlichen Intelligenz sind bekanntlich Algorithmen. Diese sind in den letzten Jahren in zunehmendem Ausmaß in den Fokus der öffentlichen Wahrnehmung gerückt. Dabei schwankt der Grad an thematischer Souveränität und Güte der einzelnen Wortmeldungen aus Presse, Politik und Gesellschaft teils erheblich.

About our Blog

This blog is a place for us to reflect on data science, AI, and machine learning. Hence, it covers a broad array of topics: technical considerations, our view on certain industries, interviews with researchers, thought leaders, and industry experts, as well as light-weight visualisation.

Featured in

idalab seminar #13: Exploring Chemical Space with Deep Learning

What if we could build batteries for electric cars that would take us further than a full tank of gasoline? If we could grow affordable, tasty and nutritious meat in the laboratory instead of occupying one third of the land on our planet with animal farming? What if we could easily identify promising targets in the human body for new cancer drugs?

idalab goes PyData

This year’s PyData Berlin conference, taking place from July 6th to 8th at the Charité-Campus (Virchow), was a huge success and with almost 600 participants the biggest PyData conference all over Europe. Concerned with providing a forum for python users and developers in the field of data analysis, a wide range of topics was covered in four simultaneous tracks, going from deep learning and scalability over data privacy and best practices to putting machine learning into production.

idalab seminar #12: The data-privacy dilemma: How full homomorphic encryption could bring healthcare into the digital era

Imagine this: The key to better cancer treatments is within reach, based on patterns from data that is scattered across various locations all over the world. This data could be digitalised, labelled, collected, stored and interpreted. However, this data belongs to a countless number of individuals – and their right to data privacy weighs just as much as the dream of curing a lethal disease.

What do we mean by “data”?

Some technical terms are so ubiquitous and (apparently) unambigious, that they almost become a transparent fluid: always used but never much reflected upon. Interestingly enough, the word “data” 1 is such a term. It is an abstract, weightless and unidentified mass of numbers (mostly digitally encoded), with a potent influence on our lives. It is also considered a rich source of insight that is worth being tapped. But what are the origins of the word “data” – and what are its implications?

idalab seminar #11: SELECT * FROM … natural language: databases, we need to talk!

Do you know the feeling? All you want is a break-down of last year’s sales numbers and suddenly you find yourself typing tedious heaps of SQL-statements, clicking through complicated dashboards or looking for the right number in an Excel sheet. The vast majority of decision makers has better things to do with their time. That’s why business intelligence software was originally born. But only 20% of users are actually coping with the solutions BI software provides. Instead, the BI team is spammed with ad hoc data requests. What if everyone had a personal virtual data analyst at hand?

Auf dem Weg zu einer nationalen KI-Strategie

Die Stiftung Neue Verantwortung hat jüngst eine Empfehlung für eine deutsche KI-Strategie in Form eines Diskussionspapiers herausgegeben. Hintergrund ist das Bestreben des Think Tanks, den gegenwärtigen Arbeitsprozess der Bundesregierung zum Thema KI-Strategie durch Experten-Input zu unterstützen und zu ergänzen. Paul von Bünau, Geschäftsführer der idalab GmbH, hat als einer der inhaltlichen Berater an dem Papier, das den Titel “Eckpunkte einer nationalen Strategie für Künstliche Intelligenz” trägt, mitgewirkt.

The Data behind Altered States of Consciousness: Interview with Timo Torsten Schmidt

When we want to grasp the subjective experiences of others, we count on their verbal accounts. Limited to language, quantifying how something feels for an individual is very hard. It is even more arduous for altered states of consciousness where descriptions become somewhat metaphorical.

Der Mythos der Juristen: Für Standardisierung zu individuell – Interview mit Professor Breidenbach Teil II

Anlässlich der Veröffentlichung des „Rechtshandbuch Legal Tech“, erschienen im C.H. Beck Verlag, waren wir im Gespräch mit Professor Breidenbach. Ausgehend von seinem Buchkapitel „Industrialisierung des Rechts“ entwickelte sich eine lebhafte Diskussion zum „Möglichkeitsraum Legal Tech“. Im zweiten Teil des Interviews sprechen wir über die digitale Fertigungsstraße, darüber, was sich an der Ausbildung der Juristen ändern sollte, wie man durch Potenzialentfaltung an Schulen gegen die Spaltung der Gesellschaft vorgehen könnte, und die Frage, ob die Industrialisierung des Rechts den Juristen von seiner Arbeit entfremdet.