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The concept of “Artificial Intelligence” had a massive impact over the past several years. Marvelous tales about its prospective achievements abound, just as much as sceptical questions about whether (or when) the machines will finally substitute the humans on this planet. As a result of this heated discourse, leaders across many industries feel an urgent need to somehow incorporate AI technologies into their workflows, fearing to miss out on an important innovation step.

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.

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Data Trails No. 8 – Snapshots from the history of data visualisation

Oh, the Mississippi. The „Father of Waters“ is a heroic beauty with an eventful history, famous for its tendency to meander. At times, it poses a major threat to the people living along its shore.

Data Trails No. 7 – Snapshots from the history of data visualisation

Timelines seem like such a „natural idea“ these days that we don’t even notice their ubiquity anymore: Facebook timeline, news feeds, graphic interfaces for back-up versions – how did anyone manage their life before there were things like this?

What would you recommend?

Personal recommendations are probably the strongest referral. If your friends tell you to checkout a restaurant they recently discovered, you are highly likely to follow their advice (assuming a general level of trust between you and your friends).

idalab seminar #6: ‘Lean’ Training Data: An Incremental Approach to Supervised Machine Learning.

On December 1st 2017, idalab seminar #6 will take place, hosting a talk by Jeremiah Lewis and Edouard Malet from N26.

Data Trails No. 6 – Snapshots from the history of data visualisation

Do you know that thing when you draft a project and anticipate it will come out nicely, and once you actually start looking into it things get really complicated? This is what happened to me with this severe beauty of a tree diagram here. I stumbled upon it in the Beinecke digital collections and was immediately thrilled about this hidden gem from back in 1608. Then I never came around to really studying it — until just now.

idalab news: idalab teams up with DFKI and Deutsche Bahn in the DAYSTREAM research project (BMVI mFund program)

After becoming part of the SD4M (Smart Data 4 Mobility) consortium in 2016, we are proud to announce that we will participate in another 3-year research program, funded by the Federal Ministry of Transport and Digital Infrastructure (BMVI) as part of the mFund program.

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.