Throughout my ongoing meetings and conferences about the GDPR and how it relates to cutting-edge technologies, I encounter many ‘add-on’ privacy solutions such as ‘secure your Office 365’, ‘breach detection’ and ‘fix your network.’ Such options, which aim to patch privacy vulnerabilities as they arise, also have the secondary effect

I’ll never forget my “aha” moment with bias in AI. I was working at IBM as the product owner for Watson Visual Recognition. We knew that the API wasn’t the best in class at returning “accurate” tags for images, and we needed to improve it. I was nervous about the

The digital advertising market has doubled in size over the past five years, with the total ad spend in Europe approaching €50 billion, according to the IAB. The success and continued growth of the market is reliant on the massive volumes of data produced each day – an estimated 2.5 quintillion

Artificial Intelligence is dominating innovation in companies across the globe- doesn’t matter if they are giant conglomerates or young startups. According to a report by Research and Markets titled Artificial Intelligence Market by Technology, and Industry Vertical – Global Opportunity Analysis and Industry Forecast, 2018-2025, the global Artificial Intelligence market

For some time, observability in IT operations has been associated with three data types that monitoring systems must ingest in order to be at least somewhat effective: logs, metrics, and traces. This limit to the type of data consumed is far from efficient when it comes to the true needs

Disasters are dangerous, but Big Data can help improve disaster relief and preparedness to cut back on lives lost and community damage. Historically, public policies have proved ineffective in providing adequate help for disaster-stricken citizens. A year after hurricane Harvey in 2017, for example, residents are still in the midst

It’s no news that unstructured data has been a highly sought after source since its inception, first for determining public topical insights and now for training machine learning algorithms. The critical question to answer is whether you should outsource the collection to overcome business challenges or not? Mike Madarasz explains

Organizations yearn order and simplicity over chaos and confusion, but the data-driven era we live in challenges these desires on a daily basis. Seemingly every day, massive amounts of transactional and streaming data is being introduced into enterprises. This data must be collected, deciphered, shared, and acted upon. Cloud-native technologies

With the help of a use case, Dr Patrick Vetter, Head of Competence Center Data Science at Supper and Supper GMBH explains how a deep learning methodology can locate and segment wind turbines on satellite imagery. As a pioneer in fighting global climate change, Germany is increasingly investing in renewable

A clever algorithm that has digested seven decades’ worth of articles in China’s state-run media is now ready to predict its future policies. The research design of this “crystal ball” can also be applied to tackling a variety of other problems. Supervised learning — the most developed form of Machine