The new EU draft AI regulation has leaked, reopening again the regulation vs. innovation debate. Is regulation really going to kill innovation in Europe?

“European Commission” by tiseb is licensed under CC BY 2.0

It has been already two years since the European High-Level Expert (HLE) group on Artificial Intelligence presented its Ethics Guidelines for Trustworthy Artificial Intelligence. The guidelines identified seven key requirements that AI systems should meet to be trustworthy:

As the European Commission explained after publishing the guidelines in 2019, “The Commission will propose a horizontal regulatory proposal in 2021. This proposal will aim to safeguard fundamental EU values and rights and user safety by obliging high-risk AI systems…


The combination of digital generative art and NFTs is getting a lot of attention. But, is the real value of these art pieces really encoded in the token?

“Generative art — pic.7” by Sergey Horo is marked with CC PDM 1.0

Let me start by saying that this story does not pretend to be a technical article describing how Generative art or NFTs work although I will introduce the basic concepts and some references for those who want to explore deeper. On the contrary, it pretends (and hopefully achieves) to generate a debate on how/ if NFTs are capturing the real value behind Generative art.

Generative art

A simple definition of Generative art can be found on Wikipedia as follows: “Generative art refers to art that in whole or in part has been created with the use of an autonomous system”.

The range…


Stanford’s Human-Centered Artificial Intelligence report provides a vast amount of distilled data to understand how the field of AI is moving forward under different categories. Should Europeans be worried?

AI Index Report 2021 cover, used under the Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) as allowed by its authors.

This short article highlights several charts from Stanford’s AI Index Report 2021 that should make European citizens think about its implications for the future competitivy of their economy in a global market. Although some countries like France, Germany and the nordics tend to perform better than the average European Union, the EU27 lacks behind AI world leaders in several categories.

The complete report is available here and all the figures from it included for reference purposes are used under the Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) as allowed by its authors.

1 — Private investment very far from AI world leaders


After GPT-3, OpenAI returns with two models that combine text and images. Will DALL-E be the protagonist of 2021 in the field of AI?

Photo taken by David Pereira at Dali’s museum in Figueres.

While the community is still discussing one of 2020 AI big announcements, GPT-3, whose paper was published July 22nd, 2021 has just begun and we already have two impressive new neural networks from OpenAI: CLIP and DALL-E.

Both CLIP and DALL-E are multimodal neural networks, and their creators claim them to be “a step toward systems with deeper understanding of the world”.

Multimodal neural networks: what are they?

Our experiences as humans are multimodal, meaning that we receive inputs from the world surrounding us in different formats (sound, image, odors, textures, etc.) …


The field of NLP has seen major advancements in the last years, but what does it mean for minority languages?

“File:Wubi86 keyboard layout.png” by Cangjie6 is licensed under CC BY-SA 4.0

OpenAI’s GPT-3 paper was introduced May 28th, 2020, becoming a hot topic in the field of AI Natural Language Processing. Its 175 billion parameters transformer architecture made it very popular in both specialized and general news, thanks to the vast landscape of applications that some developers quickly showcased, some of which I listed on my introductory article:

How are state-of-the-art NLP models trained in different languages?

Let’s take GPT-3 as an example. According to the GPT-3 paper, it was pre-trained on massive datasets, including the Common Crawl dataset, which contains petabytes of data collected since 2008 and weights 60% of the total training mix for GPT-3, which also includes…


After several breakthroughs such as AlphaGo or AlphaZero, researchers from DeepMind have published their latest effort, MuZero. What is it all about?

“Artificial Intelligence & AI & Machine Learning” by mikemacmarketing is licensed under CC BY 2.0

Back in 2016, DeepMind introduced AlphaGo, the first computer software able to defeat professional Go players, included the world champion. The games between Lee Sedol (18 Go world titles) and AlphaGo were even immortalized in a documentary, available now in Youtube.

Why was AlphaGo so relevant? Until then, computer programs were only able to play Go at an amateur level, as traditional Machine Learning methods such as search trees were simply not capable of evaluating all possible moves, board positions strengths, etc. …


Norbert Wiener, one of cybernetics pioneers, envisioned AI ethics problems way ahead of us

“43081” by Tekniska museet is licensed with CC BY 2.0. To view a copy of this license, visit https://creativecommons.org/licenses/by/2.0/

Ethics has definitely become a trend in the field of Artificial Intelligence. It seems clear that AI faces a lot of challenges if we want it to have a positive impact for our society. Nevertheless, it is not the first time that researchers warn us about the risks of this kind of technology. Norbert Wiener, cybernetics pioneer, wrote this somehow prophetic piece back in his book God & Golem, inc, back in 1964:

It is relatively easy to promote good and to fight evil and good and evil are arranged against each other in two clear lines, and when those…


My readers selected AutoML as the trend that will impact their job/ industry in the short time the most. What is it and why should you care?

“Machine Learning & Artificial Intelligence” by mikemacmarketing, licensed under CC BY 2.0

During my summer vacation, I ran across a CBInsights report called “AI trends to watch in 2020”. I was curious about what my colleagues and readers would think about the selected trends, so I launched a survey to see what they thought. I simply asked one question: “Based on your personal experience, which one is impacting your job/ industry the most?” and these were the results:


Gartner’s 2020 Hype Cycle for Emerging Technologies is out, so it is a good moment to take a deep look at the report and reflect on our AI strategy as a company. You can find a brief summary of the complete report here.

https://www.gartner.com/smarterwithgartner/5-trends-drive-the-gartner-hype-cycle-for-emerging-technologies-2020/

It has been already a year since I published a similar article on the same Gartner’s report for 2019 that you can find here. Which AI related technologies have been excluded from the report? Which ones should be, according to Gartner, focus areas for companies AI leaders?

First, a quick reminder of an important background to understand how Gartner’s Hype Cycles are presented. As Gartner explains in its research, its Hype Cycle covers a very broad spectrum of topics, so if a specific technology is not featured it does not necessarily imply that they are not important, quite the opposite…

David Pereira

Head of Data & Intelligence for Europe at everis, an NTT Data company. All opinions are my own. https://www.linkedin.com/in/dpereirapaz/

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store