Artificial Intelligence
Big Data and AI: Where Do You Stand?
Turner’s data scientist, Egbert Clevers, ponders the ubiquity of big data and AI while driving. Everyone uses AI. But how many organizations are actively using AI themselves to drive change, improve, and innovate? And where do you stand on this?
Big Data and AI: Where Do You Stand?
Early Monday morning, I’m on my way to work. I turn on the GPS. I know the route, but thanks to the green, yellow, or red colors on the map, I can immediately see where the traffic jams are and what time I’ll arrive as a result. Super handy!
During the ride, I realize just how much data must have been collected for this. The“whereabouts” and movement speeds of many millions of smartphone users, real-time information about road conditions, and the average driving speeds of others and myself on those roads. All of this has been modeled together and processed into a single smart product: an application of Artificial Intelligence (AI) to “big data.”
What is Artificial Intelligence?
What is Big Data?
AI can be found in many consumer products, as well as in Healthcare, the financial sector, Education, and other fields. AI is everywhere.
AI has evolved at breakneck speed—so fast, in fact, that both experts and laypeople are constantly learning about this intriguing world.
Do you know what AI and big data really are, and exactly how great their potential is? You probably have for a long time! But do you know what kind of data you need for a successful data application, and how an effective data team is structured? I’d also like to challenge you on the implementation process: do you encounter barriers and resistance when implementing a data application? Is your organization able to overcome such barriers?
In short, take a look at the figure: where do you stand?

In this blog series, we’ll be discussing all the ins and outs of AI—the technical aspects, but especially the organizational change aspects. How great is the promise of AI, and what factors help fulfill that promise—or stand in its way?
Roundtable Discussion on Thursday, November 19
All of our specialists’ insights on artificial intelligence.

A form has never been the best way to understand someone. AI enables multimodal input.
From minimal input to rich context: AI-driven multimodal input is transforming how financial institutions make decisions.

Banks, Start Using AI Now to Help Entrepreneurs
Artificial Intelligence Banks, Start Using AI Now to Help Entrepreneurs Since the

Consultancy.nl | Jeroen Visscher Leads the Education Working Group of the AI Coalition
AI Jeroen Visscher leads the AI Coalition’s Education Working Group Consultancy.nl has

Big Data and AI: Where Do You Stand?
Big Data and AI: Where Do You Stand? Turner data scientist Egbert Clevers reflects in the car on the ubiquity of big data and AI. Everyone uses AI. But how

Taking AI Beyond the Experimental Stage?
Artificial Intelligence Taking AI Beyond the Experimental Stage? It Starts with Focus.

Innovating with Data in Healthcare?
Artificial Intelligence Innovating with data in Healthcare? Oil the machine first. Turner’s

5 Data Governance Tips
Artificial Intelligence 5 Data Governance Tips: Don’t Let Your “Data Lake” Turn

Six Archetypes of Data Scientists—CHOOSE Your Color
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Promising Start for the Education Working Group
Monday, November 23 marked the official kickoff of the NLAIC’s Education Working Group. Approximately 225 participants took part in the session—enthusiastic and engaged individuals who want to help advance the

Kickoff of AI in Education Month
The Dutch AI Coalition (NL AIC) is a co-organizer of AI in Education Month. The month of June is therefore packed with (online) events aimed at raising awareness of AI

June, AI in Education Month
Jeroen Visscher leads the Education Working Group within the Dutch AI Coalition. In June, the working group will organize “AI in Education Month.” Together with SURF and the Acceleration Program,

10 Tips for Implementing Artificial Intelligence in Your Organization
More and more financial institutions are investing in artificial intelligence. However, not all of these AI initiatives are as successful as hoped. Why is that? And what can you, as
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