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Impact and value through AI technology
AI products that work for you and with you
Improve your AI product's
quality
transparency
explainability
compliance
adoption
value
trustworthiness
fairness
quality
January 25, 2022
Starting my own company must be the most exciting thing I've done in my career so far. Coming from a family of entrepreneurs (both of my parents ran their own pharmacy), I've always envisioned myself one day becoming my own boss. And now the time is there: I've officially set my first steps into the entrepreneurial life.
Here are the three main reasons why I think now is the right time to do so:
January 5, 2022
Data science has a problem: A recent study by Venturebeat implied that 87% of AI projects don’t make it to production*.
There are multiple root causes we can identify that result in this high number of failures, but before we go into them, I think that at its core, it has to do with a misunderstanding between the (business) people using the data product, and the (technical) people creating it. End users of data products often have little to no technical knowledge of the products they work with.
Have you ever experienced that the data solution you worked on:
January 14, 2022
My recent blog was about acknowledging the difference in perspectives between the end users of your data product and the data team developing said product.
Today I want to discuss how to take this realization and use it to improve the quality, trustworthiness, impact, and adoption of your data products.
For wouldn’t it be amazing if users and stakeholders felt that the data products you develop are game changers? Yes, yes it would. Now let’s make sure they do.
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January 23, 2022
In the past two blogs I described:
Today's blog is the third and last in this series. It aims to dive a little deeper into the user research you might want to engage in to succeed in developing user-friendly, value-creating, impactful AI products.
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