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Simply AI

Simply AI

The Great AI Debates

The Great AI Debates

As 2023 was an inflection point for AI awareness there is a lot of hype about this decades-old technology that has already gone through 2 “AI winters.” That means AI has essentially been through 2 hype cycles already, and it’s again hyped up for the third time now. Will this be just another hype, or this time is different?

Nyenrode Business Univ: GenAI guest lecture speakers

Nyenrodians: This is the Way!

Nyenrodians, I hope you enjoyed this guest lecture as much as I did. I hope this GenAI lecture on steroids helped boost some of your AI muscles by making you almost an expert on GenAI. Now that you know enough to be dangerous, please do something with it.

Inherited Biases Within Your Data

Dealing With AI Biases Part 2: Inherited Biases Within Your Data

AI bias problem is currently being thought of as a data problem. And to a large extent, if we can fix the biased data, we would’ve addressed most of the AI biases. However, not all biases are bad. In fact, biases are often introduced in training data to improve the performance of the trained model.

Acknowledging your AI is Bias

Dealing with AI Biases Part 1: Acknowledging the Bias

Today, most AI practitioners in the industry are treating AI bias as a data problem. To a large extent, if we can fix the biased data, we fix the AI bias problem. However, fixing the biased data is not the only way to address the problem.

Building a Unique Moat - Part 3: The PROS Differentiation

Building a Unique Moat – Part 3: The PROS Differentiation

PROS has fortified its market position through a combination of common moats. With a renowned brand, proprietary AI, strategic customer relationships, and robust R&D investment, we stand as a formidable player. But PROS also has a very distinctive moat – the unique synergy between our Travel and B2B.