8 Most Controversial Terms in AI, Explained

Learn about a controversial label for LLMs, whether it holds up, and what on earth parrots have to do with it.

Deciding if you think models display emergent behaviors could shape your perspective on AI, so take the time to learn why this term is so controversial.

In some quarters, the most controversial term of them all. Here, we mainly focus on the difference between open source and open weights - a key distinction!

You won't (I hope) be bitter after learning about the bitter lesson - a seminal insight onto what works best in AI, and why.

Now we're getting deep. Reflecting on whether models actually 'reason' - and what that word actually means - or just pattern-match, is crucial for anyone interested in using AI.

It's easy to 'know' that models hallucinate and are biased, but actually exploring demonstrations on how they are, and how to minimise that, is a whole other matter - a matter we discuss in this deep dive!

Takeoff' and 'takeoff speeds' are terms worth learning about, even if they are deeply theoretical, and even if you disagree with the entire notion of a takeoff. The fact that these terms have led to debate even at CEO-level is enough to make it worth grasping their meaning, whichever 'side' you are on.

Perhaps the most controversial term of them all. Whatever your stance is, knowing the origins, nuances and key positions on this term will serve you well.