Just a few days ago, I was pointed to a new scientific paper by Google DeepMind. It’s amazing as it’s from Google DeepMind, it’s about chess, but it’s not about AlphaZero! The Google DeepMind researchers were trying to build a “searchless” chess engine: an engine that doesn’t calculate at all but finds great moves by “understanding” the position through evaluation only.

Garry won the 1996 match against Deep Blue by 4-2, though not without losing the first game. The 1997 match was thus eagerly awaited: what had / could Deep Blue learn from the first match and how much would it have improved?

The idea for a series of videos on the Garry Kasparov against Deep Blue matches of 1996 and 1997 came from a subscriber to my YouTube channel. I thought it was a great idea and I’ve become a bit obsessed with it!

I am pretty confident I have analysed more engine games than anyone else in the world, and I truly feel that my understanding of chess has benefited greatly from it. However, some aspects of engine play and evaluation are still difficult to grasp and internalise. I came across an instructive example of this while analysing a line of the Classical Pirc with 6…Nc6.

There are many difficult things about learning a new chess opening, but unresolved contradictions are perhaps the most painful. Unresolved contradictions typically arise in a student’s mind when opening courses praise a strategy in one chapter and then show it leading nowhere in another!