This is truly a terrible accident. Given the flight tracking data and the cold, winter weather at the time, structural icing is likely to have caused the crash.
Ice will increase an aircraft’s stall speed, and especially when an aircraft is flown with autopilot on in icing conditions, the autopilot pitch trim can end up being set to the limits of the aircraft without the pilots ever knowing.
Eventually the icing situation becomes so severe that the stall speed of the ice-laden wing and elevator exceeds the current cruising speed and results in a aerodynamic stall, which if not immediately corrected with the right control inputs will develop into a spin.
The spin shown in several videos is a terrifying flat spin. Flat spins develop from normal spins after just a few rotations. It’s very sad and unfortunate that we can hear that both engines are giving power while the plane is in a flat spin towards the ground. The first thing to do when a spin is encountered is to eliminate all sources of power as this will aggravate a spin into a flat spin.
Once a flat spin is encountered, recovery from that condition is not guaranteed, especially in multi-engine aircraft where the outboard engines create a lot of rotational inertia.
The technical definition of AI in academic settings is any system that can perform a task with relatively decent performance and do so on its own.
The field of AI is absolutely massive and includes super basic algorithms like Dijsktra’s Algorithm for finding the shortest path in a graph or network, even though a 100% optimal solution is NP-Complete, and does not yet have a solution that is solveable in polynomial time. Instead, AI algorithms use programmed heuristics to approximate optimal solutions, but it’s entirely possible that the path generated is in fact not optimal, which is why your GPS doesn’t always give you the guaranteed shortest path.
To help distinguish fields of research, we use extra qualifiers to narrow focus such as “classical AI” and “symbolic AI”. Even “Machine Learning” is too ambiguous, as it was originally a statistical process to finds trends in data or “statistical AI”. Ever used excel to find a line of best fit for a graph? That’s “machine learning”.
Albeit, “statistical AI” does accurately encompass all the AI systems people commonly think about like “neural AI” and “generative AI”. But without getting into more specific qualifiers, “Deep Learning” and “Transformers” are probably the best way to narrow down what most people think of when they here AI today.