> I don’t see any path from continuous improvements to the (admittedly impressive) ‘machine learning’ field that leads to a general AI
> I share the skepticism towards any progress towards 'general AI' - I don't think that we're remotely close or even on the right path in any way.
This isn't how science works though. Quoting the wikipedia page for Thomas Kuhn's "The Structure of Scientific Revolutions" (https://en.wikipedia.org/wiki/The_Structure_of_Scientific_Re...):
"Kuhn challenged the then prevailing view of progress in science in which scientific progress was viewed as "development-by-accumulation" of accepted facts and theories. Kuhn argued for an episodic model in which periods of conceptual continuity where there is cumulative progress, which Kuhn referred to as periods of "normal science", were interrupted by periods of revolutionary science."
I think this is the accepted model in the philosophy of science since the 1970s. That's why I find this argument about AI so strange, especially when it comes from respected science writers.
The idea that accumulated progress along the current path is insufficient for a breakthrough like AGI is almost obviously true. Your second point is important here. Most researchers aren't concerned with AGI because incremental ML and AI research is interesting and useful in its own right.
We can't predict when the next paradigm shift in AI will occur. So it's a bit absurd to be optimistic or skeptical. When that shift happens we don't know if it will catapult us straight to AGI or be another stepping stone on a potentially infinite series of breakthroughs that never reaches AGI. To think of it any other way is contrary to what we know about how science works. I find it odd how much ink is being spent on this question by journalists.
> I share the skepticism towards any progress towards 'general AI' - I don't think that we're remotely close or even on the right path in any way.
This isn't how science works though. Quoting the wikipedia page for Thomas Kuhn's "The Structure of Scientific Revolutions" (https://en.wikipedia.org/wiki/The_Structure_of_Scientific_Re...):
"Kuhn challenged the then prevailing view of progress in science in which scientific progress was viewed as "development-by-accumulation" of accepted facts and theories. Kuhn argued for an episodic model in which periods of conceptual continuity where there is cumulative progress, which Kuhn referred to as periods of "normal science", were interrupted by periods of revolutionary science."
I think this is the accepted model in the philosophy of science since the 1970s. That's why I find this argument about AI so strange, especially when it comes from respected science writers.
The idea that accumulated progress along the current path is insufficient for a breakthrough like AGI is almost obviously true. Your second point is important here. Most researchers aren't concerned with AGI because incremental ML and AI research is interesting and useful in its own right.
We can't predict when the next paradigm shift in AI will occur. So it's a bit absurd to be optimistic or skeptical. When that shift happens we don't know if it will catapult us straight to AGI or be another stepping stone on a potentially infinite series of breakthroughs that never reaches AGI. To think of it any other way is contrary to what we know about how science works. I find it odd how much ink is being spent on this question by journalists.