So, the foundational problems remain...
They remain because there is no foundation to these cortical systems. Anyone who states this is railed and laughed at. So, you get what you get.....
The article states :
"Machines that truly understand language would be incredibly useful–but we don’t know how to build them."
There are people and groups who know how to build them. They are focusing on the 'foundation' first. That is not where the spotlight or money are directed. So, they remain in the dark.
We gained head-winds with a very trivial model of neurons and cortex like hierarchical neural network designs and the money sent people off to the races. People began writing wrappers, stuccoing the top floor, hacking up scaffolding, applying any C.S concept they could find in the parts bin to fancify the top floor.
That's where all of the attention and money is.. What does your system do? What benchmark can it beat? What data can it classify? What cool trick can it do to impress us? So, you get impressive trick systems that require massive amounts of data, training, and answer maps to obscure the lack of intelligence. As there is none explicitly designed into these systems, the system cannot convey its understanding.
It's nothing more than an answer map w/ annealing routines and memory... Very similar to cortical regions.
The foundation and supporting layers up to the top have been ignored, aren't getting any spot-light or money, nor are the individuals who continue to toil on it.
They're considered to be 'philosophers' and jokers and not real scientist/engineers/industry leaders. The A.I space shuts out a huge pool of varying opinions via its : If you don't have a PHD, one need not apply. If you're approaching it from any other methods than the ones subscribed to and you're not a name, face, or have a laundry list of papers you get the : Good luck (thumbs up).
And people stand around and wonder why the fundamental problems remain? Come on...
In any event, it wont remain for long and that will be due to someone/groups actually investing the time and energy to build a sound foundation. This begins first and foremost by deep philosophical questions about the nature of the universe and intelligence. The answers derived serve as a guiding light for further along scientific and engineering pursuits.
This article should be : AI's lack of a foundation. Whose going to build it? Whose going to invest the time to understand what exactly it is as opposed to hacking away at it?
It's the truth but would be considered a 'hit piece'.
Until someone constructs a proper foundation, no one is going to give credence to the idea that current A.I lacks it. Hindsight is 20-20 as is a force-fed neo-cortex.