"As Kay himself has said so many times, this question is entirely about funding. With ARPA/IPTO-style funding, you get Kays (and Engelbarts, Minskys, McCarthys, Corbatós, etc) With VC and NSF, you don't. Even Kay hasn't been able to "be Kay" since the 80s: http://worrydream.com/2017-12-30-alan/ "
Another problem, I think, is that many people are no longer interested in this kind of research. Two popular lines of thought are:
- Our infrastructural computing is already awesome or at least good enough, so we do not need anything simpler or different, just more tooling and automation.
- Machine learning will fix everything in computing.
I'm very interested in doing this kind of research, but I can tell you it's incredibly difficult in academia, for instance, to publish research about programming languages, or wild new designs. It seems to me the academic world has moved to a model where everything has to be incremental, and you have to immediately have positive results that beat prior work on a number of metrics. Anything else is unpublishable.
As far as machine learning fixing everything. I work in machine learning now, and I'm incredibly skeptical. Especially with the way companies always rush things to market and seek to eliminate competition. There are going to be a lot of bugs, hacks, and malicious uses of machine learning. I will also mention that the quality of the code I'm seeing in ML right now is absolutely terrible. Everything is so fast-moving. People don't take time to polish anything, they've already moved on to another project, nothing is maintained. The code is largely written by academics who are rushing to write papers and look down on programming as some kind of unfortunate necessity, and the quality of the code they produce reflects that. Oh and, the machine learning world thinks Python is the best programming language ever... Sigh.
I'm in industry, but have similar leanings of wanting to work on this stuff. For a few years I was convinced academia was the way to do this; now I'm not certain. It's as if the collective capacity of dreaming about the possibilities of computing was lost when we realized we could make lots of money. Instead of building bicycles for the mind, we're obsessed with building TV 2.0, and getting lots of money doing it. Nowadays I see my meager, fledgling research as art pretty much.
I don't know where I'll end up long-term, but I doubt I'm the only person that feels this way. I've occasionally thought of starting a Slack for this sort of thing.
Bret Victor has some good conceptual stuff. But as he said himself:
https://twitter.com/worrydream/status/947177766885081088
"As Kay himself has said so many times, this question is entirely about funding. With ARPA/IPTO-style funding, you get Kays (and Engelbarts, Minskys, McCarthys, Corbatós, etc) With VC and NSF, you don't. Even Kay hasn't been able to "be Kay" since the 80s: http://worrydream.com/2017-12-30-alan/ "
Another problem, I think, is that many people are no longer interested in this kind of research. Two popular lines of thought are:
- Our infrastructural computing is already awesome or at least good enough, so we do not need anything simpler or different, just more tooling and automation.
- Machine learning will fix everything in computing.