And what could be done to re-spark interest in moving forward?
My gut feeling says that it would require a complete overhaul in almost every layer in the stack we use today and that there's reluctance to do that. Would you agree to some degree with that?
In our not-quite-an-industry, we seem to laud attempts to optimize the artifact of a residual hack, and we are absolutely dismissive of attempts to rebuild the stack as being too ambitious. And the problem with being dismissive is that it's a judgement without trial. We have precious few "crazy professors" and no tolerance for them.
What can we do?
There's the 2020 group in San Francisco. Is that kind of meetup the right direction?
"Doctors need disease"
Things have happened in the past when passionate and confident people with chops have decided to do something. These have not always correlated with "What is actually needed" (often not) but they usually get things into a state where people who are mainly trying to advance their own goals see some advantage (including "tech chic").
We are certainly not in a position where this can't happen a few more times.
Looking back, I've been struck not by how few really good researchers there are, but more so by how few really good managers of researchers there have been, and even more so by how really really few good funders there have been.
Maybe too simplistic, but in my view great funding has caused great stuff. So the funders should get the gold medals rather than the researchers! (Think about it: the good funders give out the gold in advance knowing full well that if even if they are very luckly 70% of the gold will turn to lead in just a few years!)
Bob Taylor has been generally praised as a great manager, and I believe them of course. But when I heard stories of his management style, it seemed to go against every instinct we have on how to foster creativity. Could you comment on that?
Also, in terms of funding, I wonder -- haven't things changed? Wasn't funding more important in, say, the 1960's and 70's due to the cost of computer time, especially at the processing level that would let you "see the future." A $1000 computer today is not so different, in terms of power, from a similar machine 5 years ago, right?
Things have happened in the past when passionate and confident people with chops have decided to do something.
But wasn't the past more open? When a field is just forming, everything is crazy, so nothing is. It's only when it has solidified (and in exactly the wrong direction) that you would more expect to find a "crazy professor" having more of an impact, right?
If you are computing on a $1000 computer, you are computing in the past. Part of the idea here is that you want to do research and development on supercomputers of the present that will give you the resources that will be available at lower prices in the future.
With salaries as they are today -- and real estate much worse -- it is actually more expensive to fund the same kinds of research today.
The past was similar to today in that most people in computing back then were orbiting around some local vendor's and local fads notions of computing. And it was a lot harder to make computers and other tools back then. It wasn't a crazy professor having an impact back then, but a whole research community that was required to make an impact.
If you are computing on a $1000 computer, you are computing in the past.
I know that this was true in the past but it's my contention that hardware has had Moore's Law where software has stagnated, and that the passing of time has meant that now current software doesn't often take full advantage of the hardware available. If you did architect based on where the puck is going (optimized for multi-core, no main memory) current hardware wouldn't slow you down the same way as it did before and sometimes you would even see a performance gain.
By the way, thanks for doing this.
Let me respectfully disagree with your contention. The point that is missed is not what the hardware could do, but what can you do without optimizing. It is very very hard to put on the optimization hat without removing the design hat, and once you've removed the latter you are lost.
The key to the Parc approach was to be able to do many experiments in the future without having to optimize. (There was a second part to this "key" but I'll omit it here)
For my second point -- I definitely didn't mean optimization that way. I guess the word I meant to use was "targeted", as in "targeted for multi-core" but I see your point and respect it fully.
I'm thrilled and deeply, deeply honored to have had this time with you, Dr. Kay. Thank you so much again. If you're ever in the Bay Area on the first Saturday of the month and feel inclined to stop briefly by the 2020 group meeting (which is an attempt at a replacement for the Future of Programming Workshops that used to take place at Strange Loop), we would be over the moon. You can reach out to Jonathan Edwards if you need the details.
The ARPA/Parc process "funded people, not projects" -- and today this seems quite outre to most.
As you probably know, Jonathan is doing some work with us ...
And that group is probably also the reasons for my views. I would never qualify to be in HARC and yet I don't just want to be content to scorn the state of the industry and state of the art. I see that there's additionally interesting research coming from garages and weekend projects. I feel that "problem finding" is somewhat interchangeable with "point of view" and that can come from surprising sources. Funding might be needed for the hardware but my own experience, for what it's worth, hasn't borne that out. The main component then is time, and while weekends aren't much, they'll have to suffice. The last step is to see if we can't get further as a community, giving that feedback so critical at PARC, and so that is why the group was created.