Bret Victor The Future of Programming

Lots of cynic-cynics in here :) I'll stand up for the author. The lists in the article are not great, but I still agree with the sentiment. I recommend everyone watch Bret Victor's classic "The Future of Programming" [this video] Yes, we've had a trillion dollars invested in "How to run database servers at scale". And, we've had some incremental improvements to the C++ish language ecosystem. We've effectively replaced Perl with Python. That's nice. Deep Learning has been a major invention. Probably the most revolutionary I can think of in the past couple decades. But, what do I do in Visual Studio 2019 that is fundamentally different than what I was doing in Borland Turbo Pascal back on my old 286? C++20 is more powerful. Intellisense is nice. Edit-and-continue worked 20 years ago and most programmers still don't use it. If you are super awesome, you might use a reversible debugger. That's still fringe science these days. There is glacial momentum in the programming community. A lot of "grep and loose, flat ASCII files were good enough for my grandpappy. I can't accept anything different" And, so we don't have code-as-database. A lot of "I grew up learning how to parse curly bracket blocks. So, I can't accept anything different". So, so many languages try to look like C and are mostly flavors of the same procedural-OO-bit-of-functional paradigm. A lot of "GDB is terrible, don't even try" so many programmers are in reverse-stockholm system where they have convinced themselves debug

Bret Victor's, "The Future of Programming" is illuminating. He walks through what "programming" means and how the concept of "programming" has shifted in little evolutionary leaps. [this video] "There can be a lot of resistance to new ways of working that require you to unlearn what you've already learned and think in new ways. ... And there can even be outright hostility." Programming Baduk used to involve expert systems. Now convolutional neural networks (CNNs) can hoist a computer to superhuman performance, even doing so without pre-programmed rules (see MuZero). We no longer "program" computers to play Go, chess, shogi, or even Atari games. Some people have difficulty keeping code structures in their mind's eye. Here's a conceptual development environment for navigating code visually, ending with a dual text editor: [link] Is that programming? What's the difference between _typing_ instructions into a computer to place a graphical user interface widget on a screen and _telling_ the computer you'd like to put a toroid on the screen? Computers can use CNNs to fill in knowledge gaps. Even though the computer wasn't told the colour, size, shading, material, or location of the toroid, it can still show us the ring. Is telling a holodeck that you'd like to replay a scene from a novel a form of programming? [link] Each evolutionary step in programming has given us more powerful ways to express ideas in ever terser forms. Few people code in binary anymore. Did Picard need to tell the

PeerJ has actually quite a few publications, one of them is CS ;) [link] the dropdown on the top left allows you to switch between them. I think MathJax is certainly a step in the right direction, they even support rendering to MathML. But I agree that there is a certain lack there in terms of full semantic representations. MathJax is more accessible than TeX but it's still describing visual layout, instead of semantic meaning. Pushing HTML to arxiv is also a step into the right direction. I think the most important thing we can do is not be complacent with the state of the art. We need to go back to an age of computing where we didn't think we had it all figured out. We need to experiment, and not be afraid to take a step back in some aspects, like layout and kerning, in exchange for other advances like semantic representations and knowledge representation. I think bred victor has a great talk on this: [this video] I think we need to experiment with things like observablehq.com or nextjournal.com or the many other that are coming into existence.

Programming was in its infancy 50 years ago, but in reality we don't really know what its development arc is. We could be in the toddler stage right now, or we could still be in infancy when compared to future developments in the field. I believe we are much closer to the latter. There were things being done in the 60s that we still haven't really integrated into our trade. [0] We joke about having to program with hardware switches and punch cards, yet here we are still typing carefully crafted cryptic commands that tell the computer exactly what it is supposed to do, and storing them in linear text files which we have to mentally map to program states. I think there will always be a place for this kind of programming, just as people still use Assembly today, but it's a bit premature to say, "Well, this is it, or nearly so!" I recall reading that one of the giants of early computing, Von Neumann perhaps, never understood the benefit of Assembly and thought that it was a waste of the computer's time to compile to machine code rather than have a human write the machine code directly. We are working inside a problem domain that we barely understand. I find it hard to believe that we will have the glorious sci-fi future that many of us imagine will come out of advancements in technology without also developing corresponding advancements in how we describe and create and interact with it. One potential example that I am looking forward to learning more about is Luna, which feature

The problem is we stop pursuing answers on this topic, thus stop making progress. It's basically like what Bret Victor has described in 'The Future of Programming'. [0] There were a lot of language zealots at the end of the last century, especially on evangelizing Object-Oriented Programming. Nowadays everybody can easily counter those arguments with 'No Silver Bullet' without further thinking, it's arrogance in disguise of humility. There are still a huge amount of accidental complexities to deal with in most tech stacks. Most businesses would die fast and leave nothing behind anyway, while the progression of the industry would accumulate and benefit the whole industry itself. Java looks slightly better for creating software at scale than C. C looks slightly better than FORTRAN. FORTRAN looks slightly better than machine code. Say there's a language that looks like Haskell but has tooling and ecosystems as good as Java, I believe it would also slightly better than Java. [0]: [this video]

> and the whole history of computing is about how faster chips is an excellent answer to difficult computational problems. I don't really disagree, and I am definitely not taking their marketing pitch seriously. Yet, you could look at the same computation history and interpret it as an economically constrained hill-climbing around an idea that was simple enough to work reliably (von Neumann architecture) and that worked and scaled so well that we were rarely forced or desperate enough to move conceptually far away from it. Sufficiently general digital computers can simulate other computational models, so I think 'faster' is ultimately the end game, but for some classes of computation, as you also noted, we may need to go for analog hardware, (maybe) quantum devices, optical interconnects, and so on. Bret Victor has a talk about this, more or less: [0] [0] [this video]