AI is impressive because we've failed at personal computing

No names is not the biggest problem. You just have to come up with a name. The problem is when things have multiple names, or even worse when people disagree on what names are appropriate for something. The world rarely allows you to neatly categorize large datasets. There are always outliers.

For example, you have a set of balls and you want to sort them by color. Where does orange stop and red begin? What about striped balls or ones with logos printed on them? What if it is a hypercolor ball that changes based on heat? It gets messy very fast.

I would argue that the money is short termism though. It just assumes short term returns are the correct choice because it lacks the technical understanding of the long term benefits of a good job.

In my experience many acquisitions set the peak of a given software product. The money then makes the argument that its "good enough" and flogs the horse until its dead and a younger more agile team of developers eventually build a new product that makes it irrelevant. The only explanation I have for why so many applications fail to adapt is because of a cultural issue between the software and the money, that always gets resolved by the money winning.

For example I would suggest that the vast majority of desktop apps, especially those made by SMEs, originally in MFC or something fail to make the transition to online services that they need today because of this conflict. The company ends up dying and the money never works out what it did wrong because its much harder to appreciate those long term effects than the short term ones that gave them more money at the start.

I sympathize so much with the failure of personal computing to manifest!

> My point is that if all knowledge were stored in a structured way with rich semantic linking, then very primitive natural language processing algorithms could parse question like the example at the beginning of the article, and could find the answer using orders of magnitude fewer computational resources. And most importantly: the knowledge and the connections would remain accessible and comprehensible, not hidden within impenetrable AI models.

It's a pocket hope of mine that AI brings us back to the Semantic Web, or something very like it. In many ways these embeddings are giant non-human lexicons already. Distilling this information out seems so possible.

Even just making an AI to go markup (or uhh perhaps refine) a page with microdata seems conceptually very doable!

More broadly, looking at personal computing: my personal belief is that failure is hugely because of apps. Instead of a broader personal computing that aggregates, that allows constructivism, that enables personal growth & development (barefoot developers & home-cooked software style), computing has been defined by massificstion, by big tech software. The dominant computing paradigm has been mainframe pattern: we the user have an app that acts as a terminal to some far off cloud-y data center. Whatever agency we get is hewn out for us apriori by product teams, and any behavior not explicitly built in is a "Felony Contempt of Business Model" (an oh so accurate Doctorow-ism)! https://maggieappleton.com/home-cooked-software https://news.ycombinator.com/item?id=40633029 https://pluralistic.net/2022/10/20/benevolent-dictators/#fel... https://news.ycombinator.com/item?id=33279274

It is so so sad to see computing squandered so!

The good news is AI is changing this relationship with software. I'm sure we will have no end of AI models built in to our software, that companies will maintain the strict control (tyrant's grip) over software as long as they can! But for AI to flourish, it's going to need to work across systems. And that means tearing down some of the walls, walls that have forcibly kept computing (ardently) anti-personal.

I can go look at https://github.com/punkpeye/awesome-mcp-servers and take such great hope from it. Hundreds of ways that we have eeked out a way to talk interface with systems that, before, people had no say and no control over.

The semantic web was theoretically great for data scientists and metadata scrapers, but offered close to zero value for ordinary humans, both on the publishing side an the consumption side. Also, nobody did the hard work of defining all of the categories and protocols in a way that was actually usable.

The whole concept was too high minded and they never got the implementation details down. Even if they did it would have been horrendously complex and close to impossible to manage. Asking every single publisher to neatly categories their data into this necessarily enormous scheme would have resulted in countless errors all over the web that would have seriously undercut the utility of the project anyway. Ultimately the semantic web doesn't scale very well. It failed for the same reason command economies fail: It's too overwhelming for the people in control to manage and drowns in its own bureaucracy.

Cyc[0] tried for 40 years to make handwritten semantic rules a thing, but still don't have much to show for. Humans just aren't good or fast at writing down the rather fuzzy semantics of the real world into a computer readable format.

With RDF specially, there was also the issue of "WTF is this good for?". Semantic Web sounds lofty in theory, but was there ever even a clear plan on how the UI would look like? How would I explore all that semantic data if it ever came into existence? How would it deal with link rot?

And much like with RSS, I think a big failure of RDF is that it's some weird thing outside the Web, instead of just some addition HTML tags to enrich existing documents. If there is a failure, it's that. Even today, a lot of basic semantic tags are missing from HTML, we finally got in 2011, but we still have nothing for names, cities, units, books[1], movie, gps coordinates and a lot of other stuff we use daily.

Another big failure is that HTML has become a read-only format, the idea that one uses HTML as a source format to publish documents seems to have been completely abandoned. HTML is just a UI language for Web apps nowadays, Markdown, LaTeX or whatever is what one uses to write content.

0. https://en.wikipedia.org/wiki/Cyc

1. exists, but browsers don't support it natively