ui ai
My supervisor asked me to fill out a career map, complete with long-term and short-term goals. Since I don’t have aspirations to become a manager, I thought I’d more clearly define my user interface design goals.
Since that long-term bit is in there, I thought I’d see if I could factor in artificial intelligence. Not necessarily the personal, ( Read more... )
Since that long-term bit is in there, I thought I’d see if I could factor in artificial intelligence. Not necessarily the personal, ( Read more... )
"Those types of aggregation applications you describe are often referred to as “dashboards” right now. They’re quite popular with management types. I’d probably steer clear of the term “AI” for obvious reasons, heh, but you could probably get a lot of mileage out of a reference to dashboards or maybe even intelligent dashboards. Another popular buzzword right now is business intelligence. Government types always like the appearance that they’re following business practices.
I’m not sure I get Dyson’s emphasis on “do this with that, but not where or when”… where and when are the problems to solve, not the parts we need to get rid of. Otherwise RSS aggregators and IMAP e-mail wouldn’t be so popular right now. His focus on addressing was solved a long time ago: relational databases. In fact, the web is a prime example of relational databases and flexible addressing. I can drop a website on any host and within certain real-world limitations, it’ll work the same way. I can have one or fifty domain names point to it - and move it around and they’ll still work. (The DNS system is just a database… the socket functions are actually named GetXByY.)
With that being said, I still think he’s on to something about von Neumann’s meaning/doing breakthrough, and the lack of a similarly-important shift. But it seems like the shift he’s describing is a separation between finding/understanding, and of course “understanding” is tremendously more complicated proposition than simply “doing”… and in some sense you could complicate it with an argument that “meaning” and “understanding” are not necessarily separate concepts…
He also seems to have a poor grasp of certain technical details. For instance, he attributes Google’s success to “ingenious algorithms”… when the reality is that Google’s success is mainly attributed to massive amounts of cheap computing horsepower - tens of thousands of low-cost second-hand PCs, literally. There are certainly ingenious algorithms involved, but they’re useless without massive, cheap computing power. It’s a combination of his second and third “sectors,” not a clear-cut case of the third as he seems to believe.
I love the close of that article…"
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