Claire L. Evans on computational slime molds and other forms of unconvential computing that look beyond silicon:
In moments of technological frustration, it helps to remember that a computer is basically a rock. That is its fundamental witchcraft, or ours: for all its processing power, the device that runs your life is just a complex arrangement of minerals animated by electricity and language. Smart rocks.
I’ve really come to appreciate that performance isn’t just some property of a tool independent from its functionality or its feature set. Performance — in particular, being notably fast — is a feature in and of its own right, which fundamentally alters how a tool is used and perceived.
This is a fascinating look into how performance has knock-on effects beyond the obvious:
It’s probably fairly intuitive that users prefer faster software, and will have a better experience performing a given task if the tools are faster rather than slower.
What is perhaps less apparent is that having faster tools changes how users use a tool or perform a task.
This observation is particularly salient for web developers:
We have become accustomed to casually giving up factors of two or ten or more with our choices of tools and libraries, without asking if the benefits are worth it.
I am not a believer in the AI singularity — the rapture of the nerds — that is, in the possibility of building a brain-in-a-box that will self-improve its own capabilities until it outstrips our ability to keep up. What CS professor and fellow SF author Vernor Vinge described as “the last invention humans will ever need to make”. But I do think we’re going to keep building more and more complicated, systems that are opaque rather than transparent, and that launder our unspoken prejudices and encode them in our social environment. As our widely-deployed neural processors get more powerful, the decisions they take will become harder and harder to question or oppose. And that’s the real threat of AI — not killer robots, but “computer says no” without recourse to appeal.
Frank yearns for just-in-time computing:
With each year that goes by, it feels like less and less is happening on the device itself. And the longer our work maintains its current form (writing documents, updating spreadsheets, using web apps, responding to emails, monitoring chat, drawing rectangles), the more unnecessary high-end computing seems. Who needs multiple computers when I only need half of one?
A bit of a tangent, but I love this description of reading maps:
Map reading is a complex and uniquely human skill, not at all obvious to a young child. You float out of your body and into the sky, leaving behind the point of view you’ve been accustomed to all your life. Your imagination turns squiggly blue lines and green shading into creeks, mountains, and forests seen from above. Bringing it all together in your mind’s eye, you can picture the surroundings.
Boolean logic manifested in a Turing-complete game
This starts as a good bit of computer science nerdery, that kind of answers the question in the title:
Alone, CSS is not Turing complete. CSS plus HTML plus user input is Turing complete!
And so the takeaway here is bigger than just speculation about Turing completeness:
Given that CSS is a domain-specific language for styling user interface, this makes a lot of sense! CSS + HTML + Human = Turing complete.
At the end of that day, as CSS developers that is the language we really write. CSS is incomplete without HTML, and a styled interface is incomplete without a human to use it.
Before leading the software project that put men on the moon, Margaret Hamilton worked on the equations that led to chaos theory, followed by Mount Holyoke graduate, Ellen Fetter.
What would Wiener think of the current human use of human beings? He would be amazed by the power of computers and the internet. He would be happy that the early neural nets in which he played a role have spawned powerful deep-learning systems that exhibit the perceptual ability he demanded of them—although he might not be impressed that one of the most prominent examples of such computerized Gestalt is the ability to recognize photos of kittens on the World Wide Web.
This is the best explanation of quantum computing I’ve read. I mean, it’s not like I can judge its veracity, but I could actually understand it.
This strikes me as a sensible way of thinking about machine learning: it’s like when we got relational databases—suddenly we could do more, quicker, and easier …but it doesn’t require us to treat the technology like it’s magic.
An important parallel here is that though relational databases had economy of scale effects, there were limited network or ‘winner takes all’ effects. The database being used by company A doesn’t get better if company B buys the same database software from the same vendor: Safeway’s database doesn’t get better if Caterpillar buys the same one. Much the same actually applies to machine learning: machine learning is all about data, but data is highly specific to particular applications. More handwriting data will make a handwriting recognizer better, and more gas turbine data will make a system that predicts failures in gas turbines better, but the one doesn’t help with the other. Data isn’t fungible.
An interesting Xerox-PARC-like project dedicated to making a programmable platform out of paper and other physical objects.
A humane dynamic medium embraces the countless ways in which human beings use their minds and bodies, instead of cramming people into a tiny box of pixels.
Philip Ball certainly has a way with words.
It is a sad and beautiful world.
Thanks to their work, there was a moment in history when neuroscience, psychiatry, computer science, mathematical logic, and artificial intelligence were all one thing, following an idea first glimpsed by Leibniz—that man, machine, number, and mind all use information as a universal currency. What appeared on the surface to be very different ingredients of the world—hunks of metal, lumps of gray matter, scratches of ink on a page—were profoundly interchangeable.
Always worth bearing in mind when some perspective is needed.
If it is possible that our future species will go on to create simulations of our civilisation forerunners (us), then it is far more likely that we are currently in such a simulation than not.
Yet another brilliant far-ranging talk from Bret Victor.
I’ve tried to get him to come and speak at dConstruct for the past few years, but alas, with no success.
A wonderful presentation by time-traveller Bret Viktor.
Thoughts on artificial intelligence, computation and complexity.