Amateur Mathematicians Find Fifth ‘Busy Beaver’ Turing Machine | Quanta Magazine
The mathematics behind the halting problem is interesting enough, but what’s really fascinating is the community that coalesced. A republic of numbers.
Link tags: computation
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In new AI hype frenzy, tech is applying the label to everything now
Today’s AI promoters are trying to have it both ways: They insist that AI is crossing a profound boundary into untrodden territory with unfathomable risks. But they also define AI so broadly as to include almost any large-scale, statistically-driven computer program.
Under this definition, everything from the Google search engine to the iPhone’s face-recognition unlocking tool to the Facebook newsfeed algorithm is already “AI-driven” — and has been for years.
The man who tried to redeem the world with logic - Big Think
The fascinating—and tragic—story of Walter Pitts and Walter McCulloch whose lives and work intersected with Norbert Wiener and John von Neumann:
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.
Why Computers Won’t Make Themselves Smarter | The New Yorker
In this piece published a year ago, Ted Chiang pours cold water on the idea of a bootstrapping singularity.
How much can you optimize for generality? To what extent can you simultaneously optimize a system for every possible situation, including situations never encountered before? Presumably, some improvement is possible, but the idea of an intelligence explosion implies that there is essentially no limit to the extent of optimization that can be achieved. This is a very strong claim. If someone is asserting that infinite optimization for generality is possible, I’d like to see some arguments besides citing examples of optimization for specialized tasks.
Making Reasonable Use of Computer Resources
The paradox of performance:
This era of incredibly fast hardware is also the era of programs that take tens of seconds to start from an SSD or NVMe disk; of bloated web applications that take many seconds to show a simple list, even on a broadband connection; of programs that process data at a thousandth of the speed we should expect. Software is laggy and sluggish — and the situation shows little signs of improvement. Why is that?
Because we prioritise the developer experience over the user experience, that’s why:
Although our job is ostensibly to create programs that let users do stuff with their computers, we place a greater emphasis on the development process and dev-oriented concerns than on the final user product.
We would do well to heed Craig’s observations on Fast Software, the Best Software.
A Black Cloud of Computation
SETI—the Search for Extra Terrestrial Information processing:
What we get is a computational device surrounding the Asymptotic Giant Branch star that is roughly the size of our Solar System.
The Economics of the Front-End - Jim Nielsen’s Weblog
I do think large tech companies employ JavaScript frameworks because, amongst other things, it saves them money at their scale. And what Big Tech does trickles down in the form of default choices for many others (“they’re doing it and are insanely successful, so mimicking them can’t be a bad idea”). However, the scale at which smaller projects operate doesn’t necessarily translate to the same kind of cost savings.
Beyond Smart Rocks
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.
Reflections on software performance - Made of Bugs
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.
28c3: The Science of Insecurity - YouTube
I understand less than half of this great talk by Meredith L. Patterson, but it ticks all my boxes: Leibniz, Turing, Borges, and Postel’s Law.
(via Tim Berners-Lee)
Artificial Intelligence: Threat or Menace? - Charlie’s Diary
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 Chimero · Tweenage Computing
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?
At Dynamicland, The Building Is The Computer — Carl Tashian
A look at the ubiquitous computing work that Bret Victor has been doing over the past few years at Dynamicland.
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.
Turing Tumble - Build Marble-Powered Computers
Boolean logic manifested in a Turing-complete game
Is CSS Turing Complete? | Lara Schenck
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.
Hidden Heroines of Chaos: Ellen Fetter and Margaret Hamilton | Quanta Magazine
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.
Norbert Wiener’s Human Use of Human Beings is more relevant than ever.
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.
The Case Against Quantum Computing - IEEE Spectrum
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.
Ways to think about machine learning — Benedict Evans
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.