Tags: mac

125

sparkline

Thursday, October 4th, 2018

Infovore » Pouring one out for the Boxmakers

This is a rather beautiful piece of writing by Tom (especially the William Gibson bit at the end). This got me right in the feels:

Web 2.0 really, truly, is over. The public APIs, feeds to be consumed in a platform of your choice, services that had value beyond their own walls, mashups that merged content and services into new things… have all been replaced with heavyweight websites to ensure a consistent, single experience, no out-of-context content, and maximising the views of advertising. That’s it: back to single-serving websites for single-serving use cases.

A shame. A thing I had always loved about the internet was its juxtapositions, the way it supported so many use-cases all at once. At its heart, a fundamental one: it was a medium which you could both read and write to. From that flow others: it’s not only work and play that coexisted on it, but the real and the fictional; the useful and the useless; the human and the machine.

Sunday, September 30th, 2018

CTS - conserve the sound

An online museum of sounds—the recordings of analogue machines.

Friday, September 28th, 2018

What is Modular CSS?

A walk down memory lane, looking at the history modular CSS methodologies (and the people behind them):

Thursday, July 12th, 2018

Unchained: A story of love, loss, and blockchain - MIT Technology Review

A near-future sci-fi short by Hannu Rajaniemi that’s right on the zeitgest money.

The app in her AR glasses showed the car icon crawling along the winding forest road. In a few minutes, it would reach the sharp right turn where the road met the lake. The turn was marked by a road sign she had carefully defaced the previous day, with tiny dabs of white paint. Nearly invisible to a human, they nevertheless fooled image recognition nets into classifying the sign as a tree.

Wednesday, July 11th, 2018

Disturbances #16: Digital Dust

From smart dust and spimes, through to online journaling and social media, to machine learning, big data and digital preservation…

Is the archive where information goes to live forever, or where data goes to die?

Tuesday, July 10th, 2018

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.

Tuesday, June 26th, 2018

Untold AI: The Untold | Sci-fi interfaces

Prompted by his time at Clearleft’s AI gathering in Juvet, Chris has been delving deep into the stories we tell about artificial intelligence …and what stories are missing.

And here we are at the eponymous answer to the question that I first asked at Juvet around 7 months ago: What stories aren’t we telling ourselves about AI?

Sunday, June 24th, 2018

Derek Powazek - AI is Not a Community Management Strategy

A really excellent piece from Derek on the history of community management online.

You have to decide what your platform is for and what it’s not for. And, yeah, that means deciding who it’s for and who it’s not for (hint: it’s not bots, nor nazis). That’s not a job you can outsource. The tech won’t do it for you. Not just because it’s your job, but because outsourcing it won’t work. It never does.

Tuesday, June 19th, 2018

[Essay] Known Unknowns | New Dark Age by James Bridle | Harper’s Magazine

A terrific cautionary look at the history of machine learning and artificial intelligence from the new laugh-a-minute book by James.

Saturday, June 16th, 2018

Artificial Intelligence for more human interfaces | Christian Heilmann

An even-handed assessment of the benefits and dangers of machine learning.

Monday, April 23rd, 2018

The Woman Who Gave the Macintosh a Smile | The New Yorker

A profile of Susan Kare, icon designer extraordinaire.

I loved the puzzle-like nature of working in sixteen-by-sixteen and thirty-two-by-thirty-two pixel icon grids, and the marriage of craft and metaphor.

Friday, April 6th, 2018

‘Black Mirror’ meets HGTV, and a new genre, home design horror, is born - Curbed

There was a time, circa 2009, when no home design story could do without a reference to Mad Men. There is a time, circa 2018, when no personal tech story should do without a Black Mirror reference.

Black Mirror Home. It’s all fun and games until the screaming starts.

When these products go haywire—as they inevitably do—the Black Mirror tweets won’t seem so funny, just as Mad Men curdled, eventually, from ha-ha how far we’ve come to, oh-no we haven’t come far enough.

Thursday, April 5th, 2018

Turning a MacBook into a Touchscreen with $1 of Hardware · cat /var/log/life

Well now, this is a clever bit of hardware hacking.

Surfaces viewed from an angle tend to look shiny, and you can tell if a finger is touching the surface by checking if it’s touching its own reflection.

Friday, March 9th, 2018

How To Become A Centaur

We hoped for a bicycle for the mind; we got a Lazy Boy recliner for the mind.

Nicky Case on how Douglas Engelbart’s vision for human-computer augmentation has taken a turn from creation to consumption.

When you create a Human+AI team, the hard part isn’t the “AI”. It isn’t even the “Human”.

It’s the “+”.

Thursday, March 1st, 2018

Fair Is Not the Default - Library - Google Design

Why building inclusive tech takes more than good intentions.

When we run focus groups, we joke that it’s only a matter of seconds before someone mentions Skynet or The Terminator in the context of artificial intelligence. As if we’ll go to sleep one day and wake up the next with robots marching to take over. Few things could be further from the truth. Instead, it’ll be human decisions that we made yesterday, or make today and tomorrow that will shape the future. So let’s make them together, with other people in mind.

Thursday, January 11th, 2018

Turning Design Mockups Into Code With Deep Learning - FloydHub Blog

Training a neural network to do front-end development.

I didn’t understand any of this.

Tuesday, January 9th, 2018

Trends in Digital Tech for 2018 - Peter Gasston

Peter looks into his crystal ball for 2018 and sees computers with eyes, computers with ears, and computers with brains.

Wednesday, October 11th, 2017

Failing to distinguish between a tractor trailer and the bright white sky | booktwo.org

James talks about automation and understanding.

Just because a technology – whether it’s autonomous vehicles, satellite communications, or the internet – has been captured by capital and turned against the populace, doesn’t mean it does not retain a seed of utopian possibility.

Tuesday, September 26th, 2017

Folklore.org: The Original Macintosh

Anecdotes about the development of Apple’s original Macintosh, and the people who made it.

Like a real-life Halt And Catch Fire.

Monday, June 12th, 2017

Design in the Era of the Algorithm | Big Medium

The transcript of Josh’s fantastic talk on machine learning, voice, data, APIs, and all the other tools of algorithmic design:

The design and presentation of data is just as important as the underlying algorithm. Algorithmic interfaces are a huge part of our future, and getting their design right is critical—and very, very hard to do.

Josh put together ten design principles for conceiving, designing, and managing data-driven products. I’ve added them to my collection.

  1. Favor accuracy over speed
  2. Allow for ambiguity
  3. Add human judgment
  4. Advocate sunshine
  5. Embrace multiple systems
  6. Make it easy to contribute (accurate) data
  7. Root out bias and bad assumptions
  8. Give people control over their data
  9. Be loyal to the user
  10. Take responsibility