Tags: machine

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Saturday, July 4th, 2020

The Machines Stop

The Situation feels like it’s changing. It’s not over, not by a long shot. But it feels like it’s entering a different, looser phase.

Throughout the lockdown, there’s been a strange symmetry between the outside world and the inside of our home. As the outside world slowed to a halt, so too did half the machinery in our flat. Our dishwasher broke shortly before the official lockdown began. So did our washing machine.

We had made plans for repairs and replacements, but as events in the world outside escalated, those plans had to be put on hold. Plumbers and engineers weren’t making any house calls, and rightly so.

We even had the gas to our stovetop cut off for a while—you can read Jessica’s account of that whole affair. All the breakdowns just added to the entropic Ballardian mood.

But the gas stovetop was fixed. And so too was the dishwasher, eventually. Just last week, we got our new washing machine installed. Piece by piece, the machinery of our interier world revived in lockstep with the resucitation of the world outside.

As of today, pubs will be open. I won’t be crossing their thresholds just yet. We know so much more about the spread of the virus now, and gatherings of people in indoor spaces are pretty much the worst environments for transmission.

I’m feeling more sanguine about outdoor spaces. Yesterday, Jessica and I went into town for Street Diner. It was the first time since March that we walked in that direction—our other excursions have been in the direction of the countryside.

It was perfectly fine. We wore masks, and while we were certainly in the minority, we were not alone. People were generally behaving responsibly.

Brighton hasn’t done too badly throughout The Situation. But still, like I said, I have no plans to head to the pub on a Saturday night. The British drinking culture is very much concentrated on weekends. Stay in all week and then on the weekend, lassen die Sau raus!, as the Germans would say.

After months of lockdown, reopening pubs on a Saturday seems like a terrible idea. Over in Ireland, pubs have been open since Monday—a sensible day to soft-launch. With plenty of precautions in place, things are going well there.

I’ve been watching The Situation in Ireland throughout. It’s where my mother lives, so I was understandably concerned. But they’ve handled everything really well. It’s not New Zealand, but it’s also not the disaster that is the UK.

It really has been like watching an A/B test run at the country level. Two very similar populations confronted with exactly the same crisis. Ireland took action early, cancelling the St. Patrick’s Day parade(!) while the UK was still merrily letting Cheltenham go ahead. Ireland had clear guidance. The UK had dilly-dallying and waffling. And when the shit really hit the fan, the Irish taoiseach rolled up his sleeves and returned to medical work. Meanwhile the UK had Dominic Cummings making a complete mockery of the sacrifices that everyone was told to endure.

What’s strange is that people here in the UK don’t seem to realise how the rest of the world, especially other European countries, have watched the response here with shock and horror. The narrative here seems to be that we all faced this thing together, and with our collective effort, we averted the worst. But the numbers tell a very different story. Comparing the numbers here with the numbers in Ireland—or pretty much any other country in Europe—is sobering.

So even though the timelines for reopenings here converge with Ireland’s, The Situation is far from over.

Even without any trips to pubs, restaurants, or other indoor spaces, I’m looking forward to making some more excursions into town. Not that it’s been bad staying at home. I’ve really quite enjoyed staying put, playing music, reading books, and watching television.

I was furloughed from work for a while in June. Normally, my work at this time of year would involve plenty of speaking at conferences. Seeing as that wasn’t happening, it made sense to take advantage of the government scheme to go into work hibernation for a bit.

I was worried I might feel at a bit of a loose end, but I actually really enjoyed it. The weather was good so I spent quite a bit of time just sitting in the back garden, reading (I am very, very grateful to have even a small garden). I listened to music. I watched movies. I surfed the web. Yes, properly surfed the web, going from link to link, get lost down rabbit holes. I tell you, this World Wide Web thing is pretty remarkable. Some days I used it to read up on science or philosophy. I spent a week immersed in Napoleonic history. I have no idea how or why. But it was great.

I’m back at work now, and have been for a couple of weeks. But I wouldn’t mind getting furloughed again. It felt kind of like being retired. I’m quite okay with the propsect of retirement now, as long as we have music and sunshine and the World Wide Web.

That’s the future. For now, The Situation continues, albeit in looser form.

I’ve really enjoyed reading other people’s accounts throughout. My RSS reader is getting a good workout. I always look forward to weeknotes from Alice, Nat, and Phil (this piece from Phil has really stuck with me). Jessica has written fifteen installments—and counting—of A Journal of the Plague Week. I know I’m biased, but I think it’s some mighty fine writing. Start here.

Monday, December 16th, 2019

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.

Tuesday, December 10th, 2019

AI Weirdness • Play AI Dungeon 2. Become a dragon. Eat the moon.

After reading this account of a wonderfully surreal text adventure game, you’ll probably want to play AI Dungeon 2:

A PhD student named Nathan trained the neural net on classic dungeon crawling games, and playing it is strangely surreal, repetitive, and mesmerizing, like dreaming about playing one of the games it was trained on.

Friday, September 27th, 2019

To decarbonize we must decomputerize: why we need a Luddite revolution | Technology | The Guardian

Decomputerization doesn’t mean no computers. It means that not all spheres of life should be rendered into data and computed upon. Ubiquitous “smartness” largely serves to enrich and empower the few at the expense of the many, while inflicting ecological harm that will threaten the survival and flourishing of billions of people.

Friday, September 6th, 2019

Enigma machine / Tom MacWright / Observable

See how an Enigma machine works …and interact with it.

Letters to be encrypted enter at the boundary, move through the wire matrix, and exit.

Tuesday, August 27th, 2019

Voice User Interface Design by Cheryl Platz

Cheryl Platz is speaking at An Event Apart Chicago. Her inaugural An Event Apart presentation is all about voice interfaces, and I’m going to attempt to liveblog it…

Why make a voice interface?

Successful voice interfaces aren’t necessarily solving new problems. They’re used to solve problems that other devices have already solved. Think about kitchen timers. There are lots of ways to set a timer. Your oven might have one. Your phone has one. Why use a $200 device to solve this mundane problem? Same goes for listening to music, news, and weather.

People are using voice interfaces for solving ordinary problems. Why? Context matters. If you’re carrying a toddler, then setting a kitchen timer can be tricky so a voice-activated timer is quite appealing. But why is voice is happening now?

Humans have been developing the art of conversation for thousands of years. It’s one of the first skills we learn. It’s deeply instinctual. Most humans use speach instinctively every day. You can’t necessarily say that about using a keyboard or a mouse.

Voice-based user interfaces are not new. Not just the idea—which we’ve seen in Star Trek—but the actual implementation. Bell Labs had Audrey back in 1952. It recognised ten words—the digits zero through nine. Why did it take so long to get to Alexa?

In the late 70s, DARPA issued a challenge to create a voice-activated system. Carnagie Mellon came up with Harpy (with a thousand word grammar). But none of the solutions could respond in real time. In conversation, we expect a break of no more than 200 or 300 milliseconds.

In the 1980s, computing power couldn’t keep up with voice technology, so progress kind of stopped. Time passed. Things finally started to catch up in the 90s with things like Dragon Naturally Speaking. But that was still about vocabulary, not grammar. By the 2000s, small grammars were starting to show up—starting an X-Box or pausing Netflix. In 2008, Google Voice Search arrived on the iPhone and natural language interaction began to arrive.

What makes natural language interactions so special? It requires minimal training because it uses the conversational muscles we’ve been working for a lifetime. It unlocks the ability to have more forgiving, less robotic conversations with devices. There might be ten different ways to set a timer.

Natural language interactions can also free us from “screen magnetism”—that tendency to stay on a device even when our original task is complete. Voice also enables fast and forgiving searches of huge catalogues without time spent typing or browsing. You can pick a needle straight out of a haystack.

Natural language interactions are excellent for older customers. These interfaces don’t intimidate people without dexterity, vision, or digital experience. Voice input often leads to more inclusive experiences. Many customers with visual or physical disabilities can’t use traditional graphical interfaces. Voice experiences throw open the door of opportunity for some people. However, voice experience can exclude people with speech difficulties.

Making the case for voice interfaces

There’s a misconception that you need to work at Amazon, Google, or Apple to work on a voice interface, or at least that you need to have a big product team. But Cheryl was able to make her first Alexa “skill” in a week. If you’re a web developer, you’re good to go. Your voice “interaction model” is just JSON.

How do you get your product team on board? Find the customers (and situations) you might have excluded with traditional input. Tell the stories of people whose hands are full, or who are vision impaired. You can also point to the adoption rate numbers for smart speakers.

You’ll need to show your scenario in context. Otherwise people will ask, “why can’t we just build an app for this?” Conduct research to demonstrate the appeal of a voice interface. Storyboarding is very useful for visualising the context of use and highlighting existing pain points.

Getting started with voice interfaces

You’ve got to understand how the technology works in order to adapt to how it fails. Here are a few basic concepts.

Utterance. A word, phrase, or sentence spoken by a customer. This is the true form of what the customer provides.

Intent. This is the meaning behind a customer’s request. This is an important distinction because one intent could have thousands of different utterances.

Prompt. The text of a system response that will be provided to a customer. The audio version of a prompt, if needed, is generated separately using text to speech.

Grammar. A finite set of expected utterances. It’s a list. Usually, each entry in a grammar is paired with an intent. Many interfaces start out as being simple grammars before moving on to a machine-learning model later once the concept has been proven.

Here’s the general idea with “artificial intelligence”…

There’s a human with a core intent to do something in the real world, like knowing when the cookies in the oven are done. This is translated into an intent like, “set a 15 minute timer.” That’s the utterance that’s translated into a string. But it hasn’t yet been parsed as language. That string is passed into a natural language understanding system. What comes is a data structure that represents the customers goal e.g. intent=timer; duration=15 minutes. That’s sent to the business logic where a timer is actually step. For a good voice interface, you also want to send back a response e.g. “setting timer for 15 minutes starting now.”

That seems simple enough, right? What’s so hard about designing for voice?

Natural language interfaces are a form of artifical intelligence so it’s not deterministic. There’s a lot of ruling out false positives. Unlike graphical interfaces, voice interfaces are driven by probability.

How do you turn a sound wave into an understandable instruction? It’s a lot like teaching a child. You feed a lot of data into a statistical model. That’s how machine learning works. It’s a probability game. That’s where it gets interesting for design—given a bunch of possible options, we need to use context to zero in on the most correct choice. This is where confidence ratings come in: the system will return the probability that a response is correct. Effectively, the system is telling you how sure or not it is about possible results. If the customer makes a request in an unusual or unexpected way, our system is likely to guess incorrectly. That’s because the system is being given something new.

Designing a conversation is relatively straightforward. But 80% of your voice design time will be spent designing for what happens when things go wrong. In voice recognition, edge cases are front and centre.

Here’s another challenge. Interaction with most voice interfaces is part conversation, part performance. Most interactions are not private.

Humans don’t distinguish digital speech fom human speech. That means these devices are intrinsically social. Our brains our wired to try to extract social information, even form digital speech. See, for example, why it’s such a big question as to what gender a voice interface has.

Delivering a voice interface

Storyboards help depict the context of use. Sample dialogues are your new wireframes. These are little scripts that not only cover the happy path, but also your edge case. Then you reverse engineer from there.

Flow diagrams communicate customer states, but don’t use the actual text in them.

Prompt lists are your final deliverable.

Functional prototypes are really important for voice interfaces. You’ll learn the real way that customers will ask for things.

If you build a working prototype, you’ll be building two things: a natural language interaction model (often a JSON file) and custom business logic (in a programming language).

Eventually voice design will become a core competency, much like mobile, which was once separate.

Ask yourself what tasks your customers complete on your site that feel clunkly. Remember that voice desing is almost never about new scenarious. Start your journey into voice interfaces by tackling old problems in new, more inclusive ways.

May the voice be with you!

Sunday, April 28th, 2019

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.

Tuesday, January 22nd, 2019

What would a world without pushbuttons look like? | Aeon Essays

A history of buttons …and the moral panic and outrage that accompanies them.

By looking at the subtexts behind complaints about buttons, whether historically or in the present moment, it becomes clear that manufacturers, designers and users alike must pay attention to why buttons persistently engender critiques. Such negativity tends to involve one of three primary themes: fears over deskilling; frustration about lack of user agency/control; or anger due to perceptions of unequal power relations.

Tuesday, November 13th, 2018

Optimise without a face

I’ve been playing around with the newly-released Squoosh, the spiritual successor to Jake’s SVGOMG. You can drag images into the browser window, and eyeball the changes that any optimisations might make.

On a project that Cassie is working on, it worked really well for optimising some JPEGs. But there were a few images that would require a bit more fine-grained control of the optimisations. Specifically, pictures with human faces in them.

I’ve written about this before. If there’s a human face in image, I open that image in a graphics editing tool like Photoshop, select everything but the face, and add a bit of blur. Because humans are hard-wired to focus on faces, we’ll notice any jaggy artifacts on a face, but we’re far less likely to notice jagginess in background imagery: walls, materials, clothing, etc.

On the face of it (hah!), a browser-based tool like Squoosh wouldn’t be able to optimise for faces, but then Cassie pointed out something really interesting…

When we were both at FFConf on Friday, there was a great talk by Eleanor Haproff on machine learning with JavaScript. It turns out there are plenty of smart toolkits out there, and one of them is facial recognition. So I wonder if it’s possible to build an in-browser tool with this workflow:

  • Drag or upload an image into the browser window,
  • A facial recognition algorithm finds any faces in the image,
  • Those portions of the image remain crisp,
  • The rest of the image gets a slight blur,
  • Download the optimised image.

Maybe the selecting/blurring part would need canvas? I don’t know.

Anyway, I thought this was a brilliant bit of synthesis from Cassie, and now I’ve got two questions:

  1. Does this exist yet? And, if not,
  2. Does anyone want to try building it?

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.

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.

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.

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 “+”.