Tags: model

16

sparkline

Thursday, March 23rd, 2023

Steam

Picture someone tediously going through a spreadsheet that someone else has filled in by hand and finding yet another error.

“I wish to God these calculations had been executed by steam!” they cry.

The year was 1821 and technically the spreadsheet was a book of logarithmic tables. The frustrated cry came from Charles Babbage, who channeled his frustration into a scheme to create the world’s first computer.

His difference engine didn’t work out. Neither did his analytical engine. He’d spend his later years taking his frustrations out on street musicians, which—as a former busker myself—earns him a hairy eyeball from me.

But we’ve all been there, right? Some tedious task that feels soul-destroying in its monotony. Surely this is exactly what machines should be doing?

I have a hunch that this is where machine learning and large language models might turn out to be most useful. Not in creating breathtaking works of creativity, but in menial tasks that nobody enjoys.

Someone was telling me earlier today about how they took a bunch of haphazard notes in a client meeting. When the meeting was done, they needed to organise those notes into a coherent summary. Boring! But ChatGPT handled it just fine.

I don’t think that use-case is going to appear on the cover of Wired magazine anytime soon but it might be a truer glimpse of the future than any of the breathless claims being eagerly bandied about in Silicon Valley.

You know the way we no longer remember phone numbers, because, well, why would we now that we have machines to remember them for us? I’d be quite happy if machines did that for the annoying little repetitive tasks that nobody enjoys.

I’ll give you an example based on my own experience.

Regular expressions are my kryptonite. I’m rubbish at them. Any time I have to figure one out, the knowledge seeps out of my brain before long. I think that’s because I kind of resent having to internalise that knowledge. It doesn’t feel like something a human should have to know. “I wish to God these regular expressions had been calculated by steam!”

Now I can get a chatbot with a large language model to write the regular expression for me. I still need to describe what I want, so I need to write the instructions clearly. But all the gobbledygook that I’m writing for a machine now gets written by a machine. That seems fair.

Mind you, I wouldn’t blindly trust the output. I’d take that regular expression and run it through a chatbot, maybe a different chatbot running on a different large language model. “Explain what this regular expression does,” would be my prompt. If my input into the first chatbot matches the output of the second, I’d have some confidence in using the regular expression.

A friend of mine told me about using a large language model to help write SQL statements. He described his database structure to the chatbot, and then described what he wanted to select.

Again, I wouldn’t use that output without checking it first. But again, I might use another chatbot to do that checking. “Explain what this SQL statement does.”

Playing chatbots off against each other like this is kinda how machine learning works under the hood: generative adverserial networks.

Of course, the task of having to validate the output of a chatbot by checking it with another chatbot could get quite tedious. “I wish to God these large language model outputs had been validated by steam!”

Sounds like a job for machines.

Wednesday, March 15th, 2023

Stochastic Parrots Day Tickets, Fri, Mar 17, 2023 at 8:00 AM | Eventbrite

This free event is running online from 3pm to 7pm UK time this Friday. The line-up features Emily Bender, Safiya Noble, Timnit Gebru and more.

Since the publication of On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?🦜 two years ago, many of the harms the paper has warned about and more, have unfortunately occurred. From exploited workers filtering hateful content, to an engineer claiming that chatbots are sentient, the harms are only accelerating.

Join the co-authors of the paper and various guests to reflect on what has happened in the last two years, what the large language model landscape currently look like, and where we are headed vs where we should be headed.

Monday, September 26th, 2022

Fermented Code: Modelling the Microbial Through Miso - Serpentine Galleries

Y’know, I started reading this great piece by Claire L. Evans thinking about its connections to systems thinking, but I ended up thinking more about prototyping. And microbes.

Friday, June 12th, 2020

Friday, August 9th, 2019

Meaning without markup: Accessibility Object Model

Hidde gives an in-depth explanation of the Accessibility Object Model, coming soon to browsers near you:

In a way, that’s a bit like what Service Workers do for the network and Houdini for style: give developers control over something that was previously done only by the browser.

Wednesday, May 29th, 2019

Sunday, January 13th, 2019

Teaching a Correct CSS Mental Model

One facet of this whole CSS debate involves one side saying, “Just learn CSS” and the other side responding, “That’s what I’ve been trying to do!”

I think it’s high time we the teachers of CSS start discussing how exactly we can teach a correct mental model. How do we, in specific and practical ways, help developers get past this point of frustration. Because we have not figured out how to properly teach a mental model of CSS.

Wednesday, July 18th, 2018

Thinking in Triplicate – Mule Design Studio – Medium

Erika has written a great guest post on Ev’s blog. It covers the meaning, the impact, and the responsibility of design …and how we’ve been chasing the wrong measurements of success.

We design for the experience of a single user at a time and expect that the collective experience, and the collective impact, will take care of itself.

Saturday, April 15th, 2017

The invisible parts of CSS · MadebyMike

This is a really clear explanation of how CSS works.

Saturday, June 23rd, 2012

KyleBean.co.uk - Portfolio: Mobile Evolution

Kyle’s Matryoshka phones are as cool as they are cute.

Friday, January 11th, 2008

KnickerPicker - online dressing room

A Flash interface that allows you to interact with lingerie models when shopping for knickers. I point this out purely for reasons of interaction research, of course.

Thursday, September 27th, 2007

Amazon: A Quick Tour of Our New Remodel

Amazon is AB testing their next design iteration. Bye, bye tabs (yay!), hello fly-out menus (boo!).

Sunday, July 2nd, 2006

Overcaffeinated : Photography

That Sergio is one lucky stiff(y).

Wednesday, March 1st, 2006

Flickr: The Tilt-shift miniature fakes Pool

Take a photograph of something big and blur the foreground and background, leaving a narrow strip in focus. The result looks like a macro shot of a model.

DSC01116

Monday, January 30th, 2006

LIFEBLOG.anina.net: slides gave me an ultimatum

Anina, the blogging model, is told by her agency to stop blogging because "fashion and technology do not go together". Asshats.

Friday, September 2nd, 2005

Glenn Feron - The Art of Retouching

Airbrushing with Photoshop.