Link tags: mac

Just Another Music Monday - by Rusty Foster - Today in Tabs

I don’t read Today in Tabs with any expectation of insight (it’s more like a junk-food guilty pleasure), but these two remarks stand out for their clarity and correctness:

The more I hear people selling AI encouraging everyone to be scared of AI, the more certain I am that it’s nothing to worry about. A few months ago the same people were all shilling crypto.

And:

AI images were fascinating in the Deep Dream eyeballs everywhere era. The “better” AI gets, the blander its output becomes, and the more obvious and unacceptable its errors. We’ve already seen peak AI, and the only interesting use of it will continue to be in generating novel failure modes for human artists to explore.

The Illusion Of Developer “Productivity” Opens The Door To Snake Oil – Codemanship’s Blog

There are a lot of astute observations in here.

AI is not a paradigm shift. But it could be useful

What’s going to happen is this: in a few years, AI will come crashing down as everyone realizes it’s not going to be an evolution of human consciousness, and some other new technology will take its place. Valuations of AI companies will fall and some will go out of business. Then, some of the actual uses of the technology will become apparent and it’ll be a mainstream, but not dominant, part of the technology landscape.

The hype cycle is well-understood. What surprises me, again and again, is how thoroughly people follow it. Across industries, CEOs are right now thinking, “holy shit, if we don’t jump on AI, we’re going to be completely left behind. This is a paradigm shift.”

Statement on Generative AI | Ben Myers

I endorse this statement.

We’re still not innovating with AI-generated UI.

Prototypes and production:

It looks like it will be a great tool for prototyping. A tool to help developers that don’t have experience with CSS and layout to have a starting point. As someone who spent some time building smoke and mirrors prototypes for UX research, I welcome tools like this.

What concerns me is the assertion that this is production-grade code when it simply is not.

Squish Meets Structure: Designing with Language Models

The slides and transcript from a great talk by Maggie Appleton, including this perfect description of the vibes we get from large language models:

It feels like they’re either geniuses playing dumb or dumb machines playing genius, but we don’t know which.

Making Large Language Models work for you

Another great talk from Simon that explains large language models in a hype-free way.

Documentation for GPTBot - OpenAI API

Now that the horse has bolted—and ransacked the web—you can shut the barn door:

To disallow GPTBot to access your site you can add the GPTBot to your site’s robots.txt:

User-agent: GPTBot
Disallow: /

“If It Sounds Like Sci-Fi, It Probably Is”

Emily M. Bender:

I dislike the term because “artificial intelligence” suggests that there’s more going on than there is, that these things are autonomous thinking entities rather than tools and simply kinds of automation. If we focus on them as autonomous thinking entities or we spin out that fantasy, it is easier to lose track of the people in the picture, both the people who should be accountable for what the systems are doing and the people whose labor and data are being exploited to create them in the first place.

Alternative terms:

• Stochastic parrots
• Spicy autocomplete
• Mad Libs
• Magic Eight Ball

And this is worth shouting from the rooftops:

The threat is not the generative “AI” itself. It’s the way that management might choose to use it.

Catching up on the weird world of LLMs

This is a really clear, practical, level-headed explanatory talk from Simon. You can read the transcript or watch the video.

Pulling my site from Google over AI training – Tracy Durnell

I’m not down with Google swallowing everything posted on the internet to train their generative AI models.

A principled approach to evolving choice and control for web content

This would mean a lot more if it happened before the wholesale harvesting of everyone’s work.

But I’m sure Google will put a mighty fine lock on that stable door that the horse bolted from.

Fruit Of The Poisonous LLaMA? – Terence Eden’s Blog

I want to live in a future where Artificial Intelligences can relieve humans of the drudgery of labour. But I don’t want to live in a future which is built by ripping-off people against their will.

How to report better on artificial intelligence - Columbia Journalism Review

• Be skeptical of PR hype
• Question the training data
• Evaluate the model
• Consider downstream harms

The LLMentalist Effect: how chat-based Large Language Models replicate the mechanisms of a psychic’s con

Taken together, these flaws make LLMs look less like an information technology and more like a modern mechanisation of the psychic hotline.

Delegating your decision-making, ranking, assessment, strategising, analysis, or any other form of reasoning to a chatbot becomes the functional equivalent to phoning a psychic for advice.

Imagine Google or a major tech company trying to fix their search engine by adding a psychic hotline to their front page? That’s what they’re doing with Bard.

Word Count 53: The state of AI and the Goodreads fiasco

Could the tsunami of AI shite turn out to be a flash flood? Might the models rapidly degrade into uselessness or soon be sued or blocked out of existence? Will users rebel as their experience of the internet is degraded?

In my most optimistic moments, I find myself hoping that the whole AI edifice will come tumbling down as tools disintegrate, people realise how unreliable they are, and how valuable human-generated and curated information really is. But it’s not a safe bet.

Introducing AI Help: Your Trusted Companion for Web Development | MDN Blog

As part of this pointless push, an “AI explain” button appeared on MDN articles. This terrible idea actually got pushed to production (bypassing the usual deploy steps) where it lasted less than a day.

You can read the havoc it wreaked in the short term. We’ll find out how much long-term damage it has done to trust in Mozilla and MDN.

This may be the worst use of a large language model I’ve seen since synthentic users (if you click that link, no it’s not a joke: “user research without the users” is what they’re actually proposing).

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.

A prayer wheel for capitalism

Why “AI” won’t help you get past the blank page in any meaningful way:

The value in writing lies in what we discover while writing.

Will GPT models choke on their own exhaust? | Light Blue Touchpaper

There’s a general consensus that large language models are going to get better and better. But what if this as good as it gets …before the snake eats its own tail?

The tails of the original content distribution disappear. Within a few generations, text becomes garbage, as Gaussian distributions converge and may even become delta functions. We call this effect model collapse.

Just as we’ve strewn the oceans with plastic trash and filled the atmosphere with carbon dioxide, so we’re about to fill the Internet with blah. This will make it harder to train newer models by scraping the web, giving an advantage to firms which already did that, or which control access to human interfaces at scale.