Link tags: machine



“Artificial Intelligence & Humanity,” an article by Dan Mall

AI is great anything quantity-related and bad and anything quality-related.

Sensible thinking from Dan here, that mirrors what we’re thinking at Clearleft.

In other words, it leans heavily on averages; the closer the training data matches an average, the higher degree of confidence that the result is more “correct,” or at least desirable.

The problem is that this is the polar opposite of what we consider creativity to be. Creativity isn’t about averages. It’s about the outliers, sometimes the one thing that’s different than all the rest.

Generative AI: What You Need To Know

Generative AI: What You Need To Know is a free resource that will help you develop an AI-bullshit detector.

You can read all the cards on one page, print them out, or print to PDF.

ChatGPT is not ‘artificial intelligence.’ It’s theft. | America Magazine

But in calling these programs “artificial intelligence” we grant them a claim to authorship that is simply untrue. Each of those tokens used by programs like ChatGPT—the “language” in their “large language model”—represents a tiny, tiny piece of material that someone else created. And those authors are not credited for it, paid for it or asked permission for its use. In a sense, these machine-learning bots are actually the most advanced form of a chop shop: They steal material from creators (that is, they use it without permission), cut that material into parts so small that no one can trace them and then repurpose them to form new products.

How you want me to cover artificial intelligence

Seven principles for journalism in the age of AI

  1. Be rigorous with your definitions.
  2. Predict less, explain more.
  3. Don’t hype things up.
  4. Focus on the people building AI systems — and the people affected by its release.
  5. Offer strategic takes on products.
  6. Emphasize the tradeoffs involved.
  7. Remember that nothing is inevitable.

To have “true AI,” we need much more than ChatGPT - Big Think

LLMs have never experienced anything. They are just programs that have ingested unimaginable amounts of text. LLMs might do a great job at describing the sensation of being drunk, but this is only because they have read a lot of descriptions of being drunk. They have not, and cannot, experience it themselves. They have no purpose other than to produce the best response to the prompt you give them.

This doesn’t mean they aren’t impressive (they are) or that they can’t be useful (they are). And I truly believe we are at a watershed moment in technology. But let’s not confuse these genuine achievements with “true AI.”

AI isn’t the app, it’s the UI - Stack Overflow Blog

In some ways, the fervor around AI is reminiscent of blockchain hype, which has steadily cooled since its 2021 peak. In almost all cases, blockchain technology serves no purpose but to make software slower, more difficult to fix, and a bigger target for scammers. AI isn’t nearly as frivolous—it has several novel use cases—but many are rightly wary of the resemblance. And there are concerns to be had; AI bears the deceptive appearance of a free lunch and, predictably, has non-obvious downsides that some founders and VCs will insist on learning the hard way.

This is a good level-headed overview of how generative language model tools work.

If something can be reduced to patterns, however elaborate they may be, AI can probably mimic it. That’s what AI does. That’s the whole story.

There’s very practical advice on deciding where and when these tools make sense:

The sweet spot for AI is a context where its choices are limited, transparent, and safe. We should be giving it an API, not an output box.

Why Chatbots Are Not the Future by Amelia Wattenberger

Of course, users can learn over time what prompts work well and which don’t, but the burden to learn what works still lies with every single user. When it could instead be baked into the interface.

Talk: The Expanding Dark Forest and Generative AI

Maggie Appleton:

An exploration of the problems and possible futures of flooding the web with generative AI content.

The one about AI -

Writing, both code and prose, for me, is both an end product and an end in itself. I don’t want to automate away the things that give me joy.

And that is something that I’m more and more aware of as I get older – sources of joy. It’s good to diversify them, to keep track of them, because it’s way too easy to run out. Or to end up with just one, and then lose it.

The thing about luddites is that they make good punchlines, but they were all people.

The Technium: Dreams are the Default for Intelligence

I feel like there’s a connection here between what Kevin Kelly is describing and what I wrote about guessing (though I think he might be conflating consciousness with intelligence).

This, by the way, is also true of immersive “virtual reality” environments. Instead of trying to accurately recreate real-world places like meeting rooms, we should be leaning into the hallucinatory power of a technology that can generate dream-like situations where the pleasure comes from relinquishing control.

The Intelligence Illusion

Baldur has new book coming out:

The Intelligence Illusion is an exhaustively researched guide to the business risks of Generative AI.

LukeW | Ask LukeW: New Ways into Web Content

I like how Luke is using a large language model to make a chat interface for his own content.

This is the exact opposite of how grifters are selling the benefits of machine learning (“Generate copious amounts of new content instantly!”) and instead builds on over twenty years of thoughtful human-made writing.

Welcome to the Artificial Intelligence Incident Database

The AI Incident Database is dedicated to indexing the collective history of harms or near harms realized in the real world by the deployment of artificial intelligence systems.

We need to tell people ChatGPT will lie to them, not debate linguistics

There’s a time for linguistics, and there’s a time for grabbing the general public by the shoulders and shouting “It lies! The computer lies to you! Don’t trust anything it says!”

The machines won’t save your design system — Hey Jovo Design

Every day, a new marketing email, Medium post, or VC who will leave Twitter when they’re cold in a body bag tells us that machine learning (ML, which they call AI because it sounds more expensive) is going to change the way we work. Doesn’t really matter what your job is. ML is going to read, write, code, and paint for us.

Naturally, the excitement around ML has found its way into the design systems community. There’s an apparent natural synergy between ML and design systems. Design systems practitioners are tantalized by the promise of even greater efficiency and scale. We wish a machine would write our docs for us.

We are all, every single one of us, huge fucking nerds.

Why ChatGPT Won’t Replace Coders Just Yet

I’ve been using Copilot for over a year now, and this is more or less how I use it: To help me quickly blast through boilerplate code so I can more quickly get to the tricky bits.

There’s a more subtle problem with ChatGPT’s code generation, which is that it suffers from ChatGPT’s general “bullshit” problem.

Smoke screen | A Working Library

The story that “artificial intelligence” tells is a smoke screen. But smoke offers only temporary cover. It fades if it isn’t replenished.

The AI hype bubble is the new crypto hype bubble

A handy round-up of recent wrtings on artificial insemination.

Artificial Guessing

Artificial Intelligence sounds much more impressive than Artificial Guessing in a slide deck.

Robin picks up on my framing.

Instead of brainstorming, discussing, iterating, closely inspecting a product to understand it and figure out what to show on a page, well, we can just let the machines figure it out for us! This big guessing machine can do our homework and we can all pack up and go to the beach.

ongoing by Tim Bray · The LLM Problem

It doesn’t bother me much that bleeding-edge ML technology sometimes gets things wrong. It bothers me a lot when it gives no warnings, cites no sources, and provides no confidence interval.

Yes! Like I said:

Expose the wires. Show the workings-out.