No, the blinking cursor is a feature, not a bug. Alec Watons over at Technology Connections has a much better argument for this than I could ever hope to muster, so I'll just hand it over to him:

https://www.youtube.com/watch?v=QEJpZjg8GuA

This is a tantalizing problem for me as a UX designer. My approach, which I'm quite proud of, places a UI primitive (Todo lists) center stage, with the chat thread on the side similar to Canvas or Claude's Artifacts. The interaction works like this:

1. User gets shown a list GUI based on their requirement (Meal Planning, Shopping List...) 2. Users speak directly to the list while the LLM listens in realtime 3. The LLM acknowledges with emojis that flash to confirm understanding 4. The LLM creates, updates or deletes the list items in turn (stored in localStorage or a Durable Object -> shout out https://tinybase.org/)

The lists are React components, designed to be malleable. They can be re-written in-app by the LLM, while still taking todos. The react code also provide great context for the LLM — a shared contract between user and AI. I'm excited to experiment with streaming real-time screenshots of user interactions with the lists for even deeper mind-melding.

I believe the cursor and chat thread remain critical. They ground the user and visually express the shared context between LLM and user. And of course, all these APIs are fundamentally structured around sequential message exchanges. So it will be an enduring UI pattern.

If you're curious I have a demo here -> https://app.tinytalkingtodos.com/

> Once you’ve overcome the intimidation of the blinking cursor and typed something in, one of the next obstacles you’ll likely meet is the lack of clarity regarding the overall capabilities of these general-purpose AI systems.

The article presents this as a UX problem, but isn't this actually a much deeper issue? We straight up don't know what those models can and cannot do (I.e. which tasks can be reliably done with high levels of correctness and which tasks will just lead to endless hallucinations) because the mechanism by which the models generalize tasks is still not fully understood. This stuff is still an active area of research.

A chat interface is great in the sense that it's open, flexible and intuitive.

The downside is there's a tendency to anthropomorphise AI, and you might not want to talk to your computer: it takes too long to explain all the details, can be clunky for certain tasks and as the author argues actually limiting if you don't already know what it can do.

There's a need to get past the "Turing test" phase and integrate AI into more workflows so that chat is one interface among many options depending on the job to be done.

Yep, we can build the Artificial Static Place Intelligence – instead of creating AI/AGI agents that are like librarians who only give you quotes from books and don’t let you enter the library itself to read the whole books. Why not expose the whole library – the entire multimodal language model – to real people, for example, in a computer game?

To make this place easier to visit and explore, we could make a digital copy of our planet Earth and somehow expose the contents of the multimodal language model to everyone in a familiar, user-friendly UI of our planet.

We should not keep it hidden behind the strict librarian (AI/AGI agent) that imposes rules on us to only read little quotes from books that it spits out while it itself has the whole output of humanity stolen.

We can explore The Library without any strict guardian in the comfort of our simulated planet Earth on our devices, in VR, and eventually through some wireless brain-computer interface (it would always remain a game that no one is forced to play, unlike the agentic AI-world that is being imposed on us more and more right now and potentially forever)

These seem to mostly be a human problem.

Out of the large number of things you can do, most likely you're only consciously aware of a small number of them, and even among those, you're fairly likely to fall back on doing the things you've done before.

You could potentially do something new, something you haven't even considered doing that's wildly out of character, there's any number of such things you could do, but most likely you won't, you'll follow your routines and do the same proven things over and over again.

You Can Just Do Things (TM), sure, but first you need to have the idea of doing them. That's the difficult hard part, fishing an interesting idea out of the dizzying expanse of possibilities.

> These AI systems are not able to describe their own capabilities or strengths and are not aware of their limitations and weaknesses

I've experienced this with github copilot. At the beginning of a copilot chat, there's a short paragraph. It tells you to use "slash commands" for various purposes. I ask for a list of what slash commands are available. It responds by giving me a general definition of the term "slash command". No. I want to know which slash commands you support. Then it tells me it doesn't actually support slash commands.

I definitely feel like I'm falling into the non-power-user category described here in most of my AI interactions. So often I just end up arguing them in circles and them constantly agreeing and correcting, but never addressing my original goal.

> Back then very few people knew what to do when faced with this screen

In the '80s, you could go into any computer store and see what prior visitors had been up to with the machines on display.

And what you would very often find is evidence that the user before you had been trying to type English into the computer, to see whether it would converse, and that the user soon gave up after seeing nothing but error messages.

It was incredibly common. People who didn't know anything about computers harbored a misunderstanding that you could just chat with them, like Captain Kirk or Mr. Spock in Star Trek, and they tried exactly that at the keyboard.

Fast forward 40 years, and it finally works like they expect.

So anyway, chatting with a computer at the blinking cursor is entirely discoverable. And if there's a prompt there for the human saying something like "try asking me anything in plain English", then quadruply so.

Altavista replaced Yahoo. And then Google did it the same way. And this was without language interpretation. I agree with the sentiment, and I think it's easier for professionals to build muscle memory on a 2D layout rather than text fragments, but it all depends on the use-case. I think we'll move more into a scrolling history of small widgets that you fill out. I.e. the AI builds the user interface that's needed at this point in time.

Granted, Tomi Engdahl's electronics hub [1] was an amazing resource for discovering electronics.

[1] https://www.epanorama.net/

WhatsApp has the same blinking cursor, and everybody is happy with it.

I see some good points here but overall I disagree. Traditionally all UI have required people to adapt to how machines work. We need to memorize commands and navigate clunky interfaces that are painstakingly assembled (often unsuccessfully) by UX research and UI teams.

The chat reverses this. It is now machines adapting to how we communicate. I can see some UI sugar finding its way into this new way of interaction, but we should start over and force the change to keep it on our terms.

This is a good point. The blinking cursor at the end of the text encouraging me to make a new cleaning agent by mixing bleach and concentrated acetic acid is AI’s biggest flaw

For programming, the tooling and ui is progressing. Like reasoning models and tooling around them that makes sure to write unit tests, compile the code and try the tests. If wrong, redo the code again. This causes other ui problems yet to solve like longer iterations between user feedback but the ui problems are not for the lack of progression.

Why is it that now of all times, when we could actually make it useful, Clippy has not returned to ask, "It looks like you're trying to X, would you like help with that?"

This seems true to get the most out of an LLM, but you could also say Google has this problem too.

Seems like not a huge stretch to apply how you use Google to LLMs and get good milage.

This seems a bit naive. There are no arguments given as to why things would be better if the AI is more like a human.

Just look at how the world works: we all read and write crazy little symbols, which take children years to understand. We type on keyboards with over 100 small buttons, and train everyone to be a piano player.

And you want AI to be more like that, i.e. like humans? Sorry, but I guess I'd rather see AI evolve past our human limitations, and I'd be happy with a simple console output of the number 42.

Great article, Mistral CEO spoke about this issue, it's their main task now, figuring out the interface between IA and human.

I think one of the reasons why big corporations in this sector are still keeping this "open prompt" UI as a main one is to keep up pretense that these programs are actually thinking. After all, when we open a chat with another person, there are no action buttons, scripts or prerecorded routines, because humans don't work or don't talk like that. Programs on the other hand benefit greatly from the predefined lists of actions and operations. It is telling that currently the only advanced UI for the neural network program is a Copilot, which while being based on the same LLM as the other chats, is used and feels closer to a common program - IDE with autocomplete. So people using it are expecting more of the routines and action buttons.

tl;dr - neural network companies are employing artificial tricks and dark patterns to trick user into thinking there is intelligence on the other side of the glass.

I don't think that the blinking cursor is AI's biggest flaw. I think AI's biggest flaw is that it unethically stole millions of peoples work without compensation.

> More technical computer users are often happy to experiment (time permitting), whereas less technical or simply less confident users tend to have a fear of “getting it wrong”, informed by years of experience with unforgiving computer interfaces (yes, I’m looking at you Windows … and MacOS … and …) that punish users for their lack of understanding.

So AI's biggest flaw is, in reality, a flaw of other computer interfaces? I stopped reading after that.

> Every day I find myself reflecting on the gap between the ever-growing capability of AI, and the somewhat modest impact it is having on our day-to-day life.

Yeah but isn’t that because it actually is rather useless? It is not very capable?

If it is, why did no one person team disrupt and totally take over any market anywhere these past couple of years?

This pencil is unclear. Has pointy tip problem. Needs more examples.

The not-so-secret secret of software for the past 40 years is that it has, more often than not, provided solutions to problems created first and foremost by it. This is not pessimism or ludditism, I am just trying to say something simple. The spreadsheet or the database is something that is self-validating: the very innovation of the database makes it first and foremost possible to consolidate massive amounts of data in one place; the whole world can suddenly orient itself around this possibility, and then almost imperceptibly it presents itself to us as a kind of teleological end point, as a "solution to a problem." One can possibly reply here: well, people wanted all the data in one place, and they just had to figure out how to do it, so there you go, the database. But this belies, in an important (if admittedly more philosophical) way the specific character of how an innovation or technology evolves and ultimately concretizes into day to day life. This is why and how the iPhone was cool, but now most of us agree that having an app for your toaster or Taco Bell is pretty dumb. Now entire people's careers have been made around solutions to problems that only exist because of prior innovations. One might quibble that there is some kind of surplus of benefit at the end of the day, but that's not really the point.

Posts like these, along with sentiments we see from so many people now, show a kind of, if you will, crisis of identity. The plausible language black box, slop-bot, beautiful and promising proto-consciousness, whatever you want to call it, is unmoored from what was previously the fiery organic back-and-forth of capitalism<->tech. In part because it is not actually a response to problem, it is a kind of "discovery," but also in part because, it seems, it is in essence too general and too unstable to easily slot into one thing or another.

Now we have all these very business-oriented people looking at this thing, measuring the elephant, and saying "well gosh darn-it, there is something here, there just has to be." We are burning all these resources to get something, but I truly don't think people even know what they want at the end of the day, because it hasn't followed the same chain of commoditization like social media, databases, phones, etc.

This is why there is such confusion: is AI the thing itself, or the tool we use to get... something? How can something be so impressive but not, as it seems, so easily fitted into a product? I suspect this will continue to break peoples brains and empty investors pockets for a long time yet.

If I was an evil capitalist, I would work on a better narrative, or rather, work on actually articulating a problem that "was there all along," which the bots can then solve. I haven't really seen that in a substantial sense, and at this point I love the LLMs just for its resistance to such things.

Just to say, this whole blog post I think is quite exemplary of this contradiction.