Add "fucking" to your Google searches to neutralize AI summaries

> unless you believe millions of people are spending their own money every month for useless tech.

Your premise is wrong. You assume these people are spending money creating useful output or would otherwise understand and be able to implement a more efficient means on their own. In the words of David Graeber a lot of people have bullshit jobs, are you sure the "AI" isn't alleviating some other problem for them?

> and not see the possibilities it opens up.

The current technology has no natural exponential growth curve. Which means for a linear increase in spending you get a linear increase in accuracy. Any thinking person should see where this is going. Which is why you should call these LLMs so you don't accidentally fool yourself.

I mean, of course, when AGI does arrive and has a reasonable power budget, then we're talking. The current technology will never become this or anything like this. This will almost certainly lead to a new "AI winter" before AGI happens and will likewise almost certainly not occur during yours or my lifetime.

If you do believe that then I have a self driving battery powered semi to sell you that's fully autonomous and will run road cargo trains for you all day and night for huge profits.

You can probably find some other term that disables the AI but is unlikely to occur naturally in the articles you'd like to find, e.g.: "react swipeable image carousel -coprophilia".

Reading this headline made me think, there should be voting for most useful headline of the year.

I'm sure there's a time and place for these things, but this sounds very much like the echo chamber I hear at work all the time.

Someone has a 'friend' who has a totally-not-publically-visible form where a chat bot interacts with the form and helps the user fill the form in.

...and users love it.

However, when really pressed, I've yet to encounter someone who can actually tell me specifically

1) What form it is (i.e. can I see it?)

2) How much effort it was to build that feature.

...because, the problem with this story is that what you're describing is a pretty hard problem to solve:

- An agent interacts with a user.

- The agent has free reign to fill out the form fields.

- Guided by the user, the agent helps will out form fields in a way which is both faster and more accurate than users typing into the field themselves.

- At any time the user can opt to stop interacting with the the agent and fill in the fields and the agent must understand what's happened independently of the chat context. i.e. The form state has to be part of the chat bot's context.

- At the end, the details filled in by the agent are distinguished from user inputs for user review.

It's not a trivial problem. It sounds like a trivial problem; the agent asks 'what sort of user are you?' and parses the answer into one of three enum values; Client, Foo, Bar -> and sets the field 'user type' to the value via a custom hook.

However, when you try to actually build such a system (as I have), then there are a lot of complicated edge cases, and users HATE it when the bot does the wrong thing, especially when they're primed to click 'that looks good to me' without actually reading what the agent did.

So.

Can you share an example?

What does 'and has a lot of usage' mean in this context? Has it increased the number of people filling in the form, or completing it correctly (or both?) ?

I'd love to see one that users like, because, oh boy, did they HATE the one we built.

At the end of the day, smart validation hints on form input fields are a lot of easier to implement, and are well understood by users of all types in my experience; it's just generally a better, normal way of improving form conversion rates which is well documented, understood and measurable using analytics.

...unless you specifically need to add "uses AI" to your slide deck for your next round of funding.

One prescient comment was made by Eric Yuan (Zoom CEO), who made the claim that the reliability and general efficacy issues from AI products would be solved "down the stack", and I think this is more or less the attitude right now. Firms believe if they can build their LLM/AI products, the underlying LLMs/AI will catch up over time to meet their requirements.

I've also talked to a number of CTOs and CEOs who tell me that they're building their own AI products nominally to replace human workers, but they're not necessarily confident it will be successful in the foreseeable future. However, they want to be in a good place to capitalize on the success of AI if it does happen.