The learning from mistakes part of the example is – you tried /port_wines but the path is /wines/port instead.

But what about if the path is actually /beer and you have to pass a hidden undocumented query parameter called ?wine=1 for it to give you wines. But then the response is still of Beer objects (because that's the only thing the API validator would allow), so you have to map all the Beer fields to their equivalent Wine counterparts. But not all of them make sense, so you have to ignore them. Which ones? Ask the engineering team. Turns out the guy who wrote all this left years ago, and no one remember how it works. Someone digs up a link to a documentation page, but that internal wiki was taken down and so it returns a 404. You ping a sysadmin to see if they kept any backups. He points you to a few PBs worth of SQL dumps from an internal migration a few years ago and asks you to take a look in those. You simultaneously have to write up a status update for senior leadership which is due by end of day and give them a revised launch date for the project. They want to know why it can't be done in half the time.

The day an AI can figure all this out, I will be looking for another career. Until then I'm fine.

As long as their reasoning capabilities for the general case (system 2 thinking) remains limited, trial and error will only get them so far.

The automation of telephone systems didn't make front desk workers "PABX assistants" or even "PABX Operators", the automation became a tool and faded into the background.

parent comment emphasizes on the fact that no matter how big the effort was, ultimately our tools will always be imperfect. Therefore we will always have something to do.

Yep, they're safe in 2023. At the rate things are going, I don't even know what's gonna happen in 2024.

Our jobs could eventually become unnecessary

Most humans can’t do it. Most humans aren’t expected to do it in their jobs, though.

I’m saving and investing like I only have 10 more years of work before AI takes my job.

Either I’ll be well prepared for unemployment or I’ll have plump investment accounts and still be employed. Good outcome regardless.

Agreed. The network architectures have evolved so much in the past few years alone. Imagine what they can do in just 5 years if they can embed domain-specific knowledge to the current “dumb” statistical word guessers. Ten years is truly unimaginable.

I’m not expecting the singularity within that timeframe nor do I think we need it for lots of disruption in knowledge-based work. Still, I’m leaning towards a near future where these AI tools augment our capabilities more than the alternative where we lose all our jobs.

Because that's what the linked example showed? Is there a similar example of a more complex case?

That's what the hivemind says - AI will automate all our jobs. Well, yes it will automate a lot, but we won't be having the same expectations in a few years. The bar will rise so high we'll still have jobs with AI on top.

There's also a small little thing called competition. When your competitors use AI, your job just got harder.

The marginal cost of technology is pretty close to zero (albeit slightly higher for large LLM model inference) so it would make sense that the technology gets distributed widely. Kind of like how everyone has essentially the best smart phone. And it's laughable when someone tries to create a luxury smartphone for $10k and its just a sub-par Android with leather accents.

If you have a technology with practically zero marginal cost, pricing it very low and distributing it widely would maximize your profit. Not to mention that once its out of the bag, others will know that its possible and copy it.

[0] https://newatlas.com/vertu-ti-luxury-10000-dollar-android-sm...

It won’t be. Some of the biggest companies in the tech world got that way by building platforms and ecosystems that others build on top of. AWS and Azure the most obvious examples.

What’s more likely is that someone like a Microsoft will make it part of their cloud offerings so devs like us can build things on top.

Why try to capture every market when you can build tools and take percentages of the rest of the economy?

Tony Stark is an exception, though. He was once a slave who escaped after he fooled his captor into letting him create a minature arc reactor that he embedded into his own chest in order to fly to freedom and safety - as well as to magnetically keep shrapnel from invading his heart and killing him. He isn't the normal billionaire owner of a software company (outside of comic books).

I'm kind of hoping it is available only to some people, not going to be nice when everyone can have an AI design weapons, viruses etc?

Can you think of any category of software that doesn't eventually have an open source alternative? There are many open source projects orders of magnitude more complicated than a LLM. The linux kernel, Blender, Firefox, etc.

These LLMs aren't inherently complicated to implement, just expensive to train. And if the LLaMA release/leak is anything to go by we are extremely close to ChatGPT running on consumer hardware.

It works for tony stark because he’s a fictional comic book character and there probably wasn’t that much thought put into it.

Software development isn’t just “writing code”. It’s knowing what code to write. It’s knowing how to accomplish a goal using code. It’s knowing how to structure all of your code to work together. It’s knowing how to adapt code to meet new requirements. I don’t foresee rich “idea” guys figuring out how to do that any time soon.

The proposed method would improve the model anytime the model didn’t know which api to use. This requires the model to not hallucinate knowledge and some form of incremental training.