It’s the summer of 2026. Is AI really cheaper than humans or is it an outright lie? People said AI models be improving, becoming ten times more efficient and cheaper, but what is the reality? What can we really expect in 2027, for example?
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- 60 minutes
AI sucks ass for every serious task. I’ve used it dozens of times to work on research projects, and consistently it gives me responses that sound good, but have holes, like citing works that don’t exist, mis-applying arguments, etc.
these problems never appear if you ask it standard questions, e.g. simple exercise questions from the classes. it always solves those correctly, probably because they exist in the training data. but try to ask it anything where logical inference is non-trivial and it starts splicing facts together in ways that don’t end up straight.
anyways, all being said, it’s still great for routine tasks, and for informing you about basic knowledge in a new field. since basic knowledge is all written down in books somewhere, AI knows about it quite well. also, coworkers make mistakes, and lots of them. if i sum up all the steps of progress that coworkers make and that AI make while working on a new project, i’d say it’s about on the same level. coworkers tend to think about new topics more seriously, but also they often just don’t respond, give up, never call back etc. meanwhile AI tries to output something, even if it’s wrong.
all that being said, there will still be a decline in knowledge worker jobs, but not so much because of AI being excellent at actively exploring new areas and kinda spreading out to take over jobs, but instead because like 99.999% of our jobs are kinda routine jobs anyways. people always tell themselves they’re special, and they are. but at the same time it’s mostly routine jobs. these are not mutually exclusive. and that’s why a lot of jobs are still going to vanish.
- 4 hours
There seems to be a bit of an odd relation between its value and cost. Building a model and setting up a data center is horrifically expensive, so LLMs as a service have to be just as expensive. But the stuff that can be done by LLMs is low stakes, low thought work, like copy writing, chatbot customer service answering the same 30 FAQs but crashing out on anything else, summarizing this morning’s headlines, etc. The price on these things is still being hashed out but it’s looking a lot like using AI is like hiring Anthropic for $100,000/yr. to replace a person who only gets paid $45,000/yr.
- scytale@piefed.zipEnglish9 hours
The fact that companies are now telling their employees to scale back and be mindful of their token usage shows that it’s not cheaper. It can be efficient yes, usually for automating the mundane stuff, but it’s not cheaper.
- HobbitFoot @thelemmy.clubEnglish8 hours
Right now, the state of the art appears to be that LLM’s are far more expensive to run than humans for many tasks. So, yeah, it is a lie.
There are uses for specialty AI that seem to work well, but they are usually bespoke for a certain task.
I expect that, if AI is used in 2027, it is going to be used with a lot more intent in targeted uses. I also expect some companies are going to realize it is better to fully control their own AI on their own hardware than to use a more state of the art AI which will use all their data as training data.
- [deleted]@piefed.worldEnglish12 hours
Fuck no, it is a lie. It is like an actor pretending to be a knowledge worker which fools people who don’t know better or who want to believe the lie.
Remember, it just regurgitates what it is fed plus some randomization and it can’t come up with novel ideas based on experience. That is what knowledge workers are for, applying knowledge to novel situations.
what knowledge workers are for, applying knowledge to novel situations.
how often does that really happen in your daily life, and how much money do all people in society make with it?
i get a feeling that this mostly applies to scientists figuring out new stuff. which makes about 1 in 10000 people in society. the amount of money earned through wages that way is rather little. most knowledge workers really have an office job where they fill paperwork, send it to someone else, do calls, etc.
- 10 hours
I like to call AI the next gen search engine, but be careful of some things:
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you’re much easier to track and profile
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you may be fed false information easier without context of source information
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you’re killing the planet
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hallucinations
- [deleted]@piefed.worldEnglish10 hours
That makes it something other than a search engine, not a new version of one.
- 6 hours
I disagree.
I can go into chatgpt and search for landscaping companies near me. It will link them.
I can search for a recipe.
I can search for anything I would normally use a search engine for with much faster speeds.
If that’s not searching, I don’t know what you mean.
- [deleted]@piefed.worldEnglish5 hours
Google and Bing return the results instantly for me.
Is chatgpt twice as instant?
- 4 hours
Ya with their AI things. For example, of you dont HSE their AI things, searching for a recipe yields you results of said recipe. Click on it. Then you have to scroll though a bunch of bullshit about their family recipe and how it tastes, then they should you the ingredients. Then the sizing. Then the instructions.
Do the same on an AI assistant and its just text of the recipe and steps no bullshit.
One of these is improved over the other.
- [deleted]@piefed.worldEnglish4 hours
Recipes are something I rarely take the first result for, since they can vary widely for the same dish.
Do you care what website it came from?
Have you ever checked to see if it actually matches the source page recipe?
Recipes are something that I always check a couple sites for to look for consistency or variation and some cooking sites are better than others.
- 3 hours
Yes I care what the source site is, that’s why you can check sources in chatgpt. Anyways its only one example, and I’m not defending AI here, my argument is that they are basically improved search engines. What is a search engine, you might need to ask yourself. You query, something responds.
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- Mniot@programming.devEnglish14 hours
It’s quite good for any problem that nobody cares about. For example, if you have a boss who wants hourly status-updates but does not actually read the updates. Or if you need to fill out security forms, but you were going to lie on all the forms and trust that nobody reads them. Or if you get a bonus for writing >100k lines of code, but the code doesn’t need to do anything that people want. Or if you need to have someone answer customer-support questions, but it doesn’t matter if the customers get helped or are happy.
- 14 hours
If my experience with it at work is anything to go by, no. Increasing amounts of my time are spent fixing the sloppy output of coworkers who use AI. Far from being “left behind” I’ve become one of the few people who is actually able to solve complicated problems.
- stoy@lemmy.zipEnglish13 hours
There was a great example of the issue with AI when compared to skilled workers.
There was a company that needed a special function in their software, they wrote it in four weeks and it worked fine.
Then they hired an AI pilled CTO, and needed to write a very similar function to the previous one, only this time, the CTO demanded to save time with AI.
The second function took months of testing to be production ready, and was still far more buggy than the first one, even a year or two later they still had issues with it.
I work at a company with AI-pilled management, they push hard for copilot, and I have noticed that the admin center for Copilot in Microsoft 365 has an overview screen where it has stats, and one of the stats is “hours saved with copilot”.
I would LOVE to see how those stats are calculated, they are probably extremely vauge and highly inflated.
- stoy@lemmy.zipEnglish10 hours
I wouldn’t be surprised if they just make the assumption that any time spent in Copilot means that the user saved at least that amount of time, if not more.
14 hoursThis exactly. We have one or two people, who are supposed to be more technician level people who have started submitting thousands and thousands of lines of code for “features” they dreamed up and which aren’t on any backlog or roadmap, and the actual software team is just like “fuck off we don’t have time for this.” They aren’t actually contributing, they are just causing drama at this point.
- 14 hours
speaking of which, it seems to me that over time one person will check the work of 3 to 5+ AI agents, when most people are fired, do you think it will be damn hard for the remaining people to work?
- 14 hours
I don’t think my colleagues are going to be replaced by ai. I think they are going to continue to use llms to generate “output” that needs someone like me to constantly fix until that becomes too expensive. At which point they will go back to doing their work the way they used to.
These llms are impressive word guessing machines, but the are nowhere near as capable as their companies say they are.
- ParlimentOfDoom@piefed.zipEnglish13 hours
The price of using these LLMs is already outpacing what it costs to hire a developer.
And their output is generally trash.
- 11 hours
Considering they’re raising the prices of it significantly, I’m gonna say no it’s not cheaper.
- 13 hours
Nope.
“Do the thing. I have a script that does the thing. I made it by listing the things in excel and asking Claude to write a script that does all the things”
The script not only doesn’t run, but it also quietly doesn’t do parts, and breaks stuff too.
So now I’ve got a pile of code that doesn’t work and it would be faster if I’d written it myself than troubleshooting the spaghetti. It’s like having a dumb intern, except the intern is incapable of improvement.
- 14 hours
Cheaper, prolly
Efficient? Debatable.
Reliable? Nowhere close, and humans aren’t even all that reliable.
- WhatAmLemmy@lemmy.worldEnglish13 hours
That doesn’t stop the parasite class from viewing AI as a hammer, and every task as a nail… or spending trillions failing upwards.
- 13 hours
It’s gotten much more expensive in the past month after AI companies changed their pricing models. They still aren’t making money, so expect the price to be jacked up in 2027 as well.
I think eventually we’ll reach a price point where companies will realize it’s only worth it at certain tasks in certain situations. They’re not gonna want to shell out serious cash so middle managers can have their emails written and read by computers.
Yeah, there is a reckoning on the horizon. From what i am able to see, the only area where LLMs make sense seems to be testing for security issues in software. There might be some edge cases, like small models for generating in-universe dialogue in games, but we should really prepare for OpenAI and Anthropic and all the AI startups depending on them to crash and burn, taking billions of dollars with them. The only one here profiting are Nvidia, SK Hynix, Micron and Samsung - because they are the people selling the pickaxes and shovels to the fools digging for gold.
In 2027 we can probably expect vastly larger bills or reduced usage limits. The price at which some models are being offered right now is in no way sustainable. For example Anthropics subscription plan gives you tons of quota for the most expensive models, while costing relatively little. Github Copilot recently changed its billing to token-based (before it was request-based) and it already produces incredible bills within the company I work for.
- 8 hours
In 2026 you still need expert knowledge to be able to judge whether it’s actually generating statements that match reality or just happen to take on a truthy shape.
Web search went from being the most powerful tool in acquiring knowledge to being mostly useless, a crapshoot, because of the difficulty in discerning which articles are useful versus which ones just take on a useful shape.
- 14 hours
Interesting… pair this with current state of reading comprehension in the North America education system… things are gonna be fuuuuucked.
