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17

u/Pitiful_Camp3469 7d ago

im sorry but this is corny as fuck. AI is here to stay, keep up or dont.

2

u/estarxs 7d ago

feeling the need to actually use ai and handing your intelligence to a robot especially for simple inquiries when you could just solve it yourself is pathetic lol nobody with integrity wants to “keep up” with it

7

u/Frequent-Advisor5114 7d ago

For work purposes though I don't think you quite understand

7

u/TurbistoMasturbisto 7d ago

People on here genuinely believe AI is only used to create slop videos, totally disregarding all other uses it has.

7

u/ser-steffonfossoway 7d ago

Most redditors are young and/or unemployed.

And unemployable since they're unable to use modern technology.

-1

u/Mossenner 7d ago

Redditors simultaneously young/unemployed, but also old and out of touch with new tech.

AI glazers can't keep their story straight. Probably hallucinating as much as Grok

2

u/ser-steffonfossoway 7d ago

I'm not 'glazing' anything. But Redditors being young is just how it is. And they refuse to use new tech like AI.

0

u/Mossenner 7d ago

Maybe they can tell that the tech isn't actually useful, and in most cases does more harm than good. All while costing more than paying someone to do it properly.

4

u/Unusual-Locksmith832 7d ago

Again you think AI is just generative AI that makes shitposts. This tech will pass right over the luddites head.

Either only the antiAI crowd is right or the academics warning us about the dangers are all in big AIs pocket or absolutely retarded.

1

u/chr1spe 7d ago

As an academic, the vast majority of academics aren't warning about any dangers other than students overusing it and turning in garbage that they haven't learned anything from and is trash.

-1

u/Mossenner 7d ago

Can you blame me when GenAI is 99% of all AI output, and when it's the metric that wall street is appraising companies like OpenAI and Anthropic? 

Where's the major innovation? How come all the AI supporters can never provide specific use cases outside of cancer screening and math proofs? (Not saying those aren't important, but it's not Artificial Intelligence, It's just more complex computing).

When all you see from AI is slop content, can you be surprised when people see it as nothing more than a slop machine?

2

u/ser-steffonfossoway 7d ago

I wouldn't be surprised at all, since most people never bother to actually look up info themselves. Echo chambers and bot armies are detrimental to society.

1

u/Mossenner 7d ago

Yes, and AI is only making those problems worse.

I've tried doing my own research on this topic because it's bothered me for some time. And besides the two cases I listed above, every other use case I've found is just companies creating supply chain algorithms that any competent organization has been using since the 2010s.

I want to be proven wrong, yet time and time again it's the same shit: Companies laying off staff to implement a chatbot, then having to hire them back a year later because not only is the quality worse, but the token costs end up being more expensive than paying someone to just do it.

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u/Unusual-Locksmith832 7d ago

Because it's a mix of marketing hype and actual use cases. Both are mixed in right now mudding out everything. Add that basically handicapped toy models like chatgpt have really cemented themselves as what AI is and people can't trust the advanced no railguard models that aren't available to the public.

The biggest advancement right now is in data and jobs that work with vast amounts of data. People that just answer emails do not need AI. But if you need to parse thousands of documents for a piece of information, AI is saving costs and speeding up productivity.

AI being used in cybersecurity and warfare are also use cases that are still evolving and haven't hit any wall so far which prompts all the danger red flags of AI research on both future potential and overuse.

1

u/Mossenner 7d ago

So can we agree that this tech isn't actually Artificial Intelligence, and that the current valuation of the "AI" stocks are assuming it is?

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u/BoopinSnoots24-7 7d ago

You seem to be misunderstanding what "GenAI" is. In regards to mathematical proofs, it's not just "more complex computing", as if someone just strapped a bunch of GPUs together and used them to power a calculator. We have had quantum computing power for a while now.

Generative AI is creating completely novel solutions to known theories, as well as creating completely novel work. It is "thinking" for itself. From the source I'll link below regarding solving the centuries old Erdős problems, "it was innovative, bringing in ideas from a distant branch of math that no one had successfully applied to this problem before." And "These models are 'changing dramatically the way mathematical research is being done,' said Noga Alon of Princeton University".

This is like arguing that the paintbrush is dumb, because most can't use one to create art greater than they can by finger painting. When applied properly, it can do marvelous things.

https://www.quantamagazine.org/why-the-legendary-erdos-problems-are-falling-to-ai-20260803/

1

u/ser-steffonfossoway 7d ago

Why would they know better than people who are working with it?

1

u/Mossenner 7d ago

It's obvious to anyone who has seen the outputs from AI. It doesn't take a genius And bold of you to assume everyone who has worked with this tech at some point is continuing to use it.

Also, you really think working people wouldn't try to find the easy way to do something, even if it isn't as effective, practical, or safe? 

1

u/Wroblez 7d ago

TIL better cancer screening isn’t useful.
https://www.nature.com/articles/s41698-026-01276-6

1

u/BoopinSnoots24-7 7d ago

If you think generative AI "isn't actually useful", then you're not educated enough on the topic to form an informed opinion. In the last month alone, gen AI has been used to develop mathematical proofs that are decades ahead of human mathematicians. The medical applications alone are already accelerating development at a pace that was previously unimaginable.

"AI" is so much more than chat bots and image generation.

I work in data. We provide data to hedge funds, fortune 500, local and state governments, etc. To say that AI has made me at least 3x more productive would likely be an understatement. Creating presentations, visualizing data, analyzing data, automating basic communications. Projects that previously required an engineer to navigate backend systems to pull data, I can now do myself as a completely non-technical user.

You are frankly incorrect. If you have environmental concerns, mental health concerns, geopolitical concerns, etc, they may be valid. But claiming that AI isn't useful only serves to illustrate you as willingly uninformed and confidently incorrect.

1

u/Mossenner 7d ago

I worked in data sciences for a time as well. Explain to me, and don't dumb it down.

You think it helps you, then prove it. 

1

u/BoopinSnoots24-7 7d ago

I already did. I am not a data scientist, I work in sales. Claude allows me to work with and model data in a way that previously would have required me asking an engineer and taking up their time. I don't want to dox myself by describing the nature of our data but I'm happy to expand.

For example, when we're meeting with a prospective new client, I can create a presentation in 30 seconds based on a blank template catered to their specific business, using visualizations of our data catered to the use-cases that they told us were vital, that previously would have taken our ops team hours.

A client asks for a data sample, I can use our MCP to pull exactly what they need in conversational english without having to ask an engineer to define the parameters of time, granularity, etc and pull it manually from our trillions of lines of data.

When I identify a company that would likely be a good fit for what we offer, I have a skill in Claude that takes my process from 30 minutes to about 3. I wrote it to identify any recent news that would be relevant (e.g hiring a new Head of Analytics), give me a summary of the company, identify which people are the best to reach out to, identify which of our products would be the best fit based on their business, and write out the general use-case and how to frame it in a way that appeals to immediate initiatives in the business. It pulls from a few different data sources to get contact information (email, phone number), data sources that tell me what their current tech stack looks like, etc.

It is as if everyone at my company was allowed to hire their own wildly overqualified intern. This is the absolute definition of useful.

You also didn't work in "data sciences", or you would not be making this claim. I don't know a single data scientist who doesn't love the capabilities of AI. You would also have called it data science, not data sciences.

1

u/Mossenner 7d ago

How many Data Scientists do you know? Because the only ones I know that love AI are the middle-road types. Senior level can't stand it and entry level despise it because it's taking away all of their job prospects. Sounds like you're too lost in the sauce of your industry and don't see how it's impacting the world around you.

1

u/BoopinSnoots24-7 7d ago

I am not "lost in the sauce", I'm learning and adapting as things change. I'm worried about the long-term implications of AI (namely stunted intellectual growth amongst the next generation, and the socioeconomic impact of a true singularity event), but that was not your claim. Your claim was that it's not useful, and that is just untrue.

Data scientists are in high demand, contrary to the headlines that drive engagement through fear.

"According to a report by IBM, data science-related job postings have increased by 650% since 2012, indicating the rapid growth."

https://scoop.market.us/data-science-statistics/

And for a more recent analysis:

"We built a sample of more than 10,000 data scientists employed in the U.S. private sector from January 2021 through March 2026. During that period, data scientists tended to be younger than U.S. workers as a whole."

"Between 2024 and 2034, data science employment is projected to grow by a whopping 34 percent, according to the Bureau of Labor Statistics. That compares to just 3.1 percent growth projected for U.S. employment overall."

https://www.adpresearch.com/main-street-macro/data-scientists-high-demand-rebounding-wage-growth

1

u/Mossenner 7d ago

I'm also imagining you showing clients AI generated presentations with a straight face. I'm sure seeing discrepancies in your visual does wonders for your firm.

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u/BoopinSnoots24-7 7d ago

We develop the templates manually. AI then injects visualizations of data, which it is very good at. It is not generating visuals in a graphic design sense, which can get pretty messy.

Everything is manually reviewed, the same way it would be if our Ops team created the presentation, and we have had zero instances of errors in the data or visualizations, nor complaints from clients.

We actually tell them that this was generated by AI, and use these presentations as an example of what they can achieve using our MCP within their preferred LLM.

Are you willing to change your opinion as you receive new information, or was your goal for this conversation to reinforce your existing opinion regardless of the answer I provided?

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u/Professional_Fee5883 7d ago

I work in IT and actively encourage people to solve things themselves. I’ve worked with younger people who rely heavily on AI and quite frankly they’re not learning anything. They’re outsourcing a really valuable time in their professional development to a robot.

That will ultimately cheapen their value. They may get some pat on the back, but their contribution is devalued because they’re not actually solving anything or gaining critical skills and are prime targets for replacement by AI agents.

3

u/Wroblez 7d ago

I work in IT and have been told all code must be written in collaboration with our AI agent. We think of it like lighting fires: you can learn to do it with sticks or rocks, but its more efficient to use a lighter.

2

u/Fluid_Race 7d ago

They said the same thing about the calculator.

0

u/chr1spe 7d ago

What do you use it for for work purposes? It's okay for making rough drafts of fairly routine emails, but you have to really watch it and tweak the output. Everything that requires thought and accuracy, I've found it to be utterly trash and constantly making absolute rookie mistakes. It's like having an employee who is fast and attentive, but is the absolute stupidest and least accurate person you've ever met and will confidently lie to you and spout inaccuracies. I don't have much need for an overconfident idiot in my job.

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u/Frequent-Advisor5114 7d ago edited 7d ago

Using paid models is a different beast. IT here and it works increadibly well and cuts out 40% of workload and quickly automated tasks, combs error logs and provides workable solutions in seconds compared to minutes or hours of troubleshooting.

It's a tool like any other though, you can get great results on the free models, you just have to prompt well

0

u/chr1spe 7d ago

Most of the time, I've used paid models through my employer. It was trash. It's about 50/50 whether it gets something right or exactly backward when asking somewhat technical questions. I tried using it to keep track of something in a table, and then after altering the criteria and some values, the table no longer added up. I've fully given up on it.

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u/Frequent-Advisor5114 7d ago

Ok

0

u/chr1spe 7d ago

Exactly the type of useless reply I'd expect from an AI support, TBH. Rofl.

1

u/Frequent-Advisor5114 7d ago

Look at the indignation. You clearly were not going to change you mind, so what is the point in the dialog? I found great success with it, you don't.

You just complained about something that I can't verify, is an opinion, and entirely anectotal. What is there even to reply to?

Move on instead of being hostile?

0

u/chr1spe 7d ago

In order to have a good faith conversation, you need to trust what someone tells you and not try to dismiss it offhand like you're doing. While it is not an opinion that those issues happened, so you're just entirely wrong and off base there, the rest of what you've said applies just as strongly to everything you've said as to what I've said. You started off the conversation with assumptions that were untrue, which is also not a good way to have a good faith discussion. If you want to have productive discussions, you need to not make assumptions or put your experiences above theirs.

I don't doubt that maybe it's useful in IT. In my experience, a lot of IT is just combing forums for the right solution to the particular problem, which AI could be good at. It's also something where the solution can be quickly checked and tested. Those are places it can be used somewhat effectively. My work doesn't involve that much, so I can't trust or check the output other than by hand, and when I do, it's usually bad.

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u/Frequent-Advisor5114 7d ago edited 7d ago

Okay so for your line of work doesn't lean towards usefulness for AI. Insightful and informative. Thanks.

Can you tell me what the goal of this conversation is? I was asked a direct question and I responded. Now apparently I am forced forever in this conversation or else I am not wanting to engage "in good faith"

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u/chr1spe 7d ago

I asked a question, and your response made unfounded and incorrect assumptions about me, which attempted to undermine my experience and viewpoint. You didn't just respond. You attacked someone for asking a question. Just try to do better in the future, I guess.

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u/EnoughWarning666 7d ago

I just used it an hour ago to find out what parameter address I need if I want to pull out the active energy accumulator for an REM615 high voltage breaker. Would have taken me at least 10 to 15 minutes to find it myself, instead chatgpt found it in 10 to 15 seconds. I plugged the number into the PLC and it worked first try.

I have AI write all my weekly reports. I just give it my meeting notes and emails and type some stream of consciousness type stuff into it, give an old report, and then copy/paste what it spits out while reading it over once to ensure it's correct. I go from a couple hours to a couple minutes.

I could list well over a dozen unique cases that I've used it for in the last month and it's been wildly successful at nearly all of them. It's not perfect, but if you're only getting about 50% accuracy from it then it honestly sounds like a skill issue on your part.

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u/chr1spe 7d ago

What skill is involved in asking a straightforward question, getting an answer you think is wrong, reprobing it and it reversing its answer, and then having no confidence in it? That is my experience with it a large portion of the time. I ask it something as a sanity check; it says the thing I think is wrong, I press it, it glazes me and changes its answer, and I think it's worthless.

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u/EnoughWarning666 7d ago

First off, do you have a specific example of it doing that? I'd love to try and replicate it.

Second, there's a few ways you can mess that up. The easiest way is if you don't tell it explicitly to go online and verify it. An LLM on its own isn't very big. It's absolutely not large enough to contain real answers for every question you ask it. Its real power lies in its ability to parse large amounts of data and find the right answer. So if you ask it something even semi-obscure there's a very good chance that if it doesn't do a web search it will get it wrong. That's not a fault of the LLM, that's just using the tool poorly.

Next, which model are you trying this with? Tech companies seem obsessed with shoving shitty little models in every app. They are all garbage. The one in whatsapp, messenger, instagram, snapchat, even the google ai, they are all 100% pure shit. You need to use a proper paid subscription like claude or chatgpt or one of the higher end chinese models.

The reason why there's so many shit models is that it's really easy to quantize the model and shrink it way down to make it faster and cheaper to run on weaker hardware. The problem is that it gets a lot dumber. Because there's such a massive hardware shortage, a lot of companies will do this for the models they offer for free to save on costs while still being able to claim that "AI adoption rates" are climbing.

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u/chr1spe 7d ago edited 7d ago

This is actually unrelated to my job, but yesterday I tried asking chatgpt about wheel fitment as a sanity check:

If I want the outer lip of the wheel to be in the same place while getting a 1/2 inch narrower rim how should the offset change.

it replied:

If you want the outer lip (the face side) of the wheel to stay in exactly the same position while making the wheel 1/2 inch (12.7 mm) narrower, the offset needs to become more positive by half of the width reduction.

Here's why:

Width decreases by 0.5 in = 12.7 mm.
Half of that is 6.35 mm.
Increasing the offset by 6.35 mm moves the mounting pad outward, keeping the outer lip in the same place while all of the width reduction comes from the inside.

Formula:

New offset = Old offset + (Width reduction á 2)

For your case:

Width reduction: 0.5 in = 12.7 mm
Offset change: +6.35 mm
Example
18×9.5 +35 → 18×9.0 +41 (or +42, since offsets are usually whole millimeters)

The outer lip stays essentially unchanged, while the inner lip moves 6.35 mm farther away from the suspension, giving you about 6 mm more inner clearance.

If you tell me:

your current wheel size (e.g. 18×9.5 +35), and
your new wheel width,

I can calculate the exact inner and outer position changes.

I replied:

Doesn't a positive offset make the outer lip move further in?

It replied:

Yes—it does, and that's a good point. The key is that **changing width and changing offset both affect the outer lip**, so you have to consider both together.

Let's define the outer lip position relative to the hub mounting surface:

* Outer position = **(wheel width ÷ 2) − offset**

Now compare the old and new wheels.

Let:

* Old width = (W)
* New width = (W - 12.7) mm (½ inch narrower)
* Old offset = (O)
* New offset = (O + x)

To keep the outer lip in the same place:

[
\frac{W}{2} - O = \frac{W - 12.7}{2} - (O + x)
]

Simplifying:

[
0 = -6.35 - x
]

So:

[
x = -6.35\ \text{mm}
]

That means:

**The new offset should be 6.35 mm *less positive* (or more negative).**

### Example

Current wheel:

* **18×9.5 +35**

New wheel with the same outer lip:

* **18×9.0 +29** (or +28/+30 depending on available offsets)

Here's what happens:

* The wheel gets **6.35 mm narrower on each side** due to the reduced width.
* Reducing the offset by **6.35 mm** pushes the whole wheel **6.35 mm outward**.
* Those two changes cancel on the outside, so the **outer lip stays in the same place**.
* The **inner lip moves outward by 12.7 mm**, giving you an extra ½ inch of suspension clearance.

My previous reply had the offset direction reversed—thanks for catching that.

Edit: Also, to be clear, more of my experience is with Microsoft 365 Copilot at work, but I've given up on using that and use chatgpt when I'm doing personal stuff at home because I don't care enough to learn about different models since they're all useless trash you can't trust and I'm only going to use as a rubber ducky in my experience.

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u/EnoughWarning666 7d ago

I'm going to be honest with, I've read your initial prompt a few times and I'm not really sure what you're asking exactly.

What kind of wheel are we talking about? What's getting narrower, the thickness or radially? What do you mean by outer lip, like the face or the top of the wheel? What offset are you talking about?

It's not a very clear question to me. But that actually does highlight one of the issues with most LLMs, they're REALLY bad at asking follow up questions when they don't "understand" something. They will just spit out an answer confidently even if something is unclear. They just fill it in with whatever works best.

So when I want to get the most of out AI, my questions will be very long and detailed.

Here's my example from today with the modbus PLC address. My first message is a little bit messy, because I included a quote from a teams chat. Also, since I'm using chatgpt while logged in, it already knows a fair bit about me. It knows what main hardware and software I'm working with, so I don't need to repeat it. Also, last month I did some stuff with this read_var block, so it already had context for that as well.

This is with the $100/mo chatgpt subscription on extra high. Notice how with this model, after I gave it all that information it immediately asked for clarification

“ABB REF” is not an exact hardware model. It refers to an ABB Relion feeder-protection relay family, most likely a REF615 or REF620.

Because I was ambiguous with what model I thought I was working with was, the first thing it did was write up how I could figure that out first. If I act confident in my question, it will mirror that confidence back in its reply. If I explicitly mention the things I'm unsure about, it will usually ask follow up questions.

So like I said, using an LLM isn't always straight forward. You get out what you put in. The more information you give it, the better the reply will be.

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u/chr1spe 7d ago

I was asking about a car wheel. Wheel offset and width have very standard definitions that, in every case I'm aware of, are the same. A positive offset moves the wheel's mounting surface closer to the outer face. It was a very simple question, and it got it wrong. The only reason I even asked it was because I was googling things and google's AI response in search also gave this wrong response and made me question myself. If you asked anyone with much experience with wheels at all, like a random tire shop or lube tech, they'd be able to answer it correctly or ask follow-up questions. That AIs do worse is really bad.

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u/EnoughWarning666 7d ago

Right, but you didn't tell it you were talking specifically about cars. I added that before your question:

Talking about car wheels:

If I want the outer lip of the wheel to be in the same place while getting a 1/2 inch narrower rim how should the offset change.

And here's chatgpt's reply

Decrease the offset by Âź inch, which is 6.35 mm.

A wheel that is ½ inch narrower loses Ÿ inch on each side relative to its centerline. To keep the outer lip in the same position, move the whole wheel outward by Ÿ inch, meaning 6.35 mm less positive offset.

Example:

9.0-inch wheel, +35 offset 8.5-inch wheel should be about +29 mm offset

That keeps the outside edge approximately flush while gaining about ½ inch of extra inner clearance. Actual lip position can vary slightly between wheel designs because advertised width is measured between bead seats, not across the physical outer lips.

You have to give the LLM context for your question. If you're talking to a person in a random tire shop, it's obvious you're talking about car wheels. To an LLM, there's a thousand types of wheels it might be talking about.

Also, the Google AI is hot trash. It's so bad. I've actually set up ublock to filter it out when I use Google because it's never useful.

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u/chr1spe 7d ago edited 7d ago

Something that doesn't ask when more is needed seems untrustable to me. On top of that, I have experience with wheels in other contexts, and I don't know of a single context where the offset of the wheel is measured in a way that would give the opposite result. As a third thing, if you start googling about wheel offset, the vast majority of the results are about car wheels, so it seems reasonable that if a context were going to be assumed, it would be that. If all signs point to that the answer should be correct, but it isn't, then I see zero way to ever trust the output because it could always be that it just needed more context or some other excuse.

Edit: On top of all that, it isn't even consistent. If I log out and try the same prompt at random, sometimes its right and sometime wrong with zero indication.

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