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.com bubble 2.0
These idiots need to stop with LLM and create more specific machine learning algorithms. Like language translations, program writing get them good at that specific thing. Use those algorithms to train new ones.
The way they are building it is they poured a massive slab of concrete and refusing to make releif cuts. Over time the stresses cause breaks then shit gets under it and causes a mess. Build a good foundation, don’t jump to the final fucking stage
The modern tech industry is all about building products that generate hype to impress the shareholders. Building good functional products to impress the consumer isn’t necessary if you can simply put on a flashy show for the geriatric billionaires.
I need an automated code optimiser using genetic algorithms, but the best thing I could find is copilot.
Google doesn’t really let you say no, do they? Maybe there is a setting somewhere to turn it off but Gemini shows up at the top of most searches.
Luckily it seems to be regional. I don’t have it
Why is this getting downvoted?
Maybe because we’re all getting really tired of industry propaganda designed to sell us on the “inevitability” of genAI when anyone who’s paying even a little attention can see that the only thing inevitable about this current genAI fad is it crashing and burning.
(Even when content like this comes from a place of sincere interest, it becomes functionally indistinguishable from the industry propaganda, because the primary goal of the propagandists is to keep genAI in the public conversation, thus convincing their investors that its still the hottest thing around, and that they should keep shoveling money into it so that they don’t miss the boat).
OpenAI, the company behind that giant bubble in the middle there, loses two dollars and thirty five cents for every dollar of revenue. Not profit. Revenue. Every interaction with ChatGPT costs them a ridiculous amount of money, and the percentage of users willing to actually pay for those interactions is unbelievably small. Their enterprise sales are even smaller. They are burning money at an absolutely staggering pace, and that’s with the deeply discounted rate they currently get on their compute costs.
No one has proposed anything that will lower their backend costs to the point where this model is profitable, and even doubling prices (which is their current plan) will not make them profitable either. Literally not one person at OpenAI has put forth a concrete plan for the company to reach profitability. And that’s the biggest player in the game. If the most successful genAI company on the planet can’t figure out a way to actually make profit off this thing, it’s dead. Not just OpenAI; the whole idea.
The numbers don’t lie; users, at best, find it moderately interesting and fun to play around with for a while. Barely anyone wants this, and absolutely nobody needs it. Not one single genAI product has created a meaningful use-case that would justify the staggering cost of building and running a transformer based model. The entire industry is just a party trick that’s massively overstayed it’s welcome.
I mean, fuck the profitability. What about its massive toll on our already crumbling climate? What about its hallucinations that were told by the massively powerful companies (currently, anyway) to just not worry about? What about the promise of it “revolutionizing” industries (corporate speak for fucking workers in new and exciting ways), what about the paradigm solidifying nature of this tech that they keep lying to us about being a democratizing super tool?
Everything about this shit is trouble because of the world it was built into. This type of tech (even though most of its capabilities and uses are lies) in the hands of the people it’s in will only serve the rich and gobble up resources when we need to be scaling back our consumption. Instead, that endless investment is fueling our climate collapse.
Fuck this LLM bullshit. It’s not for us. It will only hurt us in this timeline.
There are those who fear A.I. … but it’s on its way regardless.
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How dare you besmirch the good name of zip disks! There was a good 18 month period in the nineties where they filled a valid use case in the gap between floppy disks and the widespread instantiation of WAN solutions for moving and storing data.
I would be really annoyed if it was just a fad seeing as it makes me save at least an hour of work a day.
Do you think AI and / or AGI is a possibly at all given enough time?
Because if the answer is yes, then don’t we need people working on it all the time to keep inching towards that? I’m not saying that the current implementations are anywhere close, but they do have their use cases. I’m a software developer and my boss the lead engineer (the smartest person I’ve ever met) has made some awesome tools tools that save our company of 7 people maybe a 100 hours of work a month.
People used to complain about the LHC and that’s made countless discoveries that help in other fields.
Powered flight was an important goal, but that wouldn’t have justified throwing all the world’s resources at making Da Vinci’s flying machine work. Some ideas are just dead ends.
Transformer based generative models do not have any demonstrable path to becoming AGI, and we’re already hitting a hard ceiling of diminishing returns on the very limited set of things that they actually can do. Developing better versions of these models requires exponentially larger amounts of data, at exponentially scaling compute costs (yes, exponentially… To the point where current estimates are that there literally isn’t enough training data in the world to get past another generation or two of development on these things).
Whether or not AGI is possible, it has become extremely apparent that this approach is not going to be the one that gets us there. So what is the benefit of continuing to pile more and more resources into it?
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This is such a weak take. It’s constantly getting more efficient, and it’s already extremely helpful- It’s been incorporated into countless applications. OpenAI might go away, but llms and genai won’t. I run an open source local llm to automate most of my documentation workflow, and that’s not going away
“it’s been incorporated into countless applications”
I think the phrasing you were looking for there was “hastily bolted onto.” Was the world actually that desperate for tools to make bad summaries of data, and sometimes write short form emails for us? Does that really justify the billions upon billions of dollars that are being thrown at this technology?
This comment shows you have no idea of what is going on. Have fun in your little bubble, son.
LLMs are not AI. They’re content stealing blenders wearing a name tag that says AI on it.
Isn’t Microsoft Copilot just ChatGPT?
Microsoft Copilot integrates OpenAI’s technology like GPT-4, but it is not exactly the same as ChatGPT. Copilot is designed to integrate AI into specific productivity tools like Microsoft Word, Excel, PowerPoint, and other Microsoft 365 apps. It also seems to have different system prompts and fine tuning which leads to different answers and styles.
March 2024… Useless data.
“… as of August 2024” is literally front and centre in the image.
I only saw the one text saying march
I don’t understand how people can use Gemini. I have always had bad experiences with it.
I am actually using Gemini sometimes. And it is actually decent. Especially in certain tasks, especially at video reasoning.
Why do you say that?
nice try, gemini
Nice, gonna call something bad and not even give any reason for it
It’s answers just don’t feel as good as chatgpt. Sometimes they are incorrect, and sometimes they are lackluster.
