Mine is that the useState hook is an actual plague on the entire React ecosystem. Regardless of your opinions of React, if you wanna use something then use it right.
Mine is that the useState hook is an actual plague on the entire React ecosystem. Regardless of your opinions of React, if you wanna use something then use it right.
Current AI tools are excellent productivity and quality enhancers, but only for people who are willing to adjust their workflows and guide it to give good quality output.
The damage is done by Capitalism running the AI industry and the over financialization of the market.
Don’t be anti AI, be anti unregulated Capitalism.
I am anti commercial capitalistic LLMs which, coincidentally is ALL of them.
“B-But Axo the open weigh—!” They are NOT open, it’s the equivalent of giving you the executable of M$ Edge or a Windows ISO and calling it open, fuck this shit
If I was king of the world, I would rule that all AI models were based on stealing from all the knowledge of humanity. Since it cannot be un-stolen, I would decree that all copyright is unenforceable and all current proprietary data must be public domain forever as restitution for the abuse.
Stealing?
Using without permission to their own benefit.
Permission?
Why do I get the feeling I am training someone’s social media bot?
I’m not sure you’re offering anything of value to the bot if you can’t even formalize a sound position. Just paroting random rage bait you read somewhere, no full thoughts - why even spend your time like this?
Here your crown sir 👑
Its like money laundering, but for copyright
I was thinking more of the French revolution when all the palaces were emptied of valuables and taken by the people.
Many of them are truly open though, with training data and everything open source
Can you share some links please? I tried searching for them but nothing came out but weights
maybe we should call them ‘piratable’ instead
Work has forced us all to adopt it, so everyone did. It was either that or suddenly be the slowest person at work, which eventually gets you canned. People will evangelize all day long about how they refuse to use AI, how it’s dog shit, etc. Meanwhile I’ve managed to dial in my AI workflow so that it never deviates from our code standards, it never tries to invent its own components or styles, and I still manage to review it with experienced human eyes. It’s the reason I can start my work day at 10:30am, walk away from my desk at 4:30pm and still be well ahead of schedule. I’ve malicious-compliance’d the fuck out of my job, it has made my life easier, and I don’t give a fuck what some nerd still devoted to the “art of code” says. We live in a capitalist hellscape and I’m a survivalist.
With all of that said, I’d still wipe this capitalist shithole fever dream of a tool off the planet because I’m tired of data centers and AI companies fucking up the entire industry, the planet, and people’s lives. I’ve already witnessed firsthand what it did to my industry and I’m lucky to even still have a job (especially one that pays as well as it does—it helps to be in the industry just shy of 20 years).
turns out, you can just refuse to do so and you’ll still be just as fast as everyone else (source: me). Turns out that you’ll actually do the same amount of work and you don’t have to babysit a robot all day long losing your mind.
I know for a fact that I am not as fast as this. I had it build out entire page flows and pull together Vue components while connected to Figma’s MCP, and it was done in 1 hour. Tests, types, services, everything. I can’t compete with my own AI flow. I had it finishing 5-6 Jira tickets in one go.
Refusing also has its own caveats. Like painting a target on my back for layoffs.
That sounds useful. Id like to find a good place that is for optimizing use of this shit (esp locally) while not going full “hey check out my slop project”, or people going “the ai are our gods / will cause an apocalypse”
I use it to corral data a lot of the time. Stuff that is already verified by humans. It’s great for getting quick metrics, or pulling info about something into one central place. I’ve also given it an instruction to use the STE writing rules. It makes it speak more technically and deliberately, as opposed to always trying to sound like my friend.
I’m absolutely not one of those AI worshipper types, but I’ve found ways to harness it (hopefully thoughtfully) at work.
I agree on their usefulness but as long as you don’t use local and open LLMs you are unfortunately part of the ecosystem that does the damage. Luckily open models are catching on and hopefully some reliable companies take up on this business model.
I can’t wait for the crash, so that we can get more sustainable AI and access to the hardware to run it.
Won’t happen unfortunately. Unless you want to run a 1U with 6 GPU, requiring a custom water-cooling system, and which sips like 10kW/h of electricity while idle. It’s all integrated hardware born to be trash. The ram, cpu and GPU won’t be usable on consumer hardware without hard modifications.
1 of those GPUs can probably run 90% of what a small team would need, so you don’t need the full thing.
That’s about 600w of draw and 150w idle. Or about the same as a 5090. You don’t need exotic power or cooling for that.
They’re all soldered together, you can’t just take one
We also don’t need frontier models. The type of models that run on $5000 Mac studios can do today what the frontier models did 1 year ago.
We just need the Mac studio class hardware to come back to $2000 where it used to be.
Also, do not underestimate the ability of Chinese BGA rework shops from being able to salvage AI chips and install them on board that will fit in standard hardware. They proved they could do it with the Crypto only chips, they will figure it out for the AI chips if the supply is there.
The main reason these units use water cooling is for deployment density.
Local models are only months behind. The primary utility of comically large networks is a wider search space for the tiny fraction of weights that really matter.
I agree with you but that doesn’t change the fact datacentre hardware is not consumer friendly like it was in the past
Was it?
Not the point - this isn’t about secondhand servers, it’s about RAM being artificially scarce. Possibly as a deliberate measure to make cloud services sound less wasteful. If a 3090 with 32 GB was only a thousand bucks then OpenAI’s revenue would be even worse.
I have an old server with lots of DDR4 which I can for the most part just plug into my PC. The CPU can be put into another motherboard, and the GPU are discrete cards. Most of that hardware can be re used by consumers.
Most new AI datacentre deployment won’t be like that. An Nvidia Blackwell server has everything soldered. Good luck desoldering the CPU or GPU, the ram is either LPDDR5X which I never saw consumer motherboard use, the GPU is HBM3e and not a discrete card anymore. Whole package is unpractical for even a enthusiast to run.
The original point was that once the AI bubble bursts, we’ll have hardware to use for local inference. My claim is that no, it’ll probably be too specialized. Unless some maniac in China figures out a way to make new consumer hardware for it, but they probably won’t since Nvidia hardware is technically illegal (both export and import at this point). Even then, I don’t see Nvidia or others go back to making consumer hardware at a level where we can do serious inference locally.
Do not underestimate the Chinese electronics industry. Their adaptors are only 1 generation behind the current socket.
https://www.aliexpress.com/item/1005012221278601.html
Again, this is not about server hardware.
RAM is hideously overpriced because these doomed companies have open orders for all industrial capacity for years into the future. When the bubble bursts, the capacity’s still right there, and the same companies will be eager to sell mundane hardware to normal people at whatever prices we’ll still pay.
We are not in any sense talking about plugging datacenter machinery into home computers. That is not how the artificial crisis will end.
Why. Who else is gonna buy their silicon, when this diversion craters? They are presently making consumer hardware at a level for serious inference locally. What “serious” means gets better month by month, as a matter of software research. There is nothing to “go back” to; it’s just gonna be the only division in the black.
… and competent enough to actually evaluate the output properly.
Instead they spend a lot of money to push the fairy tale how anyone can now code without having a clue.
Why not both? Both is good
Nah, that would be like refusing to use a calculator, because they make them from unrecyclable plastic.
Bad comparison, it’s like refusing to use a calculator because it uses 200 times the amount of energy of existing calculators, was trained on stolen data, and despite all that gets the answer wrong
Calculators are also known to get some answers wrong.
Stolen data is not a tech problem, it’s a legal problem.
And it’s not 200 times more power. Maybe 5 years ago it was. But it is being wastefully used by burning capital.
That’s why the bubble needs to pop. So the true cost/value equation comes into play. It should probably cost 5 times what it currently costs from the big providers. It will cut down on the waste significantly.
The problems with AI is not the tech. It’s unregulated Capitalism that has hijacked it.
200 was hyperbolic.
I’ve seen AI get incredibly basic shit wrong though.
Calculators won’t miscount the number of O in strawberry, genAI confidently will.
GenAI is not a math machine. It’s an inference engine.
Still can’t do basic stuff that existing solutions can though
I can’t grow a baby, but it does not make me useless.
Yeah on one hand the field of evolutionary algorithms is fascinating and I can see potential. But on the other hand it’s being run into the ground by people forcing it into everything. It’s also not human-readable so people might think they know what they’re getting but really don’t because of the black box nature of it.