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AGI Was Never Going To Kill Us Because Suicide Happens At The End of Doomscrolling
I'll go ahead and call this the peak of AI version one-dot-oh
The headline reads "OpenAI Is Preparing to Launch a Social App for AI-Generated Videos." People will, I guess, be able to share AI generated videos with their friends (and who doesn't have THE ALGO as a friend). Awesome. This is also on the heels of the introduction of live ads within OpenAI's ChatGPT.
Some of us were waiting for The Matrix. I know I've always wanted to learn Kung Fu. Others were sharpening our pointing sticks so that when the paperclip machine came, we'd be ready. Most of us just want to look forward to spending a quiet evening with AI Waifu before we initiate her kink.exe module.
But we'll never get there. Because Silicon Valley just can't help itself. Hockey sticks and rocketships. Series E-F-G. If I can just get 5 million more Americans addicted to my app, I can buy a new yacht made completely out of bitcoin.
I am a daily "AI" user and I still have very high hopes. My current operating theory is that a combination of whatever the MCP protocol eventually settles into plus agents trading some sort of crypto or stable coin will create a kind of autonomous, goal-seek driven economy. It will be sandboxed but with (semi) real money. I don't think we, humans, will use it to actually drive the global economy, but as a kind of just-over-the-horizon global prediction market. Think of it as a way for us to have seen 2008 coming in 2006. I also was looking forward to a team of maybe 10 people making a legit billion dollar company and this paving the way for groups of 3 - 5 friends running thousands of $10 + $50 million dollar companies. No more corporate grind if you're willing to take a little risk and team up with some people you work well with. No bullshit VC games - just ship the damn thing.
And I think these things are still possible, but I also, now, think the pure consumer backlash to this silicon valley lobotomy of AI could be very much Dot-Com-2-point-O. The normies at my watering hole are making jokes about AI slop. Instead of "lol I doomscrolled into 3 am again" people are swapping stories about popping in old DVDs so that they can escape the ads and the subscription fatigue.
Culturally, this could be great. Maybe the damn kids will go outside and touch some grass. In terms of advancing the frontier of human-digital knowledge, it seems like we're going to trade it in early not even for unlimited weird porn, but for pink haired anime cat videos that my aunt likes.
To what extent is it or will it become possible or practical to run a homebrew jailbroken LLM on local hardware? That's the big question in my mind.
I'm late to the party, and I'm aware of it, in that I'm only just now using LLMs beyond a toy for research and education purposes. But essentially every day I'm aware there's an expiration date, that the product is just a few bad days for the SP500 from being enshittified. Whether that comes in the form of censorship and legal caution that makes it useless for my purposes, or in the form of pricing that makes it prohibitive, or commercialization and monetization in ways that make it unreliable (pay extra for your product to be recommended!), or optimization for it as people start to operate their products specifically to be seen and understood by LLMs. There's going to come a time when I can't just log into ChatGPT and get a good result, I'm sure the old timers are already complaining; and there's going to come a time when there isn't enough VC money sloshing around to fund a competitor like Grok that throws off shackles.
So at that point, can I or will I be able to operate a homebrew LLM for my personal and business purposes? I'm not handy enough to know how possible that currently is, or how user friendly, I'm at the level of "I can run a Linux machine but I'll need to look stuff up once a week or so."
You can run a homebrew LLM (7 billion parameters / 12bn / even 24bn) for nothing on any decent PC with a GPU. It will be lucid but really pretty dim.
You can rent a RunPod server pay-as-you-go and run a 70bn / 105bn / 200bn model for a few dollars an hour. It will be smarter but not quite GPT / Claude level. You can also pay 25 USD a month for Featherless, which is the same thing but less under your control.
Or you pay for the APIs.
I've run a few 4-byte quantized 70B models on a small home gaming machine pretty easily (Intel i3-13100, nVidia 3060, 48GB RAM). It's a little slow -- non-MoE models can go into a couple tokens-per-second, and MoE seldom go higher than 10 tps -- but there are some set-and-forget use cases where the difference isn't a big deal, and you're just a couple GPU generations away from it going faster.
Both ollama and lmstudio work pretty easy 'out-of-the-box'. You can dive down the deep end if you want, and start moving to vllm or others, but it's far from necessary for most use cases.
Scaling up without waiting can get expensive, though. Used server GPUs aren't ludicrously expensive and buy you more RAM (and thus more context/bigger models), but they're slower than current-gen (or even two-gens-old) gaming cards. Trying to break past 24GB VRAM gets into the kilobucks range, and while nVidia says that they're dropping a card that will change that in a few months, it'll probably be seconds before it get scalped. For LLMs, processing power is lower priority than total memory bandwidth, so you can get away with some goofy options like the Ryzen Max series and run 128 GB ""VRAM"" with a CPU, but setup is more annoying and throughput suffers a lot, and it's still not cheap.
I have a Ryzen Max 395+ with 128GB RAM and it runs pretty well; granted I don't use it for LLMs but the humongous amount of RAM is useful more often than one might think.
God damn man! What do you use it for if not llms?
Prototyping things which I really should be pushing off to a cluster for computation but I can't be bothered with doing the SSHing. When it comes to prototyping not needing to do the extra steps of moving my latest version of the code over to the cluster saves me around 10-15 seconds for each iteration, which is enough of an annoyance I'm happy to pay to avoid it. My machine is the HP laptop that comes with AI MAX 395 so it's my main personal device. Not needing to worry at all about RAM management for my own code has been surprisingly freeing.
That and of course playing DOTA with all settings set to maximum, it's amazing how I can get Desktop quality DOTA performance on my laptop today.
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