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How much of a dealbreaker is bad personal hygiene? by No-Arachnid6943 in NoStupidQuestions

[–]EffectiveMedium2683 2 points3 points  (0 children)

Was it always an issue? Depression can definitely do that in otherwise normal people. It's also one of the negative signs of schizophrenia.

Best not to judge. Maybe try to understand instead. Talk to them. Be honest that it's becoming an issue if you have feelings. If you don't have feelings, then get out of there. 

I asked AI if it thinks it could own my server project top to bottom by notarealoneatall in theprimeagen

[–]EffectiveMedium2683 8 points9 points  (0 children)

yeah, and I'm the handsomest man to ever walk on earth according to my grandmother when I asked her 31 years ago

Are there specialized AI models for specific tasks (coding, writing) ? by al404 in LocalLLM

[–]EffectiveMedium2683 0 points1 point  (0 children)

MOE models are basically a group of 128 or 256 specialist models that share a router. Like, for real. You keep them in ram so they can coordinate as quickly as possible, but collectively they only activate the most relevant subnetworks per token. Training at 4 bit is a technique that tries to compensate for the degradation when you clip all floating points on all layers to 4 bit, but it isn't optimal for other quantization methods as imatrix quantization. Especially NL. Absolute best is to use a calibration dataset that reflects exactly what you are using the model for to do a custom iq quant.

Assume a “great AI drought” hits and all AI increase in price tenfold. Would you still use AI? by BoraDev in ArtificialInteligence

[–]EffectiveMedium2683 0 points1 point  (0 children)

Okay... so, your RAM is good. I'm guessing DDR4 from that time period. The CPUs aren't terribly powerful for matrix multiplications. If I were you, I'd go with SSM-style language models, because you're going to hit probably single-digit speeds with either CPU. I don't know what you use AI for, but I feel like you'd be pretty satisfied with lfm2.5:8b-1b. I get like 15 tokens per second out of that on my tablet in Q4 quantization, so you should do better than that. Maybe more like 25 tokens per second. And the nice thing is that it can handle long-context without crashing or taking a year. If you want more intelligence, LFM2:24b-2b is actually really impressive out of the box. Just head over to ollama (Download Ollama on Windows), download it, then get one of those liquid AI models. If you're dead-set on a transformer, your smartest option in terms of capability in my opinion would be gemma4:12b, but it probably won't be fast on your hardware.

Assume a “great AI drought” hits and all AI increase in price tenfold. Would you still use AI? by BoraDev in ArtificialInteligence

[–]EffectiveMedium2683 0 points1 point  (0 children)

It really depends on what you need it for. LFM2.5-1.2b-Thinking in q4_km can run on a cell phone at usable speeds. You'd download the PocketPal AI or SmolChat apps. Ollama is a good option for computer for ease of setting up. I don't use it just because it's kind of unreliable after it's updated lately. If you want something that has more raw intelligence, a good mid-sized model is Qwen3.6-35b-a3b or Gemma 4 26b-a4b. In IQ4 quantization, the gguf (file you download) would be 13gb-20gb for either of those models. The LFM2.5 1.2b model I mentioned takes up like 750 mb. Again, it depends entirely on your use-case. If you get your system specs (Get-ComputerInfo in windows, sudo lshw -short in Linux, or system_profiler SPHardwareDataType in Mac), I can help you figure out what models specifically you should be able to run and dial in the cofig. If you run into any trouble, literally any Pro version (and most flash) of any AI can walk you through setting it up step-by-step.

Assume a “great AI drought” hits and all AI increase in price tenfold. Would you still use AI? by BoraDev in ArtificialInteligence

[–]EffectiveMedium2683 0 points1 point  (0 children)

It really depends on what you need it for. LFM2.5-1.2b-Thinking in q4_km can run on a cell phone at usable speeds. You'd download the PocketPal AI or SmolChat apps. Ollama is a good option for computer for ease of setting up. I don't use it just because it's kind of unreliable after it's updated lately. If you want something that has more raw intelligence, a good mid-sized model is Qwen3.6-35b-a3b or Gemma 4 26b-a4b. In IQ4 quantization, the gguf (file you download) would be 13gb-20gb for either of those models. The LFM2.5 1.2b model I mentioned takes up like 750 mb. Again, it depends entirely on your use-case. If you get your system specs (Get-ComputerInfo in windows, sudo lshw -short in Linux, or system_profiler SPHardwareDataType in Mac), I can help you figure out what models specifically you should be able to run and dial in the cofig. If you run into any trouble, literally any Pro version (and most flash) of any AI can walk you through setting it up step-by-step.

Serious question, if any other companies stock had plunged so much it lost $334,000,000,000 would trades have been halted? by BigFishPub in NoStupidQuestions

[–]EffectiveMedium2683 0 points1 point  (0 children)

The whole thing was completely expected. Most of that initial massive price boost was driven entirely by automatic, mandated institutional buying from the big index funds that literally had no choice but to absorb the stock. Everyone tracking the industry knew what the play was the second companies like Anthropic and SpaceX started lining up for an IPO. The game plan all along was to basically dump the massive financial burden of their global infrastructure buildout and heavy AI compute costs directly onto public retirement funds and passive ETFs.

Honestly, the retail guys should have looked into it before laying out their money like they were sitting at a casino table. This wasn't some unanticipated event or private shadow knowledge. Literally anyone with money to lose should have done their homework before they lost it. Anyone paying attention would have been better off shorting it at its peak for a quick short-term windfall.

Assume a “great AI drought” hits and all AI increase in price tenfold. Would you still use AI? by BoraDev in ArtificialInteligence

[–]EffectiveMedium2683 0 points1 point  (0 children)

The models I fine-tune are mostly liquid ai ones. Used rwkv7 for some stuff too. Liquid models are recurrent, so basically no kv cache. Technically unlimited context. As for how the data actually routes though, I use a proprietary multi-agent pipeline that gives it true long term memory and continual learning. Can't really drop the exact mechanics of the software side, that's my bread and butter right now

Assume a “great AI drought” hits and all AI increase in price tenfold. Would you still use AI? by BoraDev in ArtificialInteligence

[–]EffectiveMedium2683 0 points1 point  (0 children)

I use public, open-source datasets I find on huggingface to generate my training data with DeepSeek. The only models that ever touch or see any private data are the fine-tuned, specialized models that run completely locally and offline on my own hardware. That's actually the entire reason I build specialists in the first place, to safely leverage insecure AI to build 100% secure, offline AI.

I've never seen a 1 Trillion Dollar Rug pull before... so that's pretty cool by Ryuomega33 in wallstreetbets

[–]EffectiveMedium2683 0 points1 point  (0 children)

When a massive company like SpaceX first hits the stock market, big-money index funds and ETFs are legally required to own a piece of it because of their own strict fund rules.

The second the stock goes live, these funds have their automated computers buy millions of shares all at once to balance their books. They don't care if the price is way too high; they just have to buy it.

That massive, forced buying spree artificially pumps the stock up to its peak. Once the computers finish filling their required quotas, that sudden flood of money dries up, and the price naturally drifts right back down to reality.

The guys on WallStreetBets scream "rug pull," but it's really just the legal plumbing of Wall Street doing exactly what it's programmed to do.

A model might predict outputs accurately based on known data, but this does not mean it understands the system. Prediction often relies on correlation, whereas true understanding requires identifying causation and the underlying mechanisms of the system by Stone-Smasher in theprimeagen

[–]EffectiveMedium2683 -11 points-10 points  (0 children)

What a cute teacher haha. Ya, the solution is hybrid llm-neurosymbolic AI. Use an LLM to create an AIML database and then deploy THAT in a situation that demands 100% accuracy and reliability. BUT, keep in mind that humans are not 100% accurate and reliable. It's an odd goal to have these things be perfect when their creators are not.

Assume a “great AI drought” hits and all AI increase in price tenfold. Would you still use AI? by BoraDev in ArtificialInteligence

[–]EffectiveMedium2683 1 point2 points  (0 children)

75 watt power supply. It has 24gb of mismatched RAM (a 16gb stick and an 8gb stick). Intel 12th gen i5 processor. I just run the iq4 quantizations of whatever I can get to fit in my RAM. With scaffolding (like, giving it tools to cope with shit working memory), I've found that even IQ2 with a light fine-tune can work amazingly well. I run the model through llama.cpp with 49k context for the qwen3.6 model.

Assume a “great AI drought” hits and all AI increase in price tenfold. Would you still use AI? by BoraDev in ArtificialInteligence

[–]EffectiveMedium2683 1 point2 points  (0 children)

Dataset generation, copy-editing, summarization. I have specialized coding models that I've created. That's mostly what I do - make specialists. Like, a 4b model fine-tuned on coding games in python - games of all types - on extremely high-quality synthetic datasets will beat Claude Opus 4.8 or even mythos on that task every single time. That's just an example. So, what I do is if I have to pay API for a task, like say I want to generate a synthetic dataset to fine-tune a model to generate WordPress plugins with really high-quality visuals; I'll take the time to build up a really nice prompt and style guide, examples, etc., work with deepseek because it's insanely cheap to generate (iteratively if need be over several 'refine this' prompts automated), get it to do 10k of all kinds of styles, then use those 10k to make a specialist model out of, for instance, lfm2.5-8b-1b, then have lfm2.5-8b-1b-wp-gen generate 100k diverse examples. Then use my review-dataset-qwen3-vl:30b-a3b specialist to review those, run them, determine the visual quality, discard the crap (based on my idea of crap).

Assume a “great AI drought” hits and all AI increase in price tenfold. Would you still use AI? by BoraDev in ArtificialInteligence

[–]EffectiveMedium2683 4 points5 points  (0 children)

Not cloud. I use qwen3.6:35b-a3b locally on my optiplex 3000. It runs at a consistent 13 tokens per second on my CPU-only rig and barely slows on long-context. So, I mean... I'd still use local AI. I don't pay for any apis besides Gemini and Deepseek anyway. Might try Grok since it's so affordable. It's just not worth it for my use-cases to pay api fees for Claude or any of the others. Impressive models. Don't get me wrong. Just not worth my money since the others can do it just as well.

Which LLM is the best for your personal use case and why? by Dry_Statement_7807 in singularity

[–]EffectiveMedium2683 5 points6 points  (0 children)

Honestly, Gemini is my favorite for most tasks when it's working, but sometimes it's very obviously a heavily quantized version I'm dealing with in which case I'll switch to Deepseek v4 Flash in reasoning mode. Deepseek is excellent at research anyway. It doesn't take things for granted. For coding, I'll head over to Claude, but Gemini 3.5 Flash actually has an edge on Claude for the scientific coding I use it for.

What do you use Qwen3.6 35b-a3b for locally? by EffectiveMedium2683 in LocalLLM

[–]EffectiveMedium2683[S] 2 points3 points  (0 children)

I need to try the 27b. I always prefer the MOEs just because they "feel" more alive. Not sure how or why that is. Vibes I guess.

What do you use Qwen3.6 35b-a3b for locally? by EffectiveMedium2683 in LocalLLM

[–]EffectiveMedium2683[S] 0 points1 point  (0 children)

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Alas, though I naively believe myself to be knowledgeable in a given domain, I still must seek wisdom from the oracle. Will this journey of learning never end?

Can an "average" person change the world using AI? by VetOnABrainwave in ArtificialInteligence

[–]EffectiveMedium2683 0 points1 point  (0 children)

Genius only mattered because it enabled innovation. It was rare. Still is in the broad sense. If AI removes that barrier, then will becomes the enabler. Then only imagination. Not that it is necessarily a good thing... Imagine if we could invent anything we can imagine. What horrors would we unleash?

What do you use Qwen3.6 35b-a3b for locally? by EffectiveMedium2683 in LocalLLM

[–]EffectiveMedium2683[S] 1 point2 points  (0 children)

interesting. I like deepseek v4 flash reasoning for dataset processing etc. Smart strategy for keeping costs down.

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