This topic is bringing out the hallucination-panic crowd.
It's perfectly safe to use LLMs to surface underlying data and knowledge without having to trust that it's giving you correct advice.
Use the LLM as search technology: string match -> semantic search -> search intelligence.
This is especially helpful when you don't know the right question to ask. Semantics only help you find text that is semantically near the input query. Semantics won't help you when what you are looking for is connected to what you have by something other than semantics, like causation, mechanism, or interpretation.
Trying to figure out why your crops aren't growing well will likely require you to read several articles across a range of sciences, probably scoped to the specific conditions you are dealing with. A semantic search is not going to surface those first.
Allowing an LLM to chain together several sources for you to read first does not require you to ask it for a conclusion.
The readme on Github does say the system produces hallucinated sources https://github.com/anonnerdfrenzy/survival-llm#how-the-model..., but really you're correct, for this kind of highly targeted use case the LLM's summary could probably be ignored entirely and the system could work extremely well even just as a search engine: index all of the content up front, chunked by paragraph and maybe enriched with a HyDE step, have the LLM facilitate running a handful of hybrid keyword/semantic searches based on the user's question and reranking the results, and show the exact pieces of text in the corpus that are most responsive to their question. No summary needed.
A great strength of LLMs is how they provide useful answers even if the prompt has glaring spelling or grammatical mistakes. If your prompt is not great, as you said, they will reply in a way that helps you identify that flaws, and learn how to steer the model better.
They're amazingly useful tools, but they're nowhere the level believers want them to be, not yet.
In a true emergency, there are often many cases where you need not just information retrieval, but "thinking and reasoning" to deal with unprecedented situations, right? Is it technically possible to balance lightweight local performance with thinking capability, while avoiding the risk of hallucinations in life-or-death instructions?
Nevermind hallucinations, the donkey-work is important; why bypass the hours of research, which trains our in-built LLM and can lead to new realizations, and get the carrot without much effort? This LLM stuff feels like a candybar; the anticipation of the magic feels good, the thing tastes good while you're eating it, and everything thereafter is shit, but we easily forget, and reach for the next candybar.
I appreciated Blindboy Boatclub's take in his podcast episode "Artificial intelligence is Disgusting and it will never replace Artists" from 2026 March 17. I also appreciate Electrical Engineer & Computer Scientist Timnit Gebru's perspective on these stochastic parrots.
While intraspecies diversity confers, up to a point, a survival benefit, consider the long-term consequences of playing this particular game.
We don't have to eat every candybar the rich mostly-guys ply us with.
The premise in this case is to get answers quickly in an emergency situation. You don’t want to tell the person with a burn injury to wait a bit since you always wanted to learn how burns are treated.
Interesting. I have a mac mini I run headless dedicated for LLM inference. Do you know if I could run project nomad on a linux box but use qwen on the mac for the AI stuff? I can't find any info on if this configuration is possible.
I set this up on my machine and tested it with the following question:
How can I build a bow drill so I can start a fire?
It got it partially right: spindle, bow with string tied the correct way, and fire board. But then it flubbed by saying you put the spindle between both hands and move your hands back and forth to rotate the spindle and create the necessary friction… this totally ignores using the bow to rotate the spindle! It also mentioned “fanning the sparks” but there is absolutely no way your bow drill is going to create sparks.
I asked a frontier model to check the survival LLM’s conversation trace and it pointed out the errors.
I didn’t see obvious errors in the other 3 prompts I used, but this one seemed pretty egregious for a survival LLM.
I thank the creator for making this, but take it with a grain of salt.
That's why the question was whether it gave sources, not whether they asked it to go check sources. Yeah, LLMs suck and you should always assume false information. 80% accurate is not production ready.
Considering the tendency even now of LLMs to hallucinate, and the hardware requirements for any kind of LLM -why not just gather those resources into some sort of local archive that can be searched without an LLM?
This seems redundant and requiring more overhead while providing less reliability than something like Kiwix to me.
Not sure about how the code in this project works. But the way I see it, an LLM+chat is a great interface for information. If you then connect it to a db with the knowledge/articles you need, then you get a great way to navigate it, without needing the model to memorize all the info
I think that if I were to build this I might skip the LLM and just setup a nice interface to the source files using qmd style search. [0]
That way the tiny model isn't acting as a potentially incorrect interpreter but you still get semantic search to help you find the right documents quickly.
I suppose there is something to be said for a good summarization, I just worry that these tiny models aren't really GOOD summarizers.
Awesome, I didn't know qmd style search, thank you!
I'm all up for using the better/simpler task for the job. That's been a thing lately also with the Jev/decision models hype, most of those things can either already be done by a pretrained classifier[0], or you can start with a bigger model and then train your smaller/adhoc one when you have some data (it doesn't even take much for most applications, you can get about 95% accuracy on email classification with 50-100 examples)
I agree with the OP; this technology does not seem an appropriate fit for survival equipment. By definition survival scenarios can be life and death. Even one "You're absolutely right!" level mistake from an LLM could give a user bad information, leading to John Doe eating a mushroom he really should not have eaten.
I agree with your point, but if John Doe is foraging mushrooms without experience of the local flora (which I doubt this archive contains), then John Doe is kinda asking for it.
The bigger issue in this context would be canning, such as incorrectly explaining the mechanisms to avoid botulism (acid and/or pressure canning), or perhaps incorrectly wiring in repairs. However, again, it’s best to practice with these prior to emergencies anyway.
It should be noted though, that the model does source its claims, so you can fact check it and should review this information regularly.
Slight OT Survival tip, if you are starving don't go for mushrooms in the first place (unless you really, really know) - even if you get the right one, they don't contain much energy for you to burn anyway. The larves you often found in them, probably contain more. So mushrooms are a nice addition (and in rare cases good medicine), but for survival you should focus on something else.
Why not both? After the collapse of civilization, as long as you can maintain the computer running, you could educate the next generation as soon as they could write. Maybe they will bypass the local agent as they learn their way into the library, to save energy.
Consider they won't have access to the plentiful practice opportunities we have now, most resources would have to be spent with a practical goal.
Survival implies that energy would definitely be a very limited resource. Using it to replace knowledge is just... I can't describe it even. Why not just learn it on our own and keep a small guidebook in your backpack. Our overrelience on computers and now LLMs, even for basic life-saving knowledge is simply our way of going the way of the dodo... I use frontier models at work, I definitely get more done. However I will never use it as a replacement of my own knowledge.
A field guide to foraging for edible mushrooms will probably be more practical than naïve use of an LLM: “can I eat this mushroom?” is an exercise in trust that I will maybe never be comfortable with.
But “how do I effectively forage for edible mushrooms” is a great stepping stone.
Kiwix is great, but I'd also like a language model to be able to deeply interrogate all of that information much faster than I can read.
Just arrange its harness so that its responses are grounded in the source material and require source citations for everything. Then read the citations to confirm it's not a hallucination.
I like this "both / and" approach. Restructure this project to have the LLM source from local Kiwix data you've selected to make available offline, rather than a source of data you're unfamiliar with. References point directly to your Kiwix library.
I think that for situations like this we should invent a device that can hold information for an arbitrary amount of time even without electricity. Maybe we could call it "BOOK" or something like that.
This isn't clever or insightful. You can of course condense down critical information into a survival handbook, but in existential crises you don't necessarily know in advance what you'll need to know. Wikipedia (as a benchmark repository of knowledge) is ~5 million pages and would require a decent-size room to store if printed out. By contrast, a laptop + solar panel can fit in a backpack. SD cards/USB sticks with the capacity to store all of Wikipedia are a few $ each.
If things are so bad that you need to factor in the non-operability of any electronic devices, how many indestructible paper libraries are you planning to build and manage in advance, and at what budget?
That seems to have been mostly solved through scale. I was asking Opus 5.5 about some obscure stuff and it kept hedging "this is from memory since I don't have internet access" (it's sandboxed), "I'm reasonably sure about this but not about the numbers" etc.
Even though it was obscure enough that Google couldn't easily find the paper that Opus remembered (I couldn't find it at all with the traditional search results; the AI summary found it on my third try), it actually didn't hallucinate it.
In fact I can't remember Opus 5.5 ever hallucinating. They've clearly done some work on that.
Obviously this local LLM is going to hallucinate all over you though.
It already is a local archive that can be searched independently, but the LLM does RAG and is, according to them, 95% accurate. It can be useful if you don’t remember where to find a source/what words to search for, but even a durable device with Kiwix would be useless in a a lot of survival situations people imagine.
Undoubtedly useful in the right contexts, particularly for local repair or homesteading, but “survival” does imply that this would be more useful in an SHTF situation.
> Mac or PC with 16–31 GB | IBM Granite 4.2 8B | 14 of 22 right | 6 GB
So on a regular consumer machine this is going to be wrong nearly half the time. Great! Let’s hope it’s only on the simple stuff and not the “how do I perform an emergency appendectomy”.
Or just.. download the books, and slap a search engine on top of them. It'll be like 10x smaller than the model. "Survival LLM" is absolutely a non-relevant use case.
When you’re living in an igloo trying to stay warm in the hollowed out belly of a cow having a few books around the place is probably more useful than some files on a laptop that ran out of battery just before it got morbidly damp. Plus you can burn them if you really need to.
On the other hand, the laptop struggling to power a good-enough LLM will probably be a great heat source for you in that igloo... for about 45 minutes.
As I said elsewhere, you can always burn the books! And eating a laptop is considerably crunchier and more fraught than chewing through some good old fashioned leather facings, horse glue and nice heavy 120gsm wove.
Yes I slightly mangled that one. But I’m sure there is a survival technique that involves crawling into the body cavity of a hollowed out cow. You probably wouldn’t want to do that in an igloo though. I’m not even sure you could get a cow into an igloo. If standard issue humans are this flawed it’s hardly surprising that top flight LLMs get things so wrong sometimes.
The advantage of a turn-by-turn flow (honestly the chat interface was genius) is that with a little human intervention you can get much better results out of even silly models. The model of choice is strange, though. Not a particularly good one.
People apparently like Granite for RAG specifically. I'm not aware of any evaluations with numbers though, so I'm not sure if it's a real difference or just vibes.
Either it depends a lot on the model, or I’m bad at chat, or both, because in my experience once a chat starts going off the rails it’s pretty hard to correct the initial misconception. I find it works better to backtrack to just before the misconception and edit my previous response to head it off at the pass.
Definitely agreed that it's better to not have some text in the context than to have some that needs to be opposed. I suppose I meant steering prompts are a non-obvious innovation to LLM interaction.
We had a set called something like “How to do anything in an emergency” which had instructions for this and more. Alongside lots of creative uses of potassium permanganate.
I’m pretty sure it also told you how to butcher a sheep.
I used to be obsessed with it as a kid. The spectre of nuclear war and a three volume handbook on how to survive the impending apocalypse with nothing more than a plastic bucket, a packet of potassium permanganate, some charcoal and string. The late 80s and early 90s were a wild time to be a kid.
I have a bunch of military field manuals and survival guides, but they all implicitly presume the existence and contactability of civilization sooner or later. Realistically, some pocket computer(s) and solar charger(s) will store far more information, be far more portable, and give you more carrying capacity for things like medical supplies, rope, tools, and other hard-to-substitute items.
Have you re-read it recently? Some of those books were fun to read but not really something to use as a field manual. Then again some of them were great! I had a book that started with explaining how a battery and a light globe worked, went through how to make a DC motor out of copper wire and a cork, and ended with a crystal radio and I think a radio homing beacon (the latter might have been in another book.)
I have not, sadly. But I’m pretty sure I also had the book you mention. My brother and I made our own motor and many other things that would now be considered entirely unsuitable for 10 year olds to be doing. Copper sulfate crystals seem like a great idea until you have to explain why the playroom carpet has melted.
I'm not a doomsday prepper but man if you need to run an LLM locally during the apocalypse to figure out how long your food is going to last, I feel like you are in for a tough time.
This kind of stuff really feels like knowledge that probably shouldn't be offload to AI but rather learned and practiced. Again, I don't have a bunker in my backyard but seems like a weird use case.
212MB for MacOS and 25MB for Windows? Why are MacOS binaries so large? Is it typical for them to be 10x Windows binary size?
That said, I'm really looking forward to small and quick (latency wise) models are a reality. I can easily see a world where every keystroke, terminal command, etc. goes through a "autocorrect" type model. You could even blend natural language plus terminal program segments and the AI just infers what you intend. Either built-in or a second classifier model, determines if the autocorrect change needs human review first.
I have some property that doesn't really get cell reception in the summer, and even in the winter the reception is at-best spotty. I use granite and qwen together with a manually curated set of books, articles, etc. to get work done while disconnected. I tend to update the set of resources before leaving town because I'm generally intentionally disconnecting to focus on deep work. Building a workflow that makes that possible has helped me build out a setup that replaces a ton of my day-to-day anthropic/openai use even when I'm near fiber.
It is interesting how, even pre-llms, offline computers change the nature of a lot of activities. E.g., about once a year I'll walk do a random walk in the woods for a few days without paying much attention to maintaining a bearing. With maps and compasses it's a whole skill set to find your way back. With a phone and downloaded maps you just kinda press the power button and check your heading every hour or two.
The "survival" use-case is interesting. I fear a lot of the practical applications of that knowledge are either time-sensitive (e.g., RAG on a "Stop The Bleed" course won't help because by the time you learn the patient is dead) or require tools+skills that aren't easily improvised completely from scratch in high-stress situations (e.g., building shelter or even really simple stuff like building a fire when it's very cold out). And for other stuff common sense prevails (e.g., power out -> keep fridge closed).
I give it about 50/50 the internet goes down or becomes effectively unusable for weeks, maybe months, at some point in the next 5 years given abysmal commitment to cybersecurity from almost every company that exists.
Some kid with the right prompt will supply chain attack a dependency of a dependency of firmware for border routers just to watch the world burn, or runaway AI swarms will saturate all bandwidth. Or a Linux kernel zero-click vuln. So many ways this can happen.
I would suggest Hammunition, https://github.com/Renegade-Penguin/Hammunition with install docs at https://renegade-penguin.github.io/Hammunition/ . Hammunition offers much more info than Nomad for SHTF type emergencies. Hammunition uses KIWIX tools instead of an LLM to search the reference sources that you downloaded (eg. Wikipedia, etc.). You can install it on a Linux distro on a 500 GB external SSD drive that you can pick up for $100 at Microcenter. It is geared toward people interested in ham radio, but you can listen only on the ham radio bands without a ham license.
I just use llama cpp , it's light weight, I think you create your own integrations, with a larger model so llama cpp can interract with scripts that would browse the web, control your computer etc... propably will have to download some pip packages
Great idea, I do a lot of work testing small LLM's in this space and agree if you add some guardrails and train a small embedder, you won't need these large models, as your info is static, you can ship it all as one.
If every single example posted has hallucinations and the response is "it's your fault for not checking the sources" then it's obvious that an LLM isn't the right tool for the job. A search engine works perfectly fine for these kinds of datasets.
It's pretty cool. But if it's such a small model and small corpus, isn't it almost just as good just to have a static wikipedia-style copy of those key sources (WikiMed, MedlinePlus, Ready.gov, CDC etc.)? Maybe if they (and that could be static too), gave you a "what's going on?" question and then told you what you might not know - i.e. "power is out" -> "make sure you open your fridge as little as possible", "if you have backup battery ensure you turn power hungry devices off" etc.?
Back in 2018 I was working on a project for educating schools in certain parts of Africa and Middle East, on AI. The issue was it had to be air-gapped (no internet guarantees) and small/portable. I ended up downloading Wikipedia (not all of it), and then created a lightweight inverted index (for search) and TextRank (for summaries). The whole thing was on a Raspberry Pi, and installed in a small plastic enclosure. We had many of these and could easily ship them. There was an "AI Learning Module" as well we built, that started with Scratch, and then moved into Python. But if I was to do it all over today, I would probably add a tiny LLM and maybe a small ASR and a TTS model too, and you basically have a completely self-contained AI knowledge assistant in a cigarette box. The point being, you basically also have a "survival AI" you can take with you. Of course you still need electricity...
I went through a category 5 hurricane that took down everything. Prepared by downloading as much as I could ahead of time but it wasn’t enough. This, or something similar, would have been a blessing.
Love this. And as a trend, I'd love to see more local/small task-specific models/agents. Experts at helping you with that one thing, leaving the everything-and-the-kitchen-sink to the frontier models/agents
I'm conflicted here -- on the one hand, you make a good point. Things we take for granted normally are luxuries in a survival sitation. On the flip side, running a generator for a bit to get an LLM to generate schedules, guides, step-by-step that can be edited/followed on a much lower-powered device seems reasonable.
I'm using for the emergency hot tub and hairdryer first. The last thing you want in a state-wide blackout is to be walking around super relaxed but with wet hair..
Solar panels? You can go down to Harbor Freight right now and pick up a setup that will run a laptop or tablet for a while, for a couple of hundred dollars. One wouldn't have to spend a ton more to get a setup that can run a decent PC with a GPU for at least a little while.
I mean, you're probably not going to run it all day, especially not in the part of year with fewer daylight hours, but anything's better than nothing. Plus the same solar setup can be used to power other useful things.
>The app is the same everywhere. When it opens, it checks your computer's memory and downloads the AI model that fits. More memory means a smarter model.
first thing an emergency tool should require, internet access.
at first glance I figured it'd be an ultra small specialty trained survival model that'd be small and runnable anywhere, sorta like an emergency flavored version of those tiny tts models that have been all over recently.
At what point would it be better to download a few real sources and do plain text search? Why risk a hallucination for content that would probably be smaller than the size of the model?!
What this needs is a recipe or script that you can point your local agent at and it builds a bespoke implementation that’s, by definition, highly resilient.
Download a good fast local model e.g. Gemma-4-12B (small machine) or Qwen3.6-35B-A3B (larger memory). Or a Nemotron model, if you prefer that.
Then you'll have both your backup/emergency assistant that runs on your own computer and be gaining skills in a common, frequently-updated, well-supported program.
On the setup process: "You only click for about 5 minutes; the rest is downloading." On the energy consumption: "A small generator or power station runs it easily"
Five minutes of clicking and a (small) power station is a small price to pay when survival could be at stake.
With all due respect: why does this need an LLM, and this much data? Surely a "classic" knowledge base with a more traditional search bar, running on top of the same data this LLM was trained on would be way smaller, and actually as trustworthy as the source material it surfaces for you?
There are a fair number of people who seem to believe that LLMs contain "world knowledge" and are blissfully unaware of how inaccurate an ungrounded chatbot can be. They ask it questions, it gives them confident and plausible (sometimes even correct!) answers, and they leap to the conclusion that these are useful tools for end-of-civilization knowledge bases. I fought this battle countless times on HN and Reddit, generally unsuccessfully.
This project at least attempts to ground its answers with (presumably) human-vetted sources. That will make it much, MUCH more accurate and truthful than a bare model. But there is still a non-zero chance for it to hallucinate answers, especially when posed a question that it doesn't have any source material in its database.
As for why bother hooking up an LLM instead of a simple search engine, search engines don't synthesize data from multiple sources into a coherent answer for you, but LLMs are (mostly) great at that.
That said, while I like this pattern (LLM + knowledge base) for lots of things, this isn't necessarily something I'd trust with my own (or my family's) survival.
Yeah, without the ability to search the web, a very small model is going to be too dumb to be useful, and maybe even dangerous due to hallucinations. But, there is a point where the knowledge of self-hostable models will surprise you. That point is probably not runnable on the average laptop, though. It's maybe in the ~30B range, but more realistically in the 128B MoE range. I guess in their tests Qwen 3.8 27B got as many right as the much larger Nemotron Super, but I'd bet Qwen 3.8 Flash would be better than either, but it needs 128GB of unified RAM or a big GPU and lots of system RAM to run the 4-bit version.
I think if I had to build an emergency LLM today, that had to run on modest hardware, I'd bet on Gemma 4 12B. It's got excellent reasoning and good vision/audio and speaks 140 languages.
But, I don't know about the "classic" knowledge base theory, though. Is there a high quality curated pile of survival information that could be bundled into a web UI and made searchable in a knowledge base? The LLMs aren't focused on that topic, so there's a lot of wasted space, but they know a little about a lot of things, including survival topics. Combined with Wikipedia, and maybe a few other sources, you're probably better off with one than without.
I guess one could use some huge models plus web search to compile/distill a focused survival knowledge base or LLM.
Edit: Project NOMAD seems to mostly be exactly that. It has authoritative sources in a searchable knowledge base and the tiny LLMs are an afterthought, which is probably what they should be. https://www.projectnomad.us/
It's disappointing that Gemma E4B seems to perform poorly on this (42% accuracy according to the GitHub). It would be nice if a $25 phone could be loaded up with this and stuffed in a EMP proof metal box with a small solar charger. Maybe a finetune or Gemma 5 will get us there.
I can almost guarantee you that by the time you need a survival assistant, you won't be willing to spend gasoline on generating electricity for your GPUs.
(It's helpful for shorter outages. But "survival assistant", I think not, unless you run a compound)
This will come in handy after AI takes over the world.
But kidding aside, this is an interesting reveal on the ease with which a custom LLM can be spun up to fit a particular niche application, especially for systems not meant to host an LLM.
If you're actually offline and need information in a 'survival' situation, I'm not so sure the hallucinatory nature of an LLM is the based way to distribute a repository of information. Additionally, there's no need to fit an LLM entirely in memory.
In a theoretical scenario where the internet is gone and isn't coming back: If you can deal with a very low token/second rate there's no reason not to store 'offline' a much larger model like qwen 3.8-flash-next or deepseek v4 flash 1017 and use an inference engine which can stream-read it off disk to extract the information you want, albeit slowly. Of course also download and use things that'll fit in RAM, sure, like the qwen 3.8 27B in the linked page. But no need to restrict yourself to only smaller models.
Agreed. Especially for something like this, in which many imaginable situations would require the ability to run on Linux rather than MacOS or Windows, pretty strange.
Please, please do not trust a chatbot in emergencies. There’s a reason why actual survival and emergency preparedness guides include manuals rather than recommend you just use a chatbot: practicality.
Just look at those specs needed for accurate-ish results. You really think your 128GB Mac Studio or Framework desktop is going to be able to work in a real emergency situation? Even if it is, how long will it last? What about those precious seconds waiting for inference?
The danger here is less hallucinations and more, well, everything else about it. Instead of setting this up, take the time to make sure you have a restocked first aid kit and enough water for a week of use by your household. Stock up on meds and non-perishable food. Plan exit strategies and contingencies. Acquire and store little first aid booklets or manuals of common survival tasks in physical form (or hell, throw onto an eReader - infinitely more battery life than an LLM host in an emergency).
This is one of those “sounds good in my head” projects that folks with emergency experience would bristle at. This is a hindrance, not a helper.
No thanks, I'll use a generic model along with trusted sources.
Also: "Apple could not verify “Survival LLM” is free of malware that may harm your Mac or compromise your privacy." This is obviously some vibe coded trash from an inexperienced dev.
> Also: "Apple could not verify “Survival LLM” is free of malware that may harm your Mac or compromise your privacy." This is obviously some vibe coded trash from an inexperienced dev.
This is a great example of how Apple's "scare warnings" completely work to mislead folks about what they are actually warning you about.
This topic is bringing out the hallucination-panic crowd.
It's perfectly safe to use LLMs to surface underlying data and knowledge without having to trust that it's giving you correct advice.
Use the LLM as search technology: string match -> semantic search -> search intelligence.
This is especially helpful when you don't know the right question to ask. Semantics only help you find text that is semantically near the input query. Semantics won't help you when what you are looking for is connected to what you have by something other than semantics, like causation, mechanism, or interpretation.
Trying to figure out why your crops aren't growing well will likely require you to read several articles across a range of sciences, probably scoped to the specific conditions you are dealing with. A semantic search is not going to surface those first.
Allowing an LLM to chain together several sources for you to read first does not require you to ask it for a conclusion.
The readme on Github does say the system produces hallucinated sources https://github.com/anonnerdfrenzy/survival-llm#how-the-model..., but really you're correct, for this kind of highly targeted use case the LLM's summary could probably be ignored entirely and the system could work extremely well even just as a search engine: index all of the content up front, chunked by paragraph and maybe enriched with a HyDE step, have the LLM facilitate running a handful of hybrid keyword/semantic searches based on the user's question and reranking the results, and show the exact pieces of text in the corpus that are most responsive to their question. No summary needed.
A great strength of LLMs is how they provide useful answers even if the prompt has glaring spelling or grammatical mistakes. If your prompt is not great, as you said, they will reply in a way that helps you identify that flaws, and learn how to steer the model better.
They're amazingly useful tools, but they're nowhere the level believers want them to be, not yet.
Yes this has been very useful for me this week. I trapped my middle finger on my right hand in a door and it really messed up my typing.
I tried using dictation but I really disliked speaking to it.
You can write a really messed up sentence and it almost always worked out what I meant.
Quite amazing actually
Can a bad LM implementation surface bad references? Yes. Are LMs overwhelmingly useful for research? Yes.
Is a bad LM implementation still useful for research? Shmaybe.
In a true emergency, there are often many cases where you need not just information retrieval, but "thinking and reasoning" to deal with unprecedented situations, right? Is it technically possible to balance lightweight local performance with thinking capability, while avoiding the risk of hallucinations in life-or-death instructions?
But at this point why even bring a full model into scope in the first place.. just run some cheap embedding retriever
Nevermind hallucinations, the donkey-work is important; why bypass the hours of research, which trains our in-built LLM and can lead to new realizations, and get the carrot without much effort? This LLM stuff feels like a candybar; the anticipation of the magic feels good, the thing tastes good while you're eating it, and everything thereafter is shit, but we easily forget, and reach for the next candybar. I appreciated Blindboy Boatclub's take in his podcast episode "Artificial intelligence is Disgusting and it will never replace Artists" from 2026 March 17. I also appreciate Electrical Engineer & Computer Scientist Timnit Gebru's perspective on these stochastic parrots. While intraspecies diversity confers, up to a point, a survival benefit, consider the long-term consequences of playing this particular game. We don't have to eat every candybar the rich mostly-guys ply us with.
The premise in this case is to get answers quickly in an emergency situation. You don’t want to tell the person with a burn injury to wait a bit since you always wanted to learn how burns are treated.
You also don’t want to get advice like that cooking advice to make a glue pizza.
Shoutout to project nomad.
https://www.projectnomad.us/
its got a ton of useful options, preconfigured, integrates pretty easily, and can use any local LLM or data.
Interesting. I have a mac mini I run headless dedicated for LLM inference. Do you know if I could run project nomad on a linux box but use qwen on the mac for the AI stuff? I can't find any info on if this configuration is possible.
Sure can. I did similar.
We need this, but running on smartphones.
Also, I am surprised that the difference between 32GB and 128GB in right answers is so small:
* Mac with 128 GB or more memory NVIDIA Nemotron 3.5 Super 21 of 22 right 80 GB
* Windows PC with 32 GB or more NVIDIA Nemotron 3.5 Lightning 19 of 22 right 25 GB
I set this up on my machine and tested it with the following question:
How can I build a bow drill so I can start a fire?
It got it partially right: spindle, bow with string tied the correct way, and fire board. But then it flubbed by saying you put the spindle between both hands and move your hands back and forth to rotate the spindle and create the necessary friction… this totally ignores using the bow to rotate the spindle! It also mentioned “fanning the sparks” but there is absolutely no way your bow drill is going to create sparks.
I asked a frontier model to check the survival LLM’s conversation trace and it pointed out the errors.
I didn’t see obvious errors in the other 3 prompts I used, but this one seemed pretty egregious for a survival LLM.
I thank the creator for making this, but take it with a grain of salt.
Did it give you the source(s) so you could double check?
Giving incorrect instructions and saying "go check the sources" is worse than just returning the sources. Aka a search engine.
That's why the question was whether it gave sources, not whether they asked it to go check sources. Yeah, LLMs suck and you should always assume false information. 80% accurate is not production ready.
Considering the tendency even now of LLMs to hallucinate, and the hardware requirements for any kind of LLM -why not just gather those resources into some sort of local archive that can be searched without an LLM?
This seems redundant and requiring more overhead while providing less reliability than something like Kiwix to me.
Not sure about how the code in this project works. But the way I see it, an LLM+chat is a great interface for information. If you then connect it to a db with the knowledge/articles you need, then you get a great way to navigate it, without needing the model to memorize all the info
I think that if I were to build this I might skip the LLM and just setup a nice interface to the source files using qmd style search. [0]
That way the tiny model isn't acting as a potentially incorrect interpreter but you still get semantic search to help you find the right documents quickly.
I suppose there is something to be said for a good summarization, I just worry that these tiny models aren't really GOOD summarizers.
[0] https://github.com/tobi/qmd
Awesome, I didn't know qmd style search, thank you!
I'm all up for using the better/simpler task for the job. That's been a thing lately also with the Jev/decision models hype, most of those things can either already be done by a pretrained classifier[0], or you can start with a bigger model and then train your smaller/adhoc one when you have some data (it doesn't even take much for most applications, you can get about 95% accuracy on email classification with 50-100 examples)
0: http://jeffyclassify.com/blog/when-llms-fail-at-classificati...
I agree with the OP; this technology does not seem an appropriate fit for survival equipment. By definition survival scenarios can be life and death. Even one "You're absolutely right!" level mistake from an LLM could give a user bad information, leading to John Doe eating a mushroom he really should not have eaten.
I agree with your point, but if John Doe is foraging mushrooms without experience of the local flora (which I doubt this archive contains), then John Doe is kinda asking for it.
The bigger issue in this context would be canning, such as incorrectly explaining the mechanisms to avoid botulism (acid and/or pressure canning), or perhaps incorrectly wiring in repairs. However, again, it’s best to practice with these prior to emergencies anyway.
It should be noted though, that the model does source its claims, so you can fact check it and should review this information regularly.
Slight OT Survival tip, if you are starving don't go for mushrooms in the first place (unless you really, really know) - even if you get the right one, they don't contain much energy for you to burn anyway. The larves you often found in them, probably contain more. So mushrooms are a nice addition (and in rare cases good medicine), but for survival you should focus on something else.
Why not both? After the collapse of civilization, as long as you can maintain the computer running, you could educate the next generation as soon as they could write. Maybe they will bypass the local agent as they learn their way into the library, to save energy.
Consider they won't have access to the plentiful practice opportunities we have now, most resources would have to be spent with a practical goal.
Survival implies that energy would definitely be a very limited resource. Using it to replace knowledge is just... I can't describe it even. Why not just learn it on our own and keep a small guidebook in your backpack. Our overrelience on computers and now LLMs, even for basic life-saving knowledge is simply our way of going the way of the dodo... I use frontier models at work, I definitely get more done. However I will never use it as a replacement of my own knowledge.
Both. Both is good.
A field guide to foraging for edible mushrooms will probably be more practical than naïve use of an LLM: “can I eat this mushroom?” is an exercise in trust that I will maybe never be comfortable with.
But “how do I effectively forage for edible mushrooms” is a great stepping stone.
> After the collapse of civilization, as long as you can maintain the computer running ...
One of these situations prohibits the other.
Nvidia GPUs in the post-apocalyptic radioactive barrens are going to be stupid pricey.
Decent LLMs can run on anything now: https://github.com/he-be/turbo-fieldfare
Kiwix is great, but I'd also like a language model to be able to deeply interrogate all of that information much faster than I can read.
Just arrange its harness so that its responses are grounded in the source material and require source citations for everything. Then read the citations to confirm it's not a hallucination.
>can run on anything now: (link to turbo fieldfare)
Except the build process there requires a specific recent version of swift. Hardly a good definition of "anything"
I like this "both / and" approach. Restructure this project to have the LLM source from local Kiwix data you've selected to make available offline, rather than a source of data you're unfamiliar with. References point directly to your Kiwix library.
> and the hardware requirements for any kind of LLM
You can run bonsai2 27b on basically any gaming GPU from the last 15 years including on game consoles.
Everyone has access to this stuff now if they bothered to look beyond the marketing from big labs trying to collect subscription revenue.
I work on compilers, kernels, and operating systems using exclusively consumer GPUs.
I think that for situations like this we should invent a device that can hold information for an arbitrary amount of time even without electricity. Maybe we could call it "BOOK" or something like that.
This isn't clever or insightful. You can of course condense down critical information into a survival handbook, but in existential crises you don't necessarily know in advance what you'll need to know. Wikipedia (as a benchmark repository of knowledge) is ~5 million pages and would require a decent-size room to store if printed out. By contrast, a laptop + solar panel can fit in a backpack. SD cards/USB sticks with the capacity to store all of Wikipedia are a few $ each.
If things are so bad that you need to factor in the non-operability of any electronic devices, how many indestructible paper libraries are you planning to build and manage in advance, and at what budget?
The pedanticty (or is it pedanticness???) on hn is astonishing sometimes.
If there's any place to get an answer it's here.
Bravo my friend. And I mean that in a good way. Love me some diversity.
and then we have a lot of “books” so we collect them in “shelves” then in “libraries” then we want to search them etc etc
> the tendency even now of LLMs to hallucinate
That seems to have been mostly solved through scale. I was asking Opus 5.5 about some obscure stuff and it kept hedging "this is from memory since I don't have internet access" (it's sandboxed), "I'm reasonably sure about this but not about the numbers" etc.
Even though it was obscure enough that Google couldn't easily find the paper that Opus remembered (I couldn't find it at all with the traditional search results; the AI summary found it on my third try), it actually didn't hallucinate it.
In fact I can't remember Opus 5.5 ever hallucinating. They've clearly done some work on that.
Obviously this local LLM is going to hallucinate all over you though.
It already is a local archive that can be searched independently, but the LLM does RAG and is, according to them, 95% accurate. It can be useful if you don’t remember where to find a source/what words to search for, but even a durable device with Kiwix would be useless in a a lot of survival situations people imagine.
Undoubtedly useful in the right contexts, particularly for local repair or homesteading, but “survival” does imply that this would be more useful in an SHTF situation.
From the site:
>Survival LLM >It Can be wrong
thank you!
> Mac or PC with 16–31 GB | IBM Granite 4.2 8B | 14 of 22 right | 6 GB
So on a regular consumer machine this is going to be wrong nearly half the time. Great! Let’s hope it’s only on the simple stuff and not the “how do I perform an emergency appendectomy”.
Honestly, just buy some books.
Or just.. download the books, and slap a search engine on top of them. It'll be like 10x smaller than the model. "Survival LLM" is absolutely a non-relevant use case.
When you’re living in an igloo trying to stay warm in the hollowed out belly of a cow having a few books around the place is probably more useful than some files on a laptop that ran out of battery just before it got morbidly damp. Plus you can burn them if you really need to.
On the other hand, the laptop struggling to power a good-enough LLM will probably be a great heat source for you in that igloo... for about 45 minutes.
As I said elsewhere, you can always burn the books! And eating a laptop is considerably crunchier and more fraught than chewing through some good old fashioned leather facings, horse glue and nice heavy 120gsm wove.
On the other hand, if you know enough to build an igloo, you're probably going to be ok regardless.
"cow in an igloo" sounds like something an LLM would hallucinate.
Yes I slightly mangled that one. But I’m sure there is a survival technique that involves crawling into the body cavity of a hollowed out cow. You probably wouldn’t want to do that in an igloo though. I’m not even sure you could get a cow into an igloo. If standard issue humans are this flawed it’s hardly surprising that top flight LLMs get things so wrong sometimes.
And/or install Kiwix and grab an offline copy of Wikipedia.
If you have AI model there it can make any search engine for you as per your needs.
The advantage of a turn-by-turn flow (honestly the chat interface was genius) is that with a little human intervention you can get much better results out of even silly models. The model of choice is strange, though. Not a particularly good one.
People apparently like Granite for RAG specifically. I'm not aware of any evaluations with numbers though, so I'm not sure if it's a real difference or just vibes.
Either it depends a lot on the model, or I’m bad at chat, or both, because in my experience once a chat starts going off the rails it’s pretty hard to correct the initial misconception. I find it works better to backtrack to just before the misconception and edit my previous response to head it off at the pass.
Definitely agreed that it's better to not have some text in the context than to have some that needs to be opposed. I suppose I meant steering prompts are a non-obvious innovation to LLM interaction.
What is your favorite book on emergency appendectomies?
We had a set called something like “How to do anything in an emergency” which had instructions for this and more. Alongside lots of creative uses of potassium permanganate.
I’m pretty sure it also told you how to butcher a sheep.
I used to be obsessed with it as a kid. The spectre of nuclear war and a three volume handbook on how to survive the impending apocalypse with nothing more than a plastic bucket, a packet of potassium permanganate, some charcoal and string. The late 80s and early 90s were a wild time to be a kid.
I have a bunch of military field manuals and survival guides, but they all implicitly presume the existence and contactability of civilization sooner or later. Realistically, some pocket computer(s) and solar charger(s) will store far more information, be far more portable, and give you more carrying capacity for things like medical supplies, rope, tools, and other hard-to-substitute items.
Have you re-read it recently? Some of those books were fun to read but not really something to use as a field manual. Then again some of them were great! I had a book that started with explaining how a battery and a light globe worked, went through how to make a DC motor out of copper wire and a cork, and ended with a crystal radio and I think a radio homing beacon (the latter might have been in another book.)
I have not, sadly. But I’m pretty sure I also had the book you mention. My brother and I made our own motor and many other things that would now be considered entirely unsuitable for 10 year olds to be doing. Copper sulfate crystals seem like a great idea until you have to explain why the playroom carpet has melted.
Granite is not great at any size. Wonder why they picked that.
Given the whole thing reeks of vibe I don’t think anyone picked anything.
I'm not a doomsday prepper but man if you need to run an LLM locally during the apocalypse to figure out how long your food is going to last, I feel like you are in for a tough time.
This kind of stuff really feels like knowledge that probably shouldn't be offload to AI but rather learned and practiced. Again, I don't have a bunker in my backyard but seems like a weird use case.
212MB for MacOS and 25MB for Windows? Why are MacOS binaries so large? Is it typical for them to be 10x Windows binary size?
That said, I'm really looking forward to small and quick (latency wise) models are a reality. I can easily see a world where every keystroke, terminal command, etc. goes through a "autocorrect" type model. You could even blend natural language plus terminal program segments and the AI just infers what you intend. Either built-in or a second classifier model, determines if the autocorrect change needs human review first.
They bundle both python and ollama in that app bundle, and the ollama folder is something like 500MB unpacked , bundled python I think was 80MB.
Not sure what they do on the windows side.
Cool project.
I have some property that doesn't really get cell reception in the summer, and even in the winter the reception is at-best spotty. I use granite and qwen together with a manually curated set of books, articles, etc. to get work done while disconnected. I tend to update the set of resources before leaving town because I'm generally intentionally disconnecting to focus on deep work. Building a workflow that makes that possible has helped me build out a setup that replaces a ton of my day-to-day anthropic/openai use even when I'm near fiber.
It is interesting how, even pre-llms, offline computers change the nature of a lot of activities. E.g., about once a year I'll walk do a random walk in the woods for a few days without paying much attention to maintaining a bearing. With maps and compasses it's a whole skill set to find your way back. With a phone and downloaded maps you just kinda press the power button and check your heading every hour or two.
The "survival" use-case is interesting. I fear a lot of the practical applications of that knowledge are either time-sensitive (e.g., RAG on a "Stop The Bleed" course won't help because by the time you learn the patient is dead) or require tools+skills that aren't easily improvised completely from scratch in high-stress situations (e.g., building shelter or even really simple stuff like building a fire when it's very cold out). And for other stuff common sense prevails (e.g., power out -> keep fridge closed).
I give it about 50/50 the internet goes down or becomes effectively unusable for weeks, maybe months, at some point in the next 5 years given abysmal commitment to cybersecurity from almost every company that exists.
Some kid with the right prompt will supply chain attack a dependency of a dependency of firmware for border routers just to watch the world burn, or runaway AI swarms will saturate all bandwidth. Or a Linux kernel zero-click vuln. So many ways this can happen.
Better to prepare a bit and never need it.
The required specs seemed a bit high to me, and I was just looking for alternatives.
I found Project Nomad (https://projectnomad.us) which looks more polished. Any other suggestions?
I would suggest Hammunition, https://github.com/Renegade-Penguin/Hammunition with install docs at https://renegade-penguin.github.io/Hammunition/ . Hammunition offers much more info than Nomad for SHTF type emergencies. Hammunition uses KIWIX tools instead of an LLM to search the reference sources that you downloaded (eg. Wikipedia, etc.). You can install it on a Linux distro on a 500 GB external SSD drive that you can pick up for $100 at Microcenter. It is geared toward people interested in ham radio, but you can listen only on the ham radio bands without a ham license.
I just use llama cpp , it's light weight, I think you create your own integrations, with a larger model so llama cpp can interract with scripts that would browse the web, control your computer etc... propably will have to download some pip packages
Great idea, I do a lot of work testing small LLM's in this space and agree if you add some guardrails and train a small embedder, you won't need these large models, as your info is static, you can ship it all as one.
Or try these with your trained embedder: https://ollama.com/library/minicpm-v4.6 https://ollama.com/library/bonsai-2
If every single example posted has hallucinations and the response is "it's your fault for not checking the sources" then it's obvious that an LLM isn't the right tool for the job. A search engine works perfectly fine for these kinds of datasets.
It's pretty cool. But if it's such a small model and small corpus, isn't it almost just as good just to have a static wikipedia-style copy of those key sources (WikiMed, MedlinePlus, Ready.gov, CDC etc.)? Maybe if they (and that could be static too), gave you a "what's going on?" question and then told you what you might not know - i.e. "power is out" -> "make sure you open your fridge as little as possible", "if you have backup battery ensure you turn power hungry devices off" etc.?
Back in 2018 I was working on a project for educating schools in certain parts of Africa and Middle East, on AI. The issue was it had to be air-gapped (no internet guarantees) and small/portable. I ended up downloading Wikipedia (not all of it), and then created a lightweight inverted index (for search) and TextRank (for summaries). The whole thing was on a Raspberry Pi, and installed in a small plastic enclosure. We had many of these and could easily ship them. There was an "AI Learning Module" as well we built, that started with Scratch, and then moved into Python. But if I was to do it all over today, I would probably add a tiny LLM and maybe a small ASR and a TTS model too, and you basically have a completely self-contained AI knowledge assistant in a cigarette box. The point being, you basically also have a "survival AI" you can take with you. Of course you still need electricity...
I went through a category 5 hurricane that took down everything. Prepared by downloading as much as I could ahead of time but it wasn’t enough. This, or something similar, would have been a blessing.
Love this. And as a trend, I'd love to see more local/small task-specific models/agents. Experts at helping you with that one thing, leaving the everything-and-the-kitchen-sink to the frontier models/agents
Emergencies = No Internet
What about no power? You gonna run your generator for your local model? What are we doing here? Have we lost our way completely?
I'm conflicted here -- on the one hand, you make a good point. Things we take for granted normally are luxuries in a survival sitation. On the flip side, running a generator for a bit to get an LLM to generate schedules, guides, step-by-step that can be edited/followed on a much lower-powered device seems reasonable.
I'm using for the emergency hot tub and hairdryer first. The last thing you want in a state-wide blackout is to be walking around super relaxed but with wet hair..
Generators require the infrastructure that supplies fuel, and you need to have a generator you might not need.
Solar panels and batteries are great for emergencies, and they're useful besides.
Yeah, we forgot information on paper it seems. Flawed as it is I like the idea though..
> What about no power?
Solar panels? You can go down to Harbor Freight right now and pick up a setup that will run a laptop or tablet for a while, for a couple of hundred dollars. One wouldn't have to spend a ton more to get a setup that can run a decent PC with a GPU for at least a little while.
I mean, you're probably not going to run it all day, especially not in the part of year with fewer daylight hours, but anything's better than nothing. Plus the same solar setup can be used to power other useful things.
this is more like .. survival harness, no?
>The app is the same everywhere. When it opens, it checks your computer's memory and downloads the AI model that fits. More memory means a smarter model.
first thing an emergency tool should require, internet access.
at first glance I figured it'd be an ultra small specialty trained survival model that'd be small and runnable anywhere, sorta like an emergency flavored version of those tiny tts models that have been all over recently.
Maybe that's an idea for someone.
I like to use llamafile for cases like this: https://github.com/mozilla-ai/llamafile
At what point would it be better to download a few real sources and do plain text search? Why risk a hallucination for content that would probably be smaller than the size of the model?!
Really cool idea! Will give it a spin.
I’m currently using https://kiwix.org for the offline access to Wikipedia, but your Survival LLM looks even better.
Wonder why they didn’t run Qwen 3.5 9b on 16th Macs. That’s a super impressive model for size. Is granite better?
Sorry if this is a dump question but I was wondering why not fine tuning each model to get 100% accuracy on those topics?
I made it a while ago now, but similar: https://github.com/x3haloed/eowkit
Helps you download a local LLM and offline Wikipedia. Probably easier to just ask your favorite agent to glue something together yourself these days.
I like how both these projects seem to imply that in the event of an EOW scenario linux users can just f##k right off, thank you very much. xD
I saw emergency and I immediately thought in case I couldn't access online docs or get my coding/platform questions answered day-to-day.
Apocalypse emergency I don't need help on. My crisis brain has collected more than enough info and capabilities over the decades.
What this needs is a recipe or script that you can point your local agent at and it builds a bespoke implementation that’s, by definition, highly resilient.
Edit: see project nomad.
This could be made a lot more practical (and safer) if made searchable via a simple vector search / embedding that can run on any ordinary computer.
The source (data collection) seems the most important feature here worth reusing.
Odd that it doesn’t run on phones. It isn’t that large, 212MB on a Mac. Phones are basically everyone’s EDC and most are quite powerful.
That’s just the size of the app. It then downloads the appropriate model given the specs of the machine.
Alternate idea: Download Unsloth Studio https://unsloth.ai/docs/new/studio#quickstart
From the command line: unsloth studio
Browse to the URL it gives you (eg http://127.0.0.1:8888/)
Download a good fast local model e.g. Gemma-4-12B (small machine) or Qwen3.6-35B-A3B (larger memory). Or a Nemotron model, if you prefer that.
Then you'll have both your backup/emergency assistant that runs on your own computer and be gaining skills in a common, frequently-updated, well-supported program.
The only way Big AI labs will sell us appliances is when the internet was somehow destroyed.
Not sure where this would fit in.
Qwen 3.8 27B runs well on my laptop. And I can fit terabytes of human knowledge on it.
When I quit the app, why is it still running in the background?
pretty cool I like it. could you support more (small) models in the future, e.g. from the qwen or gemma family?
Nice idea! I wonder how the installed IBM Granite 4.2 8B LLM does on machines with "modest" RAM
Can this work with ollama?
On the setup process: "You only click for about 5 minutes; the rest is downloading." On the energy consumption: "A small generator or power station runs it easily"
Five minutes of clicking and a (small) power station is a small price to pay when survival could be at stake.
With all due respect: why does this need an LLM, and this much data? Surely a "classic" knowledge base with a more traditional search bar, running on top of the same data this LLM was trained on would be way smaller, and actually as trustworthy as the source material it surfaces for you?
There are a fair number of people who seem to believe that LLMs contain "world knowledge" and are blissfully unaware of how inaccurate an ungrounded chatbot can be. They ask it questions, it gives them confident and plausible (sometimes even correct!) answers, and they leap to the conclusion that these are useful tools for end-of-civilization knowledge bases. I fought this battle countless times on HN and Reddit, generally unsuccessfully.
This project at least attempts to ground its answers with (presumably) human-vetted sources. That will make it much, MUCH more accurate and truthful than a bare model. But there is still a non-zero chance for it to hallucinate answers, especially when posed a question that it doesn't have any source material in its database.
As for why bother hooking up an LLM instead of a simple search engine, search engines don't synthesize data from multiple sources into a coherent answer for you, but LLMs are (mostly) great at that.
That said, while I like this pattern (LLM + knowledge base) for lots of things, this isn't necessarily something I'd trust with my own (or my family's) survival.
Yeah, without the ability to search the web, a very small model is going to be too dumb to be useful, and maybe even dangerous due to hallucinations. But, there is a point where the knowledge of self-hostable models will surprise you. That point is probably not runnable on the average laptop, though. It's maybe in the ~30B range, but more realistically in the 128B MoE range. I guess in their tests Qwen 3.8 27B got as many right as the much larger Nemotron Super, but I'd bet Qwen 3.8 Flash would be better than either, but it needs 128GB of unified RAM or a big GPU and lots of system RAM to run the 4-bit version.
I think if I had to build an emergency LLM today, that had to run on modest hardware, I'd bet on Gemma 4 12B. It's got excellent reasoning and good vision/audio and speaks 140 languages.
But, I don't know about the "classic" knowledge base theory, though. Is there a high quality curated pile of survival information that could be bundled into a web UI and made searchable in a knowledge base? The LLMs aren't focused on that topic, so there's a lot of wasted space, but they know a little about a lot of things, including survival topics. Combined with Wikipedia, and maybe a few other sources, you're probably better off with one than without.
I guess one could use some huge models plus web search to compile/distill a focused survival knowledge base or LLM.
Edit: Project NOMAD seems to mostly be exactly that. It has authoritative sources in a searchable knowledge base and the tiny LLMs are an afterthought, which is probably what they should be. https://www.projectnomad.us/
Have you considered just having a library?
I'd want an Android version...
I recently evaluated LLMs for use for offline navigation, with this very kind of survival scenario in mind: https://fig.blue/posts/directions-from-memory/
tl;dr: Local LLMs are really really bad at offline navigation.
That said, pairing the survival guide with a library is totally the right move.
Why would you want LLM navigation where offline deterministic navigation have been there forever?
it would be useful if it would shrink a little bit
It's disappointing that Gemma E4B seems to perform poorly on this (42% accuracy according to the GitHub). It would be nice if a $25 phone could be loaded up with this and stuffed in a EMP proof metal box with a small solar charger. Maybe a finetune or Gemma 5 will get us there.
Just few days ago I thought digital preppers are soon gonna make something like that. It's a generally good idea.
I'd put in this also a ton of software documentation, minimally for Rust.
And a bunch of scientific literature.
if your computer doesnt work during an emergency because power went out, how will your LLM work?
I can almost guarantee you that by the time you need a survival assistant, you won't be willing to spend gasoline on generating electricity for your GPUs.
(It's helpful for shorter outages. But "survival assistant", I think not, unless you run a compound)
Talos Principle vibes.
This will come in handy after AI takes over the world.
But kidding aside, this is an interesting reveal on the ease with which a custom LLM can be spun up to fit a particular niche application, especially for systems not meant to host an LLM.
If you're actually offline and need information in a 'survival' situation, I'm not so sure the hallucinatory nature of an LLM is the based way to distribute a repository of information. Additionally, there's no need to fit an LLM entirely in memory.
In a theoretical scenario where the internet is gone and isn't coming back: If you can deal with a very low token/second rate there's no reason not to store 'offline' a much larger model like qwen 3.8-flash-next or deepseek v4 flash 1017 and use an inference engine which can stream-read it off disk to extract the information you want, albeit slowly. Of course also download and use things that'll fit in RAM, sure, like the qwen 3.8 27B in the linked page. But no need to restrict yourself to only smaller models.
No GNU/Linux? Meh.
Agreed. Especially for something like this, in which many imaginable situations would require the ability to run on Linux rather than MacOS or Windows, pretty strange.
Please, please do not trust a chatbot in emergencies. There’s a reason why actual survival and emergency preparedness guides include manuals rather than recommend you just use a chatbot: practicality.
Just look at those specs needed for accurate-ish results. You really think your 128GB Mac Studio or Framework desktop is going to be able to work in a real emergency situation? Even if it is, how long will it last? What about those precious seconds waiting for inference?
The danger here is less hallucinations and more, well, everything else about it. Instead of setting this up, take the time to make sure you have a restocked first aid kit and enough water for a week of use by your household. Stock up on meds and non-perishable food. Plan exit strategies and contingencies. Acquire and store little first aid booklets or manuals of common survival tasks in physical form (or hell, throw onto an eReader - infinitely more battery life than an LLM host in an emergency).
This is one of those “sounds good in my head” projects that folks with emergency experience would bristle at. This is a hindrance, not a helper.
How on earth are you going to operate this if you have no electricity?
What are generators and solar panels? Come on.
No thanks, I'll use a generic model along with trusted sources.
Also: "Apple could not verify “Survival LLM” is free of malware that may harm your Mac or compromise your privacy." This is obviously some vibe coded trash from an inexperienced dev.
> Also: "Apple could not verify “Survival LLM” is free of malware that may harm your Mac or compromise your privacy." This is obviously some vibe coded trash from an inexperienced dev.
This is a great example of how Apple's "scare warnings" completely work to mislead folks about what they are actually warning you about.
Not paying the $100 annual extortion fee doesn't make you inexperienced.
You can always not comment.