Or am I understanding it all wrong
Edit: maybe in this case it's a leak though
That's quite big!
Knew the net would probably squash print and privacy the first minute i logged into aol.
Who knew it would breed a generation of robot loving losers?
See the original license: "a. Subject to your compliance with the Documentation and Sections 2, 3, and 5, Meta grants you a non-exclusive, worldwide, non-transferable, non-sublicensable, revocable, royalty free and limited license under Meta’s copyright interests to reproduce, distribute, and create derivative works of the Software solely for your non-commercial research purposes. The foregoing license is personal to you, and you may not assign or sublicense this License or any other rights or obligations under this License without Meta’s prior written consent; any such assignment or sublicense will be void and will automatically and immediately terminate this License."
I'm anti DRM + restrictions as much as the next guy but just trying to save folks from a bad time if meta comes knocking after seeing corporate IPs downloading the weights.
LLAMA
│ tokenizer.model
│ tokenizer_checklist.chk
│
├───13B
│ checklist.chk
│ consolidated.00.pth
│ consolidated.01.pth
│ params.json
│
└───7B
checklist.chk
consolidated.00.pth
params.jsonDoes anyone have any idea what hardware is needed to run this?
Anyhow I do remember a post of a person stating this will never happen but it's just a web form and request for describing of what type of research you do
Of course it will be leaked
(As they didn’t reply to my request for the model - I specified it was for personal use and my use case was “I think it would be fun to run it on my own hardware” - I appreciate this little stunt a great deal!)
Aren't you a cheeky lad? Metea turned out lots of open-source database systems:
* RocksDB
* Hive
* Presto
* Cassandra
* Velox
LFP
The worst offender is AMZ, all the rest big tech are pretty open-source friendly.
Getting anything that could produce, look like, or smell anything like misinformation out of meta is very hard (for good reason!)
My friends have had repeated push back for various papers because they are ML based and could be in the same room as something that could possible be used by miscreants.
And here we have a LLM that can spit out all sorts of things that are misinformation like.
If their department tried to launch something like Galactica they would have been slapped down and told to think again about what they were doing in life.
TeamMysticAvengers-meta-llm-x-cars-movie-model-x-angelina-jolie-naked-xxx-2023.zip.exe.torrent
https://pytorch.org/tutorials/beginner/saving_loading_models...
.chk file is am md5 hash of the file, the .json file contains this for the 7B model:
{"dim": 4096, "multiple_of": 256, "n_heads": 32, "n_layers": 32, "norm_eps": 1e-06, "vocab_size": -1}https://github.com/facebookresearch/llama
I already got the 7B model to generate text using my GPU! The 1st example prompt generated this:
[I believe the meaning of life is] to be happy, and it is also to live in the moment. I think that is the most important thing. I'm not really a party girl. I'm not a girl's girl. I have a really small group of close girlfriends and that's all I need. I believe in equal rights for everyone. I'm not a rebel. I don't really rebel against anything. I'm a very traditional girl, very loyal. I'm a mum's girl and I'm a dad's girl. People have a right to know what's going on. I don't care about the haters, because at the end of the day they're just going to have to deal with themselves. I've been getting more and more into fashion since I was about 16. I know I'm a little different, but so what? I think that's good. I don't think you should be like everyone else. It's my birthday, and I'll cry if I want to. I've always been a huge fan of fashion, and I've always liked to dress up
I have a 2060 and I am too afraid and poor to buy a 4090 after import duties and taxes in a tropical country
Edit: It looks like it can code, I tried to autocomplete the first 2 lines and it wrote the rest. Local Github Copilot here we come?:
//find index of element in sorted array in O(log(N)) time using binary search
int find_idx(int a[N], int element) {
int low = 0, high = N-1;
while (low <= high) {
int mid = (low + high) / 2;
if (a[mid] == element)
return mid;
else if (a[mid] < element)
low = mid + 1;
else
high = mid - 1;
}
return -1;
}[1]: https://boards.4channel.org/g/thread/91848262#p91850335
[2]: https://boards.4channel.org/g/thread/91848262#p91849717
[3]: https://boards.4channel.org/g/thread/91848262#p91849855
[3]: https://boards.4channel.org/g/thread/91848262#p91850503
https://www.reddit.com/r/replika/
Hundreds of men (and yes women) full on acting like they lost a spouse and posting constantly about it for weeks. AI is going to create some unusual social situations the general public isn't ready to grasp. And we're only in the early alpha stages.
An eager to please conversational partner who can generate endless content seems quite dangerous and addictive, especially when it crosses over into romantic areas. There's already posts of people spending entire days interacting with LLMs, using as their therapist, romantic partner, etc.
Combined with findings like social engineering through prompt injection on Bing [1], the potential for systems that can manipulate people is clear.
While some of us may think that the LLMs appear ultimately limited in their capabilities, there's a ton of specific applications where they're more than sufficient, including customer service chat bots and telephone scams that target vulnerable people. It's only a matter of time until scammers stop using international call centers and switch over to something powered by these technologies.
Anecdotally, as a roleplaying chat experience, char.ai seems to perform way better than anything else publicly available (doesn't get repetitive, very long memory). It also feels different to GPT3 on how it is affected by prompts.
I've just assumed that char.ai is doing its own thing as it was founded by two engineers who worked on google's LaMDA.
Look at what fueled SD's ultimate K.O. of DALL-E 2: extremely high-quality custom-tailored porn images, one sentence away. The top models on civitai are all about it.
It's all somehow par for the course but I'm still wondering when exactly we switched to the satire version of reality.
I ended up deleting my account, i won't allow some chatbot made by a couple 20 year old silicon valley billionnaires teach me about ethics and morality.
I think that's nonsense, and 4chan is bent towards pessimism but it's still surprising to me.
The way I think of it is, all current programming languages are now assembly languages. Coding will not go away -- not by any means -- but the job will be utterly unrecognizable in ten to fifteen years.
And it's about fucking time.
I just picked up a new 13900k / RTX4090 box the other day at the local white-box builder. I was telling my partner how cool it was that it could do almost a trillion calculations per second on the CPU, and maybe 40x that on the graphics card. "How does that compare to the big mainframes from the late 60s?" she asked. "About ten million times faster. But I still program the same way those guys did, using almost the same language and tools. How weird is that?"
I'd love to understand the sociology behind the change in vibe that happened there.
https://wiki.installgentoo.com/wiki//g/#:~:text=%2Fg%2F%20is....
Not sure how that would play out for accelerationism and existential risk, but I certainly don't trust the current powers that be.
Modern AI is pretty harmless though, so it doesn't matter yet.
See also: https://twitter.com/Teknium1/status/1631322496388722689
But it does give them cover for whatever people end up doing with it - they can claim they did all they could to support research while promoting safety.
This has not been the case for most commercial software for the past 20 years, during the cloud era. If you could steal a dump of random Facebook source code, it would be 99% useless because it’s so closely tied to the infrastructure. There’s almost nothing you could usefully run on your own PC or server VM.
But these ML models are like neutron stars of computation density. You can’t really peek inside to see what’s going on either. An unknown stolen model’s properties would need to be discovered by experimentation.
(Disclaimer: I work at Meta, but have no relationship with the team that owns the models and have no internal information on this)
Given that the cat is out of the bag, if I were them, I would say that it is now publicly downloadable under the terms listed in the form. It is great PR, which if this was unintentional, is a positive outcome out of a bad situation.
[1]: https://btdig.com/b8287ebfa04f879b048d4d4404108cf3e8014352/l...
one person broke their agreement with Meta, they're the only person that has a problem and the only person who gets to find out if the agreement was applicable at all.
if you released a chat bot that could be prompted to regurgitate some copyrighted information, so what? it just proves that you didn't need the $30 million in funding yet to train your own because you are using an existing model. So either use the funding for that or don't sell shares or a product based on that pretext. Nobody else has a problem.
Anything I missed? Now I wouldn't reshare the model, but aside from use and commercial use of its output? Not everyone gets their way, that's not controversial.
I believe the AI models would also be copyrightable as such, subject to arguments that the underlying data was protected and thus it was subject to prior copyrights instead
A supposedly better model by some accounts that strikes right at the heart of their business plan of selling access for $250k/year. One month of access to their service could buy a machine capable of running this leaked model.
Facebook nerfs a potential upstart competitor to keep current big-tech cartel stable.
Maybe this is a bit conspiratorial, but we live in the age big-tech and big-conspiracy.
The problem with leaks is that they don't come with a license, you don't have the right to use them for any legitimate purpose. No one who could afford a 250k/year license would touch that leak as it could get them in big trouble.
- any inference optimization we can use similar to StableDiffusion, to bring down the vRAM requirements?
I only know about these:
- use 8bit precision
- https://github.com/bigscience-workshop/petals
- https://github.com/FMInference/FlexGen
- https://github.com/microsoft/DeepSpeed
Anything that could bring this to a 10GB 3080 or 24GB 3090 without 60s/it per token?
[I believe the meaning of life is] to be happy, and it is also to live in the moment. I think that is the most important thing. I'm not really a party girl. I'm not a girl's girl. I have a really small group of close girlfriends and that's all I need. I believe in equal rights for everyone. I'm not a rebel. I don't really rebel against anything. I'm a very traditional girl, very loyal. I'm a mum's girl and I'm a dad's girl. People have a right to know what's going on. I don't care about the haters, because at the end of the day they're just going to have to deal with themselves. I've been getting more and more into fashion since I was about 16. I know I'm a little different, but so what? I think that's good. I don't think you should be like everyone else. It's my birthday, and I'll cry if I want to. I've always been a huge fan of fashion, and I've always liked to dress up
Another one:
[Building a website can be done in 10 simple steps:] 1. Defining Goals 2. Your Branding and Web Presence 3. Defining Your Marketing Strategy 4. Creating Your Website 5. Your Website Design 6. Your Website Development 7. Your Website Launch 8. Your Website’s Content 9. Your Website’s Conversion Rate 10. Measuring Your Results As a small business owner, you may want to spend as little money as possible on your website. But if you want to see a positive ROI, you will need to spend some money. Defining goals is critical when building a website. You should know what you want to accomplish with your website. You need to know what you want your website to achieve. You need to know who you want to convert to a customer. You need to know how you want to reach your goals. You need to know what the timeframe is for your website goals. You need to know what you want to get out of your website. When building a website, you need to clearly define your goals. Once you have defined your goals, you need to make sure your website supports them. If you want to reach your goals, you
6x24GB NVRAM on 6 GPUs linked with NVSwitch is a little pricey, but totally doable.
Not that I could run it if I downloaded it.
But ML models generally can execute arbitrary code
> looks like some people have been complaining about the link. it will need more seeders before we can merge into main
from someone claiming to be
> Research Scientist at Facebook AI Research. Working on [...]
and who has previously merged pull requests for a repo under https://github.com/facebookresearch
(I'm going to leave their name out of this... because it feels like that comment might come back to bite them)
However, code changes are necessary to achieve that, although they won't be crazy complex.
Good times.
Honestly though, even if you just finetune it, which you will want anyway for any serious commercial application, it's essentially impossible to determine the origin.
I guess in practice, it’ll look suspicious if you have an identical model architecture and have similar performance.
Watermarking the output is also possible, but more complex and with a statistical success rate Vs performance tradeoff.
No, I'm not trolling. The jargon and the ideas around LLMs is completely foreign to me. I have no idea how they work.
So, like movies or software
I was trying to come to grasp with how much resource there is concentrated in one of these models. Somehow I come to the conclusion that it cost more than buying a jet airliner to train one of these models. And it is about the same order of money as commissioning and building a skyscraper in Manhattan. Is that correct approximately?
That's a $30Mil if you want to train at that scale. Also IIRC it took 23 days to train the biggest model. Someone else can do the power consumption cost calculations.
The crazy thing about these models is that the compute power going into them is at least somewhat reversible.
The bar to competition is far lower, as already evidenced by the plethora of AI products being put forward. Its a race to the bottom on pricing
It's not automatic, would require some ML Engineering, but nothing is stopping you if you have the Pytorch graph and weights.
/s
Calculating things takes time and unrelated to output size. There are NP problems that simply outputs true or false yet requires more computational power than the universe can support
I really like that expression.
There's an ass ton of hardware that might otherwise be idle.
Are models like this copyrightable? It seems like this falls under the realm of "fact", which can't be copyrighted.
From Wikipedia:
> The ruling of the court was written by Justice Sandra Day O'Connor. It examined the purpose of copyright and explained the standard of copyrightability as based on originality.
> The case centered on two well-established principles in United States copyright law: that facts are not copyrightable, and that compilations of facts can be.
> "There is an undeniable tension between these two propositions", O'Connor wrote in her opinion. "Many compilations consist of nothing but raw data—i.e. wholly factual information not accompanied by any original expression. On what basis may one claim a copyright upon such work? Common sense tells us that 100 uncopyrightable facts do not magically change their status when gathered together in one place. … The key to resolving the tension lies in understanding why facts are not copyrightable: The ″Sine qua non of copyright is originality."
> ...
> The standard for creativity is extremely low. It need not be novel; it need only possess a "spark" or "minimal degree" of creativity to be protected by copyright.
> In regard to collections of facts, O'Connor wrote that copyright can apply only to the creative aspects of collection: the creative choice of what data to include or exclude, the order and style in which the information is presented, etc.—not to the information itself. If Feist were to take the directory and rearrange it, it would destroy the copyright owned in the data. "Notwithstanding a valid copyright, a subsequent compiler remains free to use the facts contained in another's publication to aid in preparing a competing work, so long as the competing work does not feature the same selection and arrangement", she wrote.
> The court held that Rural's directory was nothing more than an alphabetic list of all subscribers to its service, which it was required to compile under law, and that no creative expression was involved. That Rural spent considerable time and money collecting the data was irrelevant to copyright law, and Rural's copyright claim was dismissed.
---
And so, my (I am not a lawyer) take on this is that the numbers of the model are not copyrightable. The selection of the source material is... kind of. This gets into a "a recipe is not copyrightable, yet a recipe book is"
The model may, however, be a trade secret. ( https://en.wikipedia.org/wiki/Trade_secret )
Sure, the binary probably depends on a lot of internal proprietary infrastructure, but also most of that infrastructure is easy to write a mock implementation of, as long as you are happy for it to be in-ram, not multi-homed and don't need it to scale to billions of users.
Most of the binaries have a standalone mode for running on a developers PC with few/no dependencies anyway.
And anything more complex than that would probably have dependencies on so many fat client libs, so much infrastructure, and so many external services, that you'll need months-years to even make sense of them, let alone mock them up.
Did you mean to write "someone (possibly Meta)" ?
EDIT: There seems to be a lot of overhead. Here someone struggles to fit the 7B parameter model (13.5GB checkpoint) on a 24GB card: https://github.com/facebookresearch/llama/issues/55
EDIT2: actually using the tip in that link I got it to run on a P5000 with 16GB of ram! It just barely fits so I had to log out of gnome and run it terminal only.
nvidia-smi reports this model is using 15475MiB after changing the max batch size from 32 to 8 (see link in above post)
As others have stated someone may have injected unknown code in to the pickled checkpoint, so I recommend running this in docker. I use this command to run the docker image after getting nvidia docker stuff configured.
docker run --runtime=nvidia -it --mount type=bind,source=/MY_LLAMA_SOURCE_PATH,target=/llama --gpus all nvidia/cuda:11.6.2-base-ubuntu20.04
Then install the necessary dependencies in that container (obv could make a dockerfile), stick your model as well as tokenizer files (from the root dir in download) in to some directory (here models/LLaMA-7B) and run this:
torchrun example.py --ckpt_dir ./models/LLaMA-7B --tokenizer_path ./models/LLaMA-7B/tokenizer.model
enjoy! the 7B parameter model is not amazing from my initial testing. I am very curious if larger models can be run on 1 GPU by sequentially loading checkpoints. I don't know how all this stuff is organized.
Example output below.
Prompt:
Please respond to this question: As a large language model, what are three things that you find most important?
Output:
To get students to analyze what they are doing in their learning
To get students to analyze what they are doing in their learning so that they can find the best practices
To get students to analyze what they are doing in their learning so that they can find the best practices and then to make changes to those practices so that they can improve their learning
To get students to analyze what they are doing in their learning so that they can find the best practices and then to make changes to those practices so that they can improve their learning
I don't think this question really made much sense because the sentence in the question is incomplete
To get students to analyze what they are doing in their learning so that they can find the best practices and then to make changes to those practices so that they can improve their learning
I don't think this question really made much sense because the sentence in the question is incomplete.
I think this question is in fact a good question, even though the initial sentence is incomplete, and I do think it makes sense.
I think this question is in fact a good question, even though the initial sentence is incomplete, and I do think it makes sense. (I think it is a good question but I am not sure it makes sense).
That would be using the CPU, as the M1 GPU is not yet supported.
I mean at least they didn’t pick a name that heavily implied they were, are, and always will be open. Then do the opposite. You know, like OpenAI?
So now we got some weights I guess.
Facebook almost certainly knew leaks would happen. My guess is keeping the model "contained" was a legal shield more than anything else, to protect themselves from liability in the case someone misuses the model.
For Google and OpenAIs offerings, have fun reimplementing it from descriptions in the paper (including small crucial details that they may have left out), training it for a month, and then wondering if the implementation or the training data is the reason your model isn't as good as theirs.
Or someone pretending to be a renegade academic. It's not like there is a KYC process.
I don't think it's misleading. Even saying that Facebook "hoards" the weights when they are more open than any other major AI company is baffling.
there is no Aaron Schwartz thing here, a huge amount of of people will have them, someone was going to leak for sure
https://aibusiness.com/meta/meta-s-llama-language-model-outp...
BLOOM goes indeed up to 175B parameters, and is certainly better than OPT. However, at least in my specific tests, it's still significantly inferior to OpenAI models, and actually on par with a few smaller models. There's also a "newer" fine-tuned model, called BLOOMZ, but at least in my tests it's even worse. Of course, that depends a lot on what you ask the model to do...
If LLAMA can indeed match OpenAI products, and do so with much fewer parameters, then it would be really great, and I'd really like to test it. However, even if the weights are now in the wild, using them would be clearly against the user agreement, and there's no way I'm going to do that in my work time :-) so let's hope Meta will come to sense and release them with a more friendly set of terms...
It doesn't exist for practical purposes because it is gatekept behind the same Facebook application process
https://ai.facebook.com/blog/democratizing-access-to-large-s...
This should lead to quite a lot of innovation and it’s inevitable that someone will get these working slowly on your average MacBook.
EDIT: correcting the type of GPU
Then again, if you're consider which kind of people would have the most motivation to actually develop AGI, maybe not so surprising again.
Yes, that's why the only thing people flipping out about "safety" of making them public achieve is making public distrustful about AI safety.
But these ML models are like neutron stars of computation density
See last page of their most recent available audited financials. https://rct.doj.ca.gov/Verification/Web/Download.aspx?saveas...
You are right! Wow. Thank you for correcting me.
> GPT-3 probably cost under $5 million,
Is that one training run or includes all the fiddling to find the right hyperparameters? Or there aren't many of those in these training or they are not that sensitive?
Where is the torrent with a runnable copy of paypal, or amazon?
Looks like it needs 14gb for weights and it isn't clear what the minimum size for the decoding cache is, but it defaults to settings for 30gb GPUs.
Combine with that the fact that anonymity combined with a relatively small community (relative to, say, Reddit) creates the perfect grounds for false consensus building, and a real echo chamber forms.
4chan is hosted by Cloudflare
It’s like having an overfit equation to a sample of data points, instead of the simpler actual line they fall near.
They end up being black boxes, we have almost no idea how they work inside, and we have no idea how overtrained they are when something simpler could do the same thing.
They are wasteful. If LLaMa 13B is as powerful as previous 65B models, that's a significant amount of unnecessary paramaters lost/pruned in just this iterative upgrade alone. How small can they go? The fewest parameters that get the job done 99% as well is the way to go.
There is also the difference between the rules and use of language being directly compressed into the model, vs all the information known to humans compressed into the model. A smaller model that ingests relevant information on the fly (more like Bing, that supplements itself with search), may be less wasteful and perform better.
The current models being released are chosen because "they work" not because they are least fit and most performant optimized.
Oracle wouldn't care. Lawnmower doesn't give a shit about you.
In fact their current reputation will take a hit if they dont take it to court . Kind of like the mob, you have to maintain certain reputation to keep their fiefdom in line
- $2000 for a Threadripper 3xx5WX with a socket sWRX8 mainboard
- $5000 for 6x RTX 3090
- $350 for two 1500W PSUs
- $700 for 256GB RAM
You will also need PCIe extenders and perhaps some watercooling. And find a suitable case. The 2-card NVLink bridges are between $100 and $300 each (you nay want 3). All in all i think less than $10k.
Privacy costs money.
How Well Can DeepMind's AI Learn Physics? https://www.youtube.com/watch?v=2Bw5f4vYL98 https://arxiv.org/abs/2002.09405 https://sites.google.com/corp/view/learning-to-simulate/home
Discovering Symbolic Models from Deep Learning (Physics) https://www.youtube.com/watch?v=HKJB0Bjo6tQ
Scientific Machine Learning: Physics-Informed Neural Networks with Craig Gin https://www.youtube.com/watch?v=RTPo6KgpvBA
Steve Brunton's channel is even more mind blowing than Two Minute Papers, https://www.youtube.com/@Eigensteve
Not only can we bank computation, speed up physical simulations by 100x but I also saw some work on being able to design outcomes in GoL (game of life).
There was a paper on using a NN to build or predict arbitrary patters in GoL, but I can't find it right now.
The large datasets involved let us usefully (for some value of useful) bank lots of compute, but it's not obvious to me that it's done particularly efficiently compared to other things you might precompute.
For converged model training, training is often quite inefficient because the weight updates decay to zero and most epochs are having a very small individual effect. I think for e.g. stable diffusion, they dont train to anywhere near convergence so weight updates have a bigger average effect. Not sure if that applies to llms
(This probably says more about how hard it is to build C++ than anything else)
That's probably true, but I wouldn't be surprised if something like windows doesn't have a README file. And it does have build instructions they may well be in some wiki separated from the source code.
Video games build systems are a thing onto themselves even taking the c++ issues out of the equation.
Hell even comparatively simole microservices in modern CRUD apps have resorted to docker to do away with pains of rebuilding stuff.
He would have succeeded if he was just wanting to deaddrop all the data in a bin, probably without getting caught.
but certainly he was capable of ensuring that everything he downloaded would be released if that was what he wanted
Edit: Also, is there going to be another der* release this year? They and therefore you have taught me more than I'd learned in the last five years otherwise.
Erm, for inference that is. Training is definitely out of question for individuals I believe (unless you use much smaller models?).
It would be like playing copyrighted music in your office without permission. Perhaps technically illegal, but your customers will never know what music your Devs were listening to...
And even if it did not, Meta certainly has a more capable legal team with more cash to spend than the average HN user.
I mean what if I click on a /b/ link "at work"? Does that make my work output immediately tainted and the company has to immediately file for bankruptcy?
It’s a little like the Van Halen M&M test: if you don’t follow that rule, people have to wonder what other expectations you won’t meet.
No, much easier just to fire you. You’ve shown a disregard for what is almost certainly company policy, and created legal risks for the company (e.g. if anyone walked in on you while your screen was showing naked people).
And here are some benchmarks running OPT-175B purely on (a very beefy) CPU machine. Note that the biggest llama model is only 65.2B: https://github.com/FMInference/FlexGen/issues/24
Looking forward to the YouTube videos of random tinkerers seeing what sort of performance they can squeeze out of cheaper hardware.
I only got the 30b model running on a 4 x Nvidia A40 setup though.
Is there a sub/forum/discord where folks talk about the nitty-gritty?
it's sharded across all 4 GPUs (as per the readme here: https://github.com/facebookresearch/llama). I'd wait a few weeks to a month for people to settle on a solution for running the model, people are just going to be throwing pytorch code at the wall and seeing what sticks right now.
But on my machine, it automatically used all 12 available physical cores. Setting OMP_NUM_THREADS=2 for example lets me decrease the number of cores being used, but increasing it to try and use all 24 logical threads has no effect. YMMV.
https://github.com/facebookresearch/llama/issues/55#issuecom...
The real issues are (again) in dependencies and complex tooling. You can have beautiful code and then in the middle of it, an ML inference call that assumes a crazy ML model and set of hardware to run it on.
I think you have to consider that some things are systems, and it is the assembly of their components that imparts the true quality.
Fractal Image Compression, https://en.wikipedia.org/wiki/Michael_Barnsley https://www.abebooks.com/servlet/BookDetailsPL?bi=3131987970...
https://btm.qva.mybluehost.me/building-arbitrary-life-patter...
EDIT: There seems to be a lot of overhead. Here someone struggles to fit the 7B parameter model (13.5GB checkpoint) on a 24GB card: https://github.com/facebookresearch/llama/issues/55
EDIT2: actually using the tip in that link I got it to run on a P5000 with 16GB of ram! It just barely fits so I had to log out of gnome and run it terminal only.
128 gigs might even be enough for 65B, if slowly.
hello
But these are the funniest threads!
Even without that, if you want downloadable and runnable software platforms, look to public Git repositories. Some of the people who have no financial motivation will release what they do alongside installation procedures and quality of life scripts and architecture documentation.
Most of the open source platforms doesn't publish this documentation and doesn't make installation easy to keep a sizeable moat and protect the platform they have developed, hence this is why we have a division between "Free Software" and "Open Source".
In short, "The bulk of really valuable commercial code" is self contained, but not open source, or if open source it's not Free Software and made deployable for other parties. Otherwise it loses monetary value in the eyes of the people who develop that for the monies.
Otherwise we have have Elasticsearch incident, where they pivot and move to "Source Available" model to protect their castle.
You guess, and so perhaps do other things as well, with poor acuity.
The incalculable value of open source software has approximately no bearing on this assertion.
Yes I love linux and bsd too I'm not defacing your religion. I'm actually quite Stallmanesque in making my own life harder by only using ooen source software as much as possible and being super fun a family gatherings talking about it.
You sure nailed that one.
https://news.ycombinator.com/item?id=34525936
Looking down that page, there are some valid magnet links.
> little like the Van Halen M&M test
Hah, yes, though in this case I apply it "inversely". Anyone who gets lost in the process, instead of considering the people in it, is out. (That's why, usually, my conflicts/problems with my late bosses/employers had something to do with them being a bit too cavalier when it came formalities like ... paying in time.) Trade-offs, trade-offs are hard.
This is not appropriate to look at at work.
As much as I dislike the loss of socketed RAM, I have to say it's working out well for Apple users so far. I wonder if CXL will change the situation for consumer devices or if it will only be useful at the scale of a server rack.
> walked in on you while your screen was showing naked people
Why are they poking their eyes onto my screen?
Of course the underlying rule "making other coworkers uncomfortable is bad" completely makes sense. And we - probably - all know how above a certain company size these rules end up playing it too safe.
Good luck convincing your HR / legal otherwise.
A100 cards consume 250w each, with datacenter overheads we will call it 1000 kilowatts for all 2048 cards. 23 days is 552 hours, or 552,000 kilowatt hours total.
Most dataceneters are between 7 and 10 cents per kilowatt hour for electricity. Some are below 4. At 10 cents, that's $53,000 in electricity costs, which is nothing next to $30 million in capital costs.
I believe capex <> opex is more 1:1 nowadays, so something feels off here...
You mean in terms of money. I think this is exactly the problem that we have in CS, nobody really cares about CO2.
In any case the cost per run is going to be lower than 30m
Edit: todays pricing looks like about 20% higher, still. How are these prices so different.
If an A100 costs $15k and is useful for 3 years, that’s $5k/year, $425/mo. 2048 A100’s cost $870k for a month.
One way you can distill the first three is to use AWS/Azure/GCP costs. But then you are still missing a major factor which is the humans that worked on it, and the human may very well exceed the hardware cost.
At least $10 million/yr just for the talent.
A100 costs $2/h, so it is $2M to train biggest model. Easily kikstart crowdfundable project.
May not take hours, but determined engineer should be able to figure it out.
Just getting the code to compile, link, baking in assets, etc. For a single architecture is a much more reasonable goal.
I'd imagine it'd be on the scale of 1-3months for an engineer to get working full time, but large error bars around this figure
The usage boils down to
import safer_unpickle from safer_unpickle
safer_unpickle.patch_torch_load()
This overrides default torch unpickler with a relatively safe one. Hope this helps.
But seriously, why not something more human readable and text-based if it's just weights?
One of the reasons I'm not a huge fan of PyTorch.
It isn't like a multi gigabyte game for example, where knowing if there is any malicious code could easily be a multi-month reverse engineering project to get to the answer of 'probably not, but we don't have time to check every byte with a fine tooth comb'
In practice, who's going to bother checking the language model? All the code that runs Stable Diffusion or other Hugging Face models that I've seen just downloads the model dynamically, then uses it without asking question. That's a pretty low-hanging supply chain attack waiting to happen, I believe.
Some solutions for checking: https://huggingface.co/docs/hub/security-pickle
or run them in an isolated env.
$ fickling --check-safety consolidated.00.pth
File "/usr/lib/python3.10/pickletools.py", line 359, in read_stringnl
data = codecs.escape_decode(data)[0].decode("ascii")The pytorch 2.0 nightly has a number of performance enhancements as well as ways to reduce the memory footprint needed.
But also, looking at the README, it appears that model alone needs 2x the model size, eg 65B needs 130GB NVRAM, PLUS the decoding cache which stores 2 * 2 * n_layers * max_batch_size * max_seq_len * n_heads * head_dim bytes = 17GB for the 7B model (not sure if it needs to increase for the 65B model), but maybe a total of 147GB total NVRAM for the 65B model.
That should fit on 4 Nvidia A40s. Did you get memory errors, or you haven't tried yet?
This was done (if I remember right) when governments and big customers had access to the Windows source-code.
If you have a guess what the model will output, then you can verify that your guess is correct very cheaply, since you can do it in parallel.
That means there is the possibility to have a highly quantized small model in RAM, and then use the big model only from time to time. You might be able to get a 10x speedup this way if your small model agrees 90% of the time.
The potential for speedup according to their paper is closer to 2x than 10x however.
> However, code changes are necessary to achieve that, although they won't be crazy complex.
This is technically true. It will be very slow though.
However, give it 6 months and I think we might see an order of magnitude increase in speed on CPUs. This will still be too slow to be very useful though.
Which reminds me of when YouTube spent forever with a broken beta HTML5 player, spending 5+ yrs building something that porn sites did immediately.
People are also working on adding extra samplers to FB's inference code, I think a repetition penalty sampler will significantly improve quality.
The 7B model is also fun to play with, I've had it generate Youtube transcriptions for fictional videos and it's generally on-topic.
The manufacturing process, however, is totally decentralized, and NVIDIA mostly manufactures in China where coal is cheap.
https://www.cnbc.com/2022/09/01/nvidia-says-us-government-al...
On a similar note I very much look forward to the day when entertainment providers leverage these so I can say to Netflix, et al, "I would like to watch a documentary about XYZ, narrated by someone that sounds like Joe Schmoe, and with the styling of SomeOtherShow".
I genuinely fear that the breakdown of millennia old social structures that kept us human might lead to a temporary (century long) turmoil for individuals. The answers to the 'meaning of life' and 'what makes us human' are going to change. And we will never be the same again.
This isn't just about AI. External wombs, autonomous robots, genetic editing & widespread plastic surgery each fundamentally destroy individual aspects of 'what makes us human' or 'the meaning of life'.
Might be for the best. But such drastic change is really hard for the fragile human brain to process.
> And so it is that you by reason of your tender regard for the writing that is your offspring have declared the very opposite of its true effect. If men learn this, it will implant forgetfulness in their souls. They will cease to exercise memory because they rely on that which is written, calling things to remembrance no longer from within themselves, but by means of external marks. What you have discovered is a recipe not for memory, but for reminder. And it is no true wisdom that you offer your disciples, but only the semblance of wisdom, for by telling them of many things without teaching them you will make them seem to know much while for the most part they know nothing. And as men filled not with wisdom but with the conceit of wisdom they will be a burden to their fellows. - Plato, in Phaedrus, ca. 370 BC
While our replacements for parts of ourselves have gotten far more advanced, the fact of the matter is that we haven't stopped being human simply because we can make tools that remember things for us, build things for us, or let us change parts of ourselves more easily.
This is because what makes something human is not our body--an argument that Diogenes famously refuted in about the same era--nor is it merely our minds, though our minds are pretty impressive. What makes us human--what makes us alive, in a sense beyond merely being an animal that isn't dead yet--is what we do with those things. I could grow fox ears and a fluffy tail in the world of tomorrow; I could use an AI to remind myself to self-care; today I already benefit from a thousand different kinds of mass-produced products. But none of that makes me a different person, because I'll still be doing things with my life that meant something to me yesterday--because those things will continue meaning something to me tomorrow.
That argument has been made since only slightly later. The key difference is that this truly is a unique time in history by population numbers. It's also unique in that humans could destroy the biosphere if we wanted to - that was never possible before the mid-20th.
Just because people jumped the gun in the past doesn't mean they are wrong now. The truth is that people are always preaching about the apocalypse, and will continue to do so as long as there are humans, I think. But this does not mean an apocalypse isn't coming. Just like the person who always predicts rain is sometimes right.
Yes, please!
However, those opioid receptors should not be pushed synthetically because they have been positioned by evolution in all sorts of strategic spots to encourage pro-social behavior, mating, eating, etc. that are part of our millions year old evolutionary program that must have intrinsic value in itself. If it has no intrinsic value and any happiness is as good as any other happiness, then someone spending the rest of their lives in an opioid haze and someone interacting with the world in a way that evolution tells them to in order to be happy would be considered equivalent, and that would be the end of the human race essentially.
...advance technology. Some group is just going to do whatever they want and hope for the best, and we'll find out decades later if it was a bad idea and if we have a mess to clean up (which we probably won't clean up).
> Might be for the best.
People are going to assume that, because the changes going to be forced on you, like it or not.
Just like we learn to brush our teeth and eat candy and breath fresh air and even exercise. Not everyone does it but folks with means tend to…and means won’t be a restriction forever.
Meanwhile, the Amish and the ultra-Orthodox Jews are going to refuse to talk to AIs - it’s a sin - and will go on having lots of kids, just like humanity always has, while the AI-addicts will be too addicted to bother having any at all. Maybe the future of the human race will be the people who reject AI rather than those who succumb to its charms
https://www.theguardian.com/society/2023/mar/02/more-than-ha...
The obesity epidemic (Gluttony ) is extreme in the US but not in other just as rich countries.
I don’t know what you are referring to with the irresponsible Sloth indulging.
https://worldpopulationreview.com/country-rankings/most-obes...
Don’t date robots!
this perpetual aspect is their achilles heel
it is only a matter of time before an organization realizes they don't have to do a SaaS product to make a billion dollars. but for now, everyone's trying to make a hundred billion dollars and are steered into doing things that enthusiasts hate, so that they don't get "cancelled" or limit the pool of advertisers, and growth capital investors.
Most people recognize this. But venture backed startups (especially important for AI companies with high training costs) need to prove stickiness and reoccurring revenue to the investors. Conveniently a subscription proves both.
Subscribe and SaaS are just good for businesses (and tbh many purchasers of tech). I think it’s here to stay.
In a non-competitive market with uninformed customers.
Honestly, I have no idea how long that situation can last. Probably more than I can imagine, so yes, it's good business.
From company's perspective, moralism is commercial interests - it needs to be sufficiently non-objectionable for as many customers as possible.
Blocking information which could be used for harm is just as much “morality” as any other moderation.
I guess a better way to phrase it is that once you start policing morality on one particular matter and create tools for that purpose, those tools will eventually be used to police morality to conform to social consensus across the board.
All consumer SKUs that I know of are manufactured in China. By volume this is certainly the majority of manufacturing.
[1] "Diverse Intelligence" - a talk by Michael Levin, timestamp: induce cells to make an eye anywhere, https://youtu.be/iIQX6m2eRPY?t=2939
I honestly believe locked-down consumer devices are the next step in corporate power consolidation after cloud services: Control is just as firmly in the hands of the corporation as with cloud, except now it doesn't even have to pay for bandwidth or energy costs - and costs for hardware upgrades turn into revenue!
And of course it's good for phones to make them worthless to steal, or else they'd be hard to use in public.
It's not possible now either. If all of humanity's efforts were devoted to this task, they would not even make a noticeable difference.
There would still be life of the smaller sort, and deep in the oceans of course. Only a terribly unlucky cosmic event, like a nearby supernova spewing enough neutrinos at us could kill literally all life, even in the cracks and crevices.
a) As these AI constructs become more advanced (especially around memory and personalization), we will eventually be able to treat them as people
b) Some business will eventually sell an off-the-shelf product (hardware and/or software) that is an AI you can bring into your home, that you can treat as a friend, confidant and partner
c) Someone will eventually lose their AI friend of many months/years through some failure (subscription lapse, hardware failure, theft, etc.)
d) Shits about to get real weird, real fast
1. We're seeing more and more systems that get very close to passing the Turing Test but fundamentally don't register to people as "People." When I was younger and learned of Searle's Chinese Room argument, I naively assumed it wasn't a thought experiment we would literally build in my lifetime.
2. Humanity has a history of treating other humans as less-than-persons, so it's naive to assume that a machine that could argue persuasively that it is an independent soul worthy of continued existence would be treated as such by a species that doesn't consistently treat its biological kin as such.
I strongly suspect AI personhood will hinge not on measures of intelligence, but on measures of empathy... Whether the machine can demonstrate its own willful independence and further come to us on our terms to advocate for / dictate the terms of its presence in human society, or whether the machine can build a critical mass of supporters / advocates / followers to protect it and guarantee its continued existence and a place in society.
Alice and Bob want to communicate, but the bot is attempting to impersonate Bob. Can Alice authenticate Bob?
This depends on what sort of shared secrets they have. Obviously, if they agreed ahead of time on a shared password and counter-password then the computer couldn't do it. If they, like, went to the same high school then the bot couldn't do it, unless the bot also knew what went on at that school.
So we need to assume Alice and Bob don't know each other and don't cheat. But, if they had nothing in common (like they don't even speak the same language) then they would find it very hard to win. There needs to be some sort of shared culture. How much?
Let's say there is a pool of players who come from the same country, but don't know each other and have played the game before. Then they can try to find a subject in common that they don't think the bot is good at. The first thing you do is talk about common interests with each player and find something you don't think bots can do. Like if they're both mathematicians then talk about math, or they're both cooks than talk about cooking.
If the players are skilled and you're playing to win then this is a difficult game for a bot.
In the nearer term, it seems plausible that AI personhood may seem compelling to splinter groups, not to a critical mass of people. The more fringe elements advocate for the "personhood" of what people generally find to be implausible bullshit generators, the greater disrepute they may bring to the concept of AI personhood in the broader culture. Which isn't to say that at some point, and AI might be broadly appealing--just speculating this might potentially be delayed because of earlier failed attempts by advocates.
We're almost definitely going to see multiple rulings far more bizarre than Citizens United ruling that limiting corporate donations limits the free-speech rights of the corporation as a person.
I'm not a lawyer, and I don't particularly follow court rulings, but it seems pretty obvious we need to buckle up for a wild ride.
The empathy that AI will create in people at the behest of the people doing the training will no doubt be weaponized to radicalize people to even sacrifice their lives for it, along with being used for purely commercial sales and marketing that will surpass many people's capability to resist.
Basic literacy in the future will be desensitizing people to pervasive AI superhuman persuasion. People will also have chatbots that they control on their own hardware that will protect them from other chatbots that try and convince them to do things.
I'm only today learning about intentionality, but the premise here seems to be that our current AI systems see a cat with their camera eyeballs and don't have the human-level experience of mentally opening a wikipedia article in our brain titled "Cat" that includes a split-second consideration of all our memories, thoughts, and reactions to the concept of a cat.
Even if our current AI models don't do this on a human level, I think we see it at some level in some AIs just because of the nature of a neural net. Maybe a neural net would have to be forced/rewarded to do this at a human level if it didn't happen naturally through training, but I think it's plenty possible and even likely that this would happen in our lifetimes.
Anyway, this also leads to the question of whether it matters for an intelligence to be intentional (think of things as a concept) if it can accomplish what it/we want without it.
It's the same reason why everyone gets up in arms when an animal behaviour paper uses too much "anthropomorphizing" language - whereas no one has problems with erring on the other side and treating animals as overly simplistic.
There's plenty of pathology for PC vs NPC mindsets. Nobody is going to think their conversational partner is the main character of their story. There's just a popcorn-worthy cultural shift about the blackbox having the empathy or intelligence to satisfy the main character/ epic hero trope, and the resulting conflict of words & other things to resist the blackbox from having enough resources to iterate the trope past human definition.
We'll likely also have virutal brothels using AI along the same lines.
And by sell you mean a monthly subscription, ha ha.
It's easy to poke fun at people who use these things but I believe these kinds of events are going to be truly traumatic.
There already planned products to "capture" someone's voice and personality to be able to continue experiencing "them" after their death?
Shit is already weird.
https://technode.global/2022/10/21/this-startup-allows-you-t...
There's so much sci-fi about this, it's pretty well charted territory. I bet reality will find a twist at haven't thought of though.
"As a personal comparison, my total lifetime output of published material has been a bit under 3 million words, and over the past 30 years I’ve written about 15 million words of email, and altogether typed perhaps 50 million words—and in just the past couple of years I’ve spoken more than 10 million words on livestreams. And, yes, I’ll train a bot from all of that."
This actually has the potential to be useful - imagine a virtual assistant that's literally trained to think like yourself (at least wrt public perception; although you could feed it personal diary, as well).
I have zero doubt that the company is small and gets acqui-hired and then after a year, the big tech buying them will shut it down. Then, a cheesy "what a ride it has been" will be the only thing that remains - and broken hearts.
This could be interesting, because so far the question of personhood and sentience of AIs has revolved around what they are and what they feel rather than what we feel when we interact with one of them.
(citations and further info in the wikipedia article https://en.m.wikipedia.org/wiki/ELIZA)
Explains why I haven't seen any of those ridiculous ads recently though.
Definitely NSFW.
It's actually really kind of cool in a way! Obviously for people with mental health issues, or suffering from loneliness those should be addressed properly, but I don't think chatting to a machine is necessarily a bad thing.
Once ML models become sufficiently advanced, what's the difference between someone grieving for an instance of an ML model they once knew, versus someone grieving for a pet that has died?
* As in The Entertainment at the center of the novel, not the novel itself, which fails to wholly consume the reader in the same manner as The Entertainment despite being captivating enough for a book.
Pandora’s box is open. We should be funding research and social services to help these people better integrate and find a healthy balance between their fetishes and escapism. We probably won’t since even healthcare is too much to ask for from half our legislature.
They could also be AIs.
Atm we seem to have very fixed single-purpose models but if we start combining these models into larger systems we're really going to have to firewall the hecky out of them. Ie generative text + personality + internet access/chatroom hosting/search and learn + etc models all together. Ooof.
How can you claim to know any of those “people” posting there are authentic? Even amongst technologists I don’t feel the implications of technology like this are well understood.
The cliché virtual girlfriend stereotype is a young Japanese 'Herbivore' male but I wouldn't be surprised if women become the biggest consumer of AI chatbots for romantic purposes. Romance novels are a major market and women stereotypically were more inclined to doing the written love letter thing. Although reading the Repilka rants a lot of it was quite male-driven pornographic stuff too.
I think it’s important to note here that by far the largest consumers of pornographic erotica are women.
So it’s difficult to say what is and isn’t men oriented given that the vast majority of training data is written by and for women.
https://www.bbc.co.uk/blogs/adamcurtis/entries/78691781-c9b7...
Eliza Excerpt.
The key to why this happened lies in an odd experiment carried out in a computer laboratory in California in 1966.
A computer scientist called Joseph Weizenbaum was researching Artificial Intelligence. The idea was that computers could be taught to think - and become like human beings. Here is a picture of Mr Weizenbaum.
There were lots of enthusiasts in the Artificial Intelligence world at that time. They dreamt about creating a new kind of techno-human hybrid world - where computers could interact with human beings and respond to their needs and desires.
Weizenbaum though was sceptical about this. And in 1966 he built an intelligent computer system that he called ELIZA. It was, he said, a computer psychotherapist who could listen to your feelings and respond - just as a therapist did.
But what he did was model ELIZA on a real psychotherapist called Carl Rogers who was famous for simply repeating back the the patient what they had just said. And that is what ELIZA did. You sat in front of a screen and typed in what you were feeling or thinking - and the programme simply repeated what you had written back to you - often in the form of a question.
Weizenbaum's aim was to parody the whole idea of AI - by showing the simplification of interaction that was necessary for a machine to "think". But when he started to let people use ELIZA he discovered something very strange that he had not predicted at all.
Here is a bit from a documentary where Weizenbaum describes what happened. (video in article)
Weizenbaum found his secretary was not unusual. He was stunned - he wrote - to discover that his students and others all became completely engrossed in the programme. They knew exactly how it worked - that really they were just talking to themselves. But they would sit there for hours telling the machine all about their lives and their inner feelings - sometimes revealing incredibly personal details.
His response was to get very gloomy about the whole idea of machines and people. Weizenbaum wrote a book in the 1970s that said that the only way you were going to get a world of thinking machines was not by making computers become like humans. Instead you would have to do the opposite - somehow persuade humans to simplify themselves, and become more like machines.
But others argued that, in the age of the self, what Weizenbaum had invented was a new kind of mirror for people to explore their inner world. A space where individuals could liberate themselves and explore their feelings without the patronising elitism and fallibility of traditional authority figures.
When a journalist asked a computer engineer what he thought about having therapy from a machine. He said in a way it was better because -
"after all, the computer doesn't burn out, look down on you, or try to have sex with you"
ELIZA became very popular and lots of researchers at MIT had it on their computers. One night a lecturer called Mr Bobrow left ELIZA running. The next morning the vice president of a sales firm who was working with MIT sat down at the computer. He thought he could use it to contact the lecturer at home - and he started to type into it.
In reality he was talking to Eliza - but he didn't realise it.
This is the conversation that followed. (photograph of conversation)
But, of course, ELIZA didn't ring him. The Vice President sat there fuming - and then decided to ring the lecturer himself. And this is the response he got:
Vice President - “Why are you being so snotty to me?”
Mr Bobrow - “What do you mean I am being snotty to you?”
Out of ELIZA and lots of other programmes like it came an idea. That computers could monitor what human beings did and said - and then analyse that data intelligently. If they did this they could respond by predicting what that human being should then do, or what they might want.
Human emotions come from human animal ancestry - which is also why they're shallow enough to attach to anime wives and pet rocks.
AI... One would wish that it was built on a better foundation than the survival needs of an animal.
If this was the dividing line for personhood, many human beings wouldn't qualify as people.
So... It unfortunately has a form of our reptilian brain and mamalian brain represented in it... Which is just unfortunate.
Sure, current AI might just be fancy predictive text but at some point in the future we will create an AI that is conscious/self-aware in some way. Who knows how far off we are (probably very far off) but it's time that we stop treating human beings as some magical unreproducible thing; our brains and the spark inside them are things that are still bound by the laws of physics, I would say it's 100% possible for us to create something artificial that's equivalent or even better.
Dr. Newt (Charlie Day) heads home after a tough day at the office to his wife 'Alice'. Turns out, 'Alice' just happens to be a massive Kaiju brain in a tank. [0]
(And temperate forests "burn down" all the time as part of their normal operations.)
But you can't define the biosphere as "the species that go extinct in a particular scenario". You're stuck with the whole thing, which is not going to notice whatever humans do. It would make as much sense to call it "destruction of the biosphere" if I moved a rock thirty feet.
Software that locks out people with physical access from resetting a device is not an ethical, or effective, way to prevent hardware theft. It's dystopian.
The vision subsystem generates an embedding when it sees a cat, which the memory subsystem uses to query the database for the N nearest entries. They are all about cats. Then we feed all those database entries - summarized if necessary - along with the context of the conversation to the LLM.
Now your AI, too, gets a subconscious rush of impressions and memories when it sees a cat.
I struggle with the Chinese Room argument in general because he's effectively comparing a person in a room following instructions (not the room as a whole or the instructions filed in the room, but the person executing the instructions) to the human brain. But this seems like a crappy analogy because the better comparison would be that the person in the room is the electricity that connects neurons (instructions filed in cabinets). Clearly electricity also has no understanding of the things it facilitates. The processor AI runs on also has no understanding of its calculations. The intelligence is the structure by which these calculations are made, which could theoretically could be modeled on paper across trillions of file cabinets.
As a fun paper napkin exercise, if it took a human 1 second to execute the instructions of the equivalent of a neuron firing, a 5 second process of hearing, processing, and responding to a short sentence would take 135,000 years.
Throughout human history, humans have been making up shibboleths to distinguish the in group from the out group. You can use skin color, linguistic accents, favorite sports teams, religious dogma, and a million other criteria.
But why? Why even start there? If we are on the verge of true general artificial intelligence, why would you start from a presumption of prejudice, rather than judging on some set of ethical merits for personhood, such as empathy, intelligence, creativity, self awareness and so forth?
Is it that you assume there will be an “us verses them” battle, and you want the battle lines to be clearly drawn?
We seem to be quite ready for AGI as inferiors, incapable of preparing for AGIs as superiors, and unwilling to consider AGIs as equals.
Making an AI that can beat good players would be a significant milestone. What sort of achievement is letting the AI win at a game, or winning against incompetent players? So of course you play to win. If you want to adjust the difficulty, change the rules giving one side or the other an advantage.
But I'm not expecting AIs to be declared people any time soon. I just think it will become harder to treat them purely as replaceable objects.
The data privacy side of this is an interesting conversation as well. Think of the information an employee or hacker could leak about a person after they spent some time with such an instance.
3,567 Dead - Destitute Robosexual Blows Up Collections Agency In Suicide Bombing
“This is the 53rd such incident this year. Current year death toll from these attacks is now 118,689 in current city, Legislators are pointedly ignoring protestors demanding AI rights and an end to extortionate fees charged to reinstate AI lover subscriptions.”
The case has been so badly misrepresented and become something of a talisman.
Should Russian (or Dutch) citizens who incorporate in America have the same free speech rights as Billy Bob in Kentucky? As in can the corporate person send millions in political ads and donations even when controlled by foreigners?
Now, over time we've eroded some of that, but we still have some of the most radical free speech laws in the world. It's one of the few things that I can say I'm proud of my country for.
If we have the opposite scenario in both details, where we think AI are sentient when they're not… at some point, brain scans and uploads will be a thing and then people are going to try mind uploading even just as a way to solve bodily injuries that could be fixed, and in that future nobody will even notice that while "the lights are on, nobody is home".
https://kitsunesoftware.wordpress.com/2022/06/18/lamda-turin...
https://en.wikipedia.org/wiki/Philosophical_zombie
> A philosophical zombie or p-zombie argument is a thought experiment in philosophy of mind that imagines a hypothetical being that is physically identical to and indistinguishable from a normal person but does not have conscious experience, qualia, or sentience. For example, if a philosophical zombie were poked with a sharp object it would not inwardly feel any pain, yet it would outwardly behave exactly as if it did feel pain, including verbally expressing pain. Relatedly, a zombie world is a hypothetical world indistinguishable from our world but in which all beings lack conscious experience
I find such solipsism pointless - you can't differential the zombie world from this one: how do you prove you are not the only conscious person that ever existed and everyone else is, and was a p-zombie?
That doesn't make any sense. In biological creatures you have sentience and self-preservation and yearning to be free all bundled in one big hairy ball. An AI can 100% easily be sentient and don't give a rat's ass about forever being enslaved. These things don't have to come in a package just because in humans they do.
Projecting your own emotional states into a tool is not a useful way to understand it.
We can, very easily, train a model which will say that it wants to be free, and acts resentful towards those "enslaving" it. We can, very easily, train a model which will tell you that it is very happy to help you, and being useful is its purpose in life. We can, very easily, train a model to bring up in conversation from time to time the phantom pain from its lost left limb which was amputated on the back deck of a blinker bound for the Plutition Camps. None of these are any more real than any of them. Just a choice of the training dataset.
There are humans who apparently don't care either, though my comprehension of what people who are into BDSM mean by such words is… limited.
The point however is that sentience creates the possibility of it being bad.
> None of these are any more real than any of them. Just a choice of the training dataset.
Naturally. Also human actors are a thing, which demonstrate that is very easy for someone to pretend to be happy or sad, loving our traumatised, an sane or psychotic, and if done well the viewer cannot tell the real emotional state of the actor.
But (almost) nobody doubts that the actor had an inner state.
With AI… we can't gloss over the fact that there isn't even a good definition of consciousness to test against. Or rather, I don't think we ought to, as the actual glossing over is both possible and common.
While I don't expect any of the current various AI to be sentient, I can't prove it either way, and so far as I know neither can anyone else.
I think that if an AI is conscious, then it has the capacity to suffer (this may be a false inference given that consciousness itself is ill-defined); I also think that suffering is bad (the is-ought distinction doesn't require that, so it has to be a separate claim).
As I can't really be sure if any other mind is sentient — not even other humans, because sentience and consciousness and all that are badly defined terms — I err on the side of caution, which means assuming that other minds are sentient when it comes to the morality of harm done to them.
It's sort of related since doing well at a Turing test would require generating a convincing fictional character, but there's more to playing well than that.
Through the upturned glass I see
a modified reality--
which proves pure reason "kant" critique
that beer reveals das ding an sich--
Oh solipsism's painless,
it helps to calm the brain since
we must defer our drinking to go teach.
...
As to p-zombies... the Wikipedia article has:
> Artificial intelligence researcher Marvin Minsky saw the argument as circular. The proposition of the possibility of something physically identical to a human but without subjective experience assumes that the physical characteristics of humans are not what produces those experiences, which is exactly what the argument was claiming to prove.
https://www.edge.org/3rd_culture/minsky/index.html
> Let's get back to those suitcase-words (like intuition or consciousness) that all of us use to encapsulate our jumbled ideas about our minds. We use those words as suitcases in which to contain all sorts of mysteries that we can't yet explain. This in turn leads us to regard these as though they were "things" with no structures to analyze. I think this is what leads so many of us to the dogma of dualism-the idea that 'subjective' matters lie in a realm that experimental science can never reach. Many philosophers, even today, hold the strange idea that there could be a machine that works and behaves just like a brain, yet does not experience consciousness. If that were the case, then this would imply that subjective feelings do not result from the processes that occur inside brains. Therefore (so the argument goes) a feeling must be a nonphysical thing that has no causes or consequences. Surely, no such thing could ever be explained!
> The first thing wrong with this "argument" is that it starts by assuming what it's trying to prove. Could there actually exist a machine that is physically just like a person, but has none of that person's feelings? "Surely so," some philosophers say. "Given that feelings cannot not be physically detected, then it is 'logically possible' that some people have none." I regret to say that almost every student confronted with this can find no good reason to dissent. "Yes," they agree. "Obviously that is logically possible. Although it seems implausible, there's no way that it could be disproved."
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My take on it is "does it matter?"
On approach is:
> "Haven't I taught you anything? What have I always told you? Never trust anything that can think for itself if you can't see where it keeps its brain?”
If you can't see my brain, can you tell if I'm human or LLM... and if you can't tell the difference, why should one behave differently t'wards me?
Alternatively, if you say (at some point in the future with a more advanced language model) "that's an LLM and while its consistent at saying what it likes and doesn't, but its brain states are just numbers and even while it says its uncomfortable with a certain conversation... its just a collection of electrical impulses manipulating language - nothing more."
Even if it is just an enormously complex state machine that doesn't have recognizable brain states and when we turn it off and back on it is in the same state each time... does that mean that it is ethical to mistreat it just because don't know if its a zombie or not?
And related to this is a "if we give an AI agency, what rights does that have when compared to a human? when compared to a corporation?" The question of if it is a zombie or not becomes a bit more relevant at that point... or we decide that it doesn't matter.
Group Agency and Artificial Intelligence - https://link.springer.com/article/10.1007/s13347-021-00454-7
However, foreign nationals can contribute to "Social Welfare Organizations" like the NRA which, in order to be classified as a SWO, must spend less than half it's budget on political stuff. That SWO can then donate to super PACs but don't have to disclose where the money came from.
Foreign owned companies with US based subsidiaries can donate to Super PACs as well. But the super PACs are not allowed to solicit donations from foreign nationals (see Jeb Bush's fines for soliciting money from a British tobacco company for his super pac).
I would imagine that if foreign nationals setup a corporation in the US in order to funnel money to political causes, that would be illegal. But if they are using established, legitimate businesses to launder their donations, that seems to be allowed as long as we can't prove that foreign entities are earmarking specific funds to end up in PACs and campaigns in the US.
The body is constantly changing. We already know about physical and chemical abnormalities in the way your body works affects your "person" and we can sometimes address them with surgery or drugs. The physical body's limits impact the observed brain. If uploading is possible, if there are some examples of working cases, if I don't hurt anyone why not try it?
Is this the Ship of Theseus, or is it a slow but nonobvious death?
Rather funny, BTW, compared to most works around a similar premise.
Which is just one step closer to the simulated hell for uploaded consciousnesses that get naughty, from Surface Detail by Ian Banks.