chrash0

chrash0 , 1 day ago

tbh this research has been ongoing for a while. this guy has been working on this problem for years in his homelab. it’s also known that this could be a step toward better efficiency.

this definitely doesn’t spell the end of digital electronics. at the end of the day, we’re still going to want light switches, and it’s not practical to have a butter spreading robot that can experience an existential crisis. neural networks, both organic and artificial, perform more or less the same function: given some input, predict an output and attempt to learn from that outcome. the neat part is when you pile on a trillion of them, you get a being that can adapt to scenarios it’s not familiar with efficiently.

you’ll notice they’re not advertising any experimental results with regard to prediction benchmarks. that’s because 1) this actually isn’t large scale enough to compete with state of the art ANNs, 2) the relatively low resolution (16 bit) means inputs and outputs will be simple, and 3) this is more of a SaaS product than an introduction to organic computing as a concept.

it looks like a neat API if you want to start messing with these concepts without having to build a lab.

chrash0 , 2 days ago

this data is not the world

i think most ML researchers are aware that the data isn’t perfect, but, crucially, it exists in a digestible form.

chrash0 , 9 days ago

there are language models that are quite feasible to run locally for easier tasks like this. “local” rules out both ChatGPT and Co-pilot since those models are enormous. AI generally means machine learned neural networks these days, even if a pile of if-else used to pass in the past.

not sure how they’re going to handle low-resource machines, but as far as AI integrations go this one is rather tame

chrash0 , 9 days ago

i mean, i’ve worked in neural networks for embedded systems, and it’s definitely possible. i share you skepticism about overhead, but i’ll eat my shoes if it isn’t opt in

chrash0 , 12 days ago

if it’s easier to pay, people spend more

chrash0 , 17 days ago

IBM then. or, i don’t know, the British Royal Family?

the reality of talking about extremist economics is no one knows how it would work out in the long term. but regardless, if it happened tomorrow we already have a Microsoft to deal with.

“taxation is theft”
“wage labour is exploitation”

sometimes things are subtle and complicated and can’t be practically boiled down to absolutes.

chrash0 , 24 days ago

gotem!

seriously tho, you don’t think OpenAI is tracking this? architecural improvements and training strategies are developing all the time

chrash0 , 24 days ago

“we don’t know how” != “it’s not possible”

i think OpenAI more than anyone knows the challenges with scaling data and training. anyone working on AI knows the line: “a baby can learn to recognize elephants from a single instance”. reducing training data and time is fundamental to advancement. don’t get me wrong, it’s great to put numbers to these things. i just don’t think this paper is super groundbreaking or profound. a bit clickbaity and sensational for Computerphile

chrash0 , 1 month ago

what else would it be? it’s a pretty common embedded target. dev kits from Qualcomm come with Android and use the Android bootloader and debug protocols at the very least.

nobody is out here running a plain Linux kernel and maintaining a UI stack while AOSP exists. would be a foolish waste of time for companies like Rabbit to use anything else imo.

to say it’s “just an Android device” is both true and a mischaracterization. it’s likely got a lot in common with a smartphone, but they’ve made modifications and aren’t supporting app stores or sideloading. doesn’t mean you can’t do it, just don’t be surprised when it doesn’t work 1-1

chrash0 , 1 month ago

i didn’t think people would really be surprised. but maybe i’m jaded by my experience in the industry.

if we’re arguing whether or not it’s objectively stupid, i think that’s up to the market to decide.

kinda seems like a toy to me anyway, and it’s kind of priced that way

chrash0 , 1 month ago

it’s not a password; it’s closer to a username.

but realistically it’s not in my personal threat model to be ready to get tied down and forced to unlock my phone. everyone with windows on their house should know that security is mostly about how far an adversary is willing to go to try to steal from you.

personally, i like the natural daylight, and i’m not paranoid enough to brick up my windows just because it’s a potential ingress.

chrash0 , 1 month ago

it’s an analogy that applies to me. tldr worrying about having my identity stolen via physical access to my phone isn’t part of my threat model. i live in a safe city, and i don’t have anything the police could find to incriminate me. everyone is going to have a different threat model. some people need to brick up their windows

chrash0 , 1 month ago

like i said, it’s more of a username than a password

chrash0 , 1 month ago

seems like chip designers are being a lot more conservative from a design perspective. NPUs are generally a shitton of 8 bit registers with optimized matrix multiplication. the “AI” that’s important isn’t the stuff in the news or the startups; it’s the things that we’re already taking for granted. speech to text, text to speech, semantic analysis, image processing, semantic search, etc, etc. sure there’s a drive to put larger language models or image generation models on embedded devices, but a lot of these applications are battle tested and would be missed or hampered if that hardware wasn’t there. “AI” is a buzz word and a goalpost that moves at 90 mph. machine learning and the hardware and software ecosystem that’s developed over the past 15 or so years more or less quietly in the background (at least compared to ChatGPT) are revolutionary tech that will be with us for a while.

blockchain currency never made sense to me from a UX or ROI perspective. they were designed to be more power hungry as adoption took off, and power and compute optimizations were always conjecture. the way wallets are handled and how privacy was barely a concern was never going to fly with the masses. pile on that finance is just a trash profession that requires goggles that turn every person and thing into an evaluated commodity, and you have a recipe for a grift economy.

a lot of startups will fail, but “AI” isn’t going anywhere. it’s been around as long as computers have. i think we’re going to see a similarly (to chip designers) cautious approach from companies like Google and Apple, as more semantic search, image editing, and conversation bot advancements start to make their way to the edge.

chrash0 , 1 month ago

they likely aren’t creating the model themselves. the faces are probably all the same AI girl you see everywhere. you gotta be careful with open weight models because the open source image gen community has a… proclivity for porn. there’s not a “function” per se for porn. the may be doing some preprompting or maybe “swim with the sharks” is just too vague of a prompt and the model was just tuned on this kind of stuff. you can add an evaluation network to the end to basically ask “is this porn/violent/disturbing”, but that needs to be tuned as well. most likely it’s even dumber than that where the contractor just subcontracted the whole AI piece and packages it for this use case

chrash0 , 2 months ago

i think it’s a matter of perspective. if i’m deploying some containers or servers on a system that has well defined dependencies then i think Debian wins in a stability argument.

for me, i’m installing a bunch of experimental or bleeding edge stuff that is hard to manage in even a non LTS Debian system. i don’t need my CUDA drivers to be battle tested, and i don’t want to add a bunch of sketchy links to APT because i want to install a nightly version of neovim with my package manager. Arch makes that stuff simple, reliable, and stable, at least in comparison.