AI is everywhere and everyone is talking
about it but as it turns out the vast
majority of what they're saying is misleading at best and at worst an
outright deception while the feature on your Smartwatch or your new co-pilot PC
is called AI it's not the AI that you're
probably thinking of so we're going to take a reality Hammer to this hype
machine and break down what AI can do
what it can't do and why the tech industry is so eager to slap the AI
label on absolutely everything and guys
this Rabbit Hole goes way deeper than you think okay predictably it ends at
money but the path to get there it turns out is really confusing on purpose which
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the
description the classic definition of AI is probably best Illustrated with
fictional examples it's what you see in sci-fi Creations like Commander Data
Hell 9000 and GLaDOS these are are
computers or machines that demonstrate a capacity for reason however naive
twisted or alien it might seem to us meatbags now you'd be forgiven for
thinking that that's still the definition of AI a lot of people seem to
think that it is but in reality the meaning of words is ever shifting and we
would now refer to these characters as having a gii or artificial general
intelligence what you're referring to as AI then is in fact narrow AI or as I've
taken to calling it AI Ani is not a
general intelligence unto itself but rather another component of a fully
functioning system made useful by specialized algorithms and data
processing utilities forming a complete artificial intelligence system didn't
think I could make that point in the style of Richard stallman's famous
interjection well I could haha but I
also didn't have to that previous paragraph was actually written by gp4
Omni and this is exactly the sort of thing that modern AI does very well and
that's because most of the time when we hear the term AI we're actually
referring to machine learning a subset
of AI involving algorithms that can analyze patterns in data they get
trained on things like text multimedia or even just raw number outputs and
using this training data they identify patterns through statistical probability
they can be further trained through reinforcement learning then by rewarding
correct outputs and punishing incorrect outputs kind of like training a hamster
the results allow these algorithms to summarize predict or even generate
something seemingly new and in many cases they are so impressive that a good
machine learning system can be indistinguishable from classic AI or a
gii well then minus if it looks like an AI and it quacks like in AI what's the
difference well artificial narrow intelligence is limited to specialized
tasks gp4 Omni specifically is a large
language model which means that it is trained to understand and generate
natural language like the words I'm speaking now it's basically an
autocomplete on steroids what sets it apart from your phone's keyboard though
is that it can also process information based on patterns that are learned
during training including definitions mathem iCal formula and so on and so
forth that makes it capable of generating unique output that wasn't
part of its training data GPT has traditionally been incapable of image
video or audio generation there are other types of generative models like
Sora sunno or dolly that feature their own specific talents but most of them
are incapable of operating outside of their specific Niche and all of them are
limited by their training data in a similar Manner and because they're
limited by their training data in many cases the answers that they give
resemble their training data which if you're an artist or a photographer and
your work gets added to a model is probably not your idea of fair use much
less a good time worse when generative
models are faced with a concept that they don't understand or they simply run
out of tokens they can begin to hallucinate that is to say they just
make things up as they go which is why sometimes you get eldrich Abominations
like these with that said these limitations don't mean that machine
learning AI is a dead end it's been deployed very effectively for diagnosing
diseases and in other highly complex scenarios where the data is dense and
the conclusions require interpretation these specialized models are extremely
useful they're just also extremely not
new simple neural networks have been in use for decades for things ranging from
handwriting recognition to web traffic analysis and yes even video game
these are not scripted sequences the AI is determining when your allies choose
to advance and how to best help you out in combat and chatbots the main
difference is that they run much faster on Modern Hardware if I had to distill
down what artificial narrow intelligence really means then I would say it's like
having a thousand monkeys at a thousand typewriters with a thousand pieces of
reference material for what the outputs are supposed to look like with enough
trial and error then they do arrive arrive at a point where they're likely
to spit out a correct or at least correct enough solution then we take all
those monkeys and we take a snapshot of the model State and we start feeding it
inputs for both Fun and Profit what ani
is to a brain then is kind of what a single app is to a computer it's a
building block it's something your brain is capable of but it's just one of its
many many functions shifting GE a bit
then what would artificial general intelligence look like well it
would need to be able to handle everything we've talked about so far
just like your brain can take some past experiences and turn them into a new
creation but again like your own brain
it would need to be able to run many of these models concurrently and
continuously train and iterate on them rather than relying on fixed snapshots
only then would an AGI have the ability to truly learn and adapt to new things
bringing it closer to that that classical definition of AI and really
blur the lines between machine learning and machine Consciousness the problem is
even if we had software that sophisticated we are nowhere close to
being able to run an AGI even on a modern supercomput let alone on your AI
smartphone but all right lonus you still
haven't explained why any of this is even a problem I mean freerange meat is
just marketing bollocks too so who cares well well truthfully in most cases I
don't I mean cooler Master's AI thermal paste snafu I was never bothered by it
because I never expected my paste to be sentient anyway but there are situations
where this kind of marketing can have an impact on user safety and therefore does
matter let's talk about Tesla Mr musk
has said among other things that any vehicle from 2019 onward will be able to
reach full autonomy and he's certainly put out some impressive demos both
canned and even in the form of public beta software that you really can use
and that's really cool but unfortunately it isn't much more than that you see to
operate a vehicle safely it's not enough to be trained with images of painted
lines and traffic cones stop signs pedestrians vehicle Telemetry data it's
not even enough to be trained to predict the likely maneuvers of nearby vehicles
and life forms on the road anything can
happen and by definition by its very
definition Ani is not capable of
handling an edge case that it has never seen before even if it was by the way I
have some really bad news for you Tesla owners out there Hardware 3.0 has about
144 tops or trillion operations per second worth of processing power for
context Windows 11 recall a feature that does little more than take screenshots
and analyze your PC usage for search asks for 40 tops now to be clear tops is
not a be all andall measure of performance and there is no way that
Microsoft has optimized the code for recall nearly as much as Tesla has for
full self-driving but this should still illustrate the point that Tesla either
did or should have known that a vehicle with the AI capabilities of a family of
iPhone 15 Pro users would never achieve
that kind of realtime contextual awareness that's required for complex
situations like operating a motor vehicle and they misrepresented its
capabilities in order to sell more software that was never going to leave
beta that is going to be a doozy of a
class action and it's a common story that has led to this current mess where
fuzzy definitions and impossible promises have turned AI into this
meaningless buzzword like all the rest of them all of them refer to legitimate
useful Technologies some of which have really come to fruition but their
meanings have become diluted with overuse and it means that when computer
cognition finally happens we're going to have to call it something completely
different in order to differentiate it from all of the marketing wank on the
subject of marketing calling ai ai
wasn't an accident the people behind that marketing know what you think AI
means they know that the promise and the Mystique behind the term is tantalizing
and they know you'll click on an article that is interviewing an AI expert who
discusses how dangerous or already alive it is they want you to buy into their
hype they want you to buy into their stocks what we have now though really
are decent summarization engines and
lukewarm guessing machines that are tuned for working with different types
of media they can't reason and anyone
who's seen chat GPT get something ridiculously confidently wrong can
attest to that and they also can't understand why they get these things
wrong which mean they can't learn or improve on their own even if you
explicitly tell them they also have a finite number of things that they can
remember called tokens which limit their ability to maintain a train of thought
for very long anyone who's tried to get chat GPT to write a novel or even a
moderately complex python script can probably attest to that of course as
time goes on some of these limitations will begin to lift and these a Ani
models will start to look more and more like a GI to the lay person I mean just
ask the guy who had Bing fall in love with him but at the end of the day it's
still the same thing as it's always been to paraphrase a paper co-written by
Emily bender and Alexander caller it's a hyper intelligent octopus that is
observing and learning the patterns that are expected of communication and
repeating them back more accurately over time so when faced with a novel
situation like a bear attack that octopus has no hope of being able to
guide you on how to defend yourself with the materials you have on hand it has no
concept of bear or stick only what words
most closely match the pattern that it has previously observed to further
illustrate this if you haven't tried it before try to craft a prompt that coaxes
stable diffusion to spit out something very specific it turns out it's pretty
challenging and when it finally does it it's generally composed of a mosaic of
shapes and patterns from its training model that best match the keywords that
sounds overly simplified but that's because it is in essence what it's doing
it takes the keywords from your prompt and starts compositing filling in the
image until it hits for example a certain percentage of computer and desk
and it does this without any context so if you asked it to show you a computer
would it show you a desktop PC a laptop a server rack and for that matter from
what era the answer is often simply yes
because it lacks the context behind what computer means to you and it can't
always even for a coherent depiction even in the same image so then Linus
just don't worry about it and wait till AGI shows up and you don't have to
bother with online dating anymore well not quite as generative AI models learn
to create works that are closer and closer to our expectations and to
finally understand how many fingers and teeth humans normally have we're going
to start to find it more and more difficult to distinguish their output from real photographs or artwork or
other people ushering in an era of unprecedented distrust and the bad news
is that the folks in charge of helping us deal with the consequences of all of
this have a lot less funding than the ones who are trying to sell it to us so
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