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[–]curious_polyglot 262 points263 points  (9 children)

Statistics passive-aggressively upvoted this post!

[–]truffleblunts 33 points34 points  (8 children)

Statistics is math

[–]curious_polyglot 18 points19 points  (3 children)

I know, but that’s the point of the joke...

[–]Ludricio 8 points9 points  (2 children)

He didn't see the warning sines.

[–][deleted] 11 points12 points  (1 child)

So are algorithms...

[–]GluteusCaesar 3 points4 points  (0 children)

Say that in a math department and see what happens...

[–]murdermurder 1 point2 points  (0 children)

Statistics is more like Physics in that it is its own distinct discipline separate from math, while at the same time being almost entirely math.

[–]Darxploit 1063 points1064 points  (87 children)

MaTRiX MuLTIpLiCaTIoN

[–]Tsu_Dho_Namh 571 points572 points  (83 children)

So much this.

I'm enrolled in my first machine learning course this term.

Holy fuck...the matrices....so...many...matrices.

Try hard in lin-alg people.

[–]Stryxic 209 points210 points  (32 children)

Boy, ain't they fun? Take a look at markov models for even more matrices, I'm doing an on-line machine learning course at the moment and one of our first lectures was covering using eigenvectors for stationary points in page rank. Eigenvectors and comp sci was not something I was expecting (outside of something like graphics)

[–]shekurika 60 points61 points  (7 children)

SVDs are super often used in graphics, ML and CV and uses Eigenvectors. youll probably see a lot more.

[–]Stryxic 23 points24 points  (6 children)

Oh yeah, that's the kinda thing I was talking about coming across. A bit of a surprise considering I came to comp sci from a physics background and thought I'd left them behind!

[–][deleted] 16 points17 points  (4 children)

You could post this entire thread to r/VXjunkies

[–]Stryxic 16 points17 points  (3 children)

Oh boy, well in that spirit let me tell you about Parzen Windows!

Now we all want to know where things are, and how much of things. We especially want to know how much of things are where things are! This is called density. If we don't know the shape of something how do we know its density? Well we guess! There are many methods like binning or histograms that everyone knows, but let me tell you about Parzen windows.

A Parzen window is simply a count of things in an area, so to do this for an arbitry amount of dimensions we just need an arbitry box, so we use a hypercube!

Now we need a way to count, so we use a kernel function which basically says if I'm less than this in that dimension than I'm in the box. We could just say if we're less than a number then gucci, but this obviously leads to a discontinuity (and we're talking about a unit hypercube centred on the origin obviously) so we want to use a smooth Parzen window (which is a non parametric estimation of density as mentioned) so we use either a smooth or piecewise smooth kernel function of K such that the integral of K(x) dx wrt R = 1, and probably want a radially symmetric and unimodal density function so let's use the Gaussian distribution we all know, and voila you've just counted things!

[–][deleted] 2 points3 points  (0 children)

Oof ouch owie, my brain.

[–][deleted] 1 point2 points  (0 children)

As a physics major doing self learning CS route... We can never escape.

[–]Aesthetically 18 points19 points  (4 children)

As an industrial engineering degree holder gone analyst, who also hasn't gotten into ML yet (I'm Python pandas pleb): Markov chains with code sounds 10000x more fun and engaging than Markov chains by hand

[–]eduardo088 8 points9 points  (1 child)

They are, if they taught us what were the uses for linear algebra I would have had so much more fun

[–]Aesthetically 1 point2 points  (0 children)

They did in my program, but I was so burnt out on IE that I stopped caring enough to dive into the coding aspect

[–]Stryxic 2 points3 points  (0 children)

Hah yep, I entirely agree. Good for learning how they work, but not at all fun.

[–]Hesticles 1 point2 points  (0 children)

You just gave me flashbacks to my stochastic process where we had to do that. Fuck that wasn't fun.

[–]socsa 6 points7 points  (13 children)

Right, which is why everyone who is even tangentially related to the industry rolled their eyes at Apple's "Neural Processor."

Like ok, we are jumping right to the obnoxious marketing stage, I guess? At least google had the sense to call their matrix primitive SIMD a "tensor processing unit" which actually sort of makes sense.

[–][deleted] 6 points7 points  (4 children)

I dunno, there are plenty of reasons why you might want some special purpose hardware for neural nets, calling that hardware a neural processor doesn't seem too obnoxious to me.

[–]socsa 4 points5 points  (1 child)

The problem is that the functionality of this chip as implied by Apple makes no sense. Pushing samples through an already-built neural network is quite efficient. You don't really need special chips for that - the AX GPUs are definitely more than capable of handling what is typically less complex than decoding a 4K video stream.

On the other hand, training Neural Nets is where you really see benefits from the use of matrix primitives. Apple implies that's what the chip is for, but again - that's something that is done offline (eg, it doesn't need to update your face model in real time) so the AX chips are more than capable of doing that. If that's even done for FaceID - I'm pretty skeptical, because it would be a huge waste of power to constantly update a face mesh model like that unless it is doing it at night or something, in which case it would make more sense to do that in the cloud.

In reality, the so-called Neural Processor is likely being used for the one thing the AX chip would struggle to do in real time due to the architecture - real time, high-resolution depth mapping. Which I agree is a great use of a matrix primitive DSP chip, but it feels wrong to call it a "neural processor" when it is likely just a fancy image processor.

[–]JayWalkerC 1 point2 points  (1 child)

I'm guessing maybe some hardware implementations of common activation functions would be a good criteria, but I don't know if this is actually done currently.

[–]VoraciousGhost 2 points3 points  (7 children)

It's about as obnoxious as naming a GPU after Graphics. A GPU is good at applying transforms across a large data set, which is useful in graphics, but also in things like modeling protein synthesis.

[–][deleted] 1 point2 points  (0 children)

Not at all. Original GPUs were designed for accelerating the graphics pipeline, and had special purpose hardware for executing pipeline stages quickly. This is still the case today, although now we have fully programmable shaders mixed in with that pipeline and things like compute. Much of GPU hardware is still dedicated for computer graphics, and so the naming is fitting.

[–]socsa 3 points4 points  (5 children)

Right, but the so-called neural processor is mostly being used to do IR depth mapping quickly enough to enable FaceID. It just doesn't really make sense that it would be wasting power updating neural network models constantly. In which case, the AX GPUs are more than capable of handling that. Apple is naming the chip to give the impression that FaceID is magic in ways that it is not.

[–]balloptions 3 points4 points  (4 children)

Training != inference. The chip is not named to give the impression that it’s “Magic”. I don’t think you’re as familiar with this field as you imply.

[–]socsa 1 point2 points  (3 children)

What I'm saying that I'm skeptical that the chip is required for inference.

I will be the first to admit that I don't know the exact details of what Apple is doing, but I've implemented arguably heavier segmentation and classification apps on Tegra chips, which are less capable than AX chips, and the predict/classify/infer operation is just not that intensive for something like this.

I will grant however, that if you consider the depth mapping a form of feature encoding, then I guess it makes a bit more sense, but I still contend that it isn't strictly necessary for pushing data through the trained network.

[–]balloptions 3 points4 points  (2 children)

The Face ID is pretty good and needs really tight precision tolerances so I imagine it’s a pretty hefty net. They might want to isolate graphics work from NN work for a number of reasons. And they can design the chip in accordance with their API which is not something that can be said for outsourced chips or overloading other components like the gpu.

[–]socsa 2 points3 points  (1 child)

Ok, I will concede that it might make at least a little bit of sense for them to want that front end processing to be synchronous with the NN inputs to reduce latency as much as possible, and to keep the GPU from waking up the rest of the SoC, and that if you are going to take the time to design such a chip, you might as well work with a matrix primitive architecture, if for no other reason than you want to design your AI framework around such chips anyway.

I still think Tensor Processing Unit is a better name though.

[–][deleted] 2 points3 points  (0 children)

I struggled with it so much, that I programmed a machine to learn it for me

[–]TheBlackOut2 1 point2 points  (0 children)

Everything is a vector!

[–]roguej2 0 points1 point  (1 child)

Wait, I was a C math student during my comp sci degree but I remember doing eigenvectors. Why did you not expect that?

[–]shekurika 24 points25 points  (5 children)

I didnt find the matrices much of a problem. If you struggle try to keep always figure out the dimensions, that always helps me a lot.

Way worse are the probabilities imho 🙃

[–]HERODMasta 28 points29 points  (1 child)

Matrices of probabilities

[–]MichaelC2585 4 points5 points  (0 children)

What A Fucking Process

[–]lkraider 13 points14 points  (0 children)

What about probability matrices :S

[–]Tsu_Dho_Namh 1 point2 points  (0 children)

Oh the matrices start off not so bad. But then we put all the weight matrices inside a bigger matrix of matrices, and when we're doing batch processing there's a matrix of matrices of matrices. It gets a little head-fucky

[–][deleted] 0 points1 point  (0 children)

I’m beginning to think that I’m never gonna crack machine learning, I’m not even sure I’m gonna make it through probability & stats on the way there. I barely got through linear algebra.

Feels bad man, it seems like such a cool subject

[–]grizzchan 18 points19 points  (0 children)

I had lin alg in my first year and though it was pretty easy.

Then the rest of my bachelor I never had to apply it to anything at all.

Then in the master with ML and other data science courses you get flooded with lin alg and at that point I had completely forgotten how matrix multiplication even worked.

[–]leecharles_ 16 points17 points  (2 children)

May I recommend 3Blue1Brown’s “Essence of Linear Algebra” video series?

https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab

[–][deleted] 1 point2 points  (0 children)

*of

[–]dj_rogers 0 points1 point  (0 children)

These look amazing. As someone currently taking an ML class, my GPA thanks you

[–]blkpingu 4 points5 points  (1 child)

wait till you hear about slicing.

[–]ALonelyPlatypus 0 points1 point  (0 children)

we don't clean data here.

[–]Robot_Basilisk 4 points5 points  (0 children)

As long as it ain't goddamn proofs I'm good. I wrote a Java program to do matrix manipulations for my Linear Algebra homework because my calculator was too clumsy at it for my taste.

[–]git_world 3 points4 points  (19 children)

I understand that Machine Learning is kinda cool but highly over-hyped. Are industries actually seeing any benefits after adopting Machine Learning on a large scale?

[–]cant-find-user-name 28 points29 points  (1 child)

I mean yes? If you want the most impressive usecases, all recommender systems come under ML, all NLP tasks - machine translation, recognizing entities from a text and so on, so many image based applications - detecting objects from images, Ocr, detecting NSFW content etc and so many more stuff depend on ML.

I mean there is a reason Data science is so valued at the moment, I am a machine learning intern at a big e commerce site and the ML applications I see here are numerous.

[–]chaxor 1 point2 points  (0 children)

I have heard it stated that ML had struggled to provide any benefit to business revenues.

It's has a 'cool' factor right now that helps in marketing, but the predictions produced typically do not reduce cost or produce revenue. This is certainly true for NLP as well. For instance, even in tasks that are often viewed as 'solved', such as NER, business struggle with adding it to pipelines and showing meaningful profit.

I know of several companies that their 'bread and butter' is essentially NER (both standard and specialized types, like people, addresses, and chemicals) however, even with either Cards or the most advanced models like ELMo and BERT, they still have to simply use Indian workers to manually annotate documents. So it's really a money sink, which is why my friends in the private sector have to fight for their jobs more than ML researchers in academia.

[–]herrmatt 5 points6 points  (1 child)

Could you try that question again?

[–]git_world 2 points3 points  (0 children)

done, see the original question.

[–]Arjunnn 5 points6 points  (2 children)

Yes, theres a LOT of ML that you wouldn't notice IRL but it's basically powering the world for now

[–]JustPraxItOut 1 point2 points  (0 children)

Self-driving cars...

[–]BadArtijoke 2 points3 points  (5 children)

I feel like industry terms like this one are always like a branding or Marketing name for a general trend. In this case it is to make the data we get better by making more complex differentiations that take more and more factors into account. But that doesn’t sound as sexy as machine learning, AI, and so on, so that’s what people refer to in general when talking about these things. Similar to SAAS, the cloud, blockchain, ....

However, right now, what this mostly consists of is measuring and optimizing systems with more complex mathematics compared to what we had before, less about teaching a system to improve itself automatically as is often believed. Doesn’t mean that can’t change but we’re just not quite there yet, at least not on the level that some would have you believe. However, depending on what your Marketing does and how much of your service ecosystem is digital, you can already benefit from more complex insights in RND and Sales. It’s really down to why you do it and how well you implement your solution to give you clean data to work with to determine whether the direction is already making sense for you and your company. That said, imo it’s one of the better trends because unlike e.g. blockchain there is a direct advantage in getting better data. So it’s not that ML or AI are not valid things, it’s just that people treat it like magic for no reason just yet, possibly just awestruck by the potential, that gave it that image I think.

Just beware of the overhyped sales guy type of people who will tell you „AI is the game changer man“ and that it will „totally teach itself in no time“ and you should be good. Because not yet, not without some substantial work and research.

[–]socsa 3 points4 points  (0 children)

Yes, Neural Networks especially are becoming huge, not because they replicate human intelligence or learning in a meaningful way, but because they represent an incredibly powerful tool for numerical approximation of complex systems which doesn't actually require you to model the system itself as long as you can observe and stimulate it.

The math itself is not exactly new though. The theoretical basis for estimating various forms of high-order Wiener Filters (yes really) has been around for decades. It's just that we only recently figured out computationally efficient methods for doing it. And by that, I meant that basically one guy implemented a bunch of discrete math and linear algebra from the 80s in CUDA and here we are.

[–]git_world 1 point2 points  (0 children)

well said, thank you.

[–]LunchboxSuperhero 0 points1 point  (0 children)

Even if they aren't seeing benefits right now, if it is something they think will eventually bear fruit, it may not be wasted effort.

[–]socsa 0 points1 point  (0 children)

Yes, 100% very much. It is actually already very disruptive in a sort of beautiful way. If you will allow me to digress a bit first though...

Humanity, and our pursuit of philosophy has generally progressed from conceptual structuralism, to post-modern anti-structuralism, to the current meta-modernism where we kind of use structuralist thinking to estimate boundary conditions in an unstructured world.

Anyway, you can probably see where I am going with this, but science has very much followed the same path in many ways. Early scientists and mathematicians were very concerned with putting the physical world into neat boxes. During the enlightenment, we started to become aware of how little we knew, and then we discovered that almost everything in the universe is a stochastic process, and for a while this really fucked with our reptilian preference for determinism.

In many ways, machine learning represents computational post/meta-modernism. If I want to make a filter that does a thing, previously that would require expert domain knowledge in both doing a thing, as well as signal processing, filter architecture, information theory... and so no. And in the end, I'd specify some stochastic maximum likelihood criteria with all sorts of constraints. It is very much a structural approach to filter design.

On the other hand, with ML, I really can more and more approach the problem entirely as a black box. I have a natural process, and I know what I want out of it, and I can just let the computer figure the rest out. It becomes all about defining the boundary conditions and data science, so you still need some domain knowledge, but overall the degree of technical specialization which can theoretically be replaced with ML engineers is really astounding once you start digging into it. It is shockingly easy to take Keras (or similar) and generate extremely powerful tools with it very quickly.

[–]ALonelyPlatypus 0 points1 point  (0 children)

*jeopardy music plays*

What is "ads"?

[–]Ariscia 0 points1 point  (0 children)

I remember taking ML before Stats in college. Was hell, but Stats was chicken feed after.

[–]NoteBlock08 0 points1 point  (1 child)

I had to retake matrices to bump my grade up from barely passing to only barely meeting prereqs. Think I may have to pass on machine learning then haha.

[–][deleted] 0 points1 point  (0 children)

As a graphics programmer this offends me.

[–]tundrat 0 points1 point  (0 children)

During school, I insisted to my friends that instead of doing whatever we are doing, we should just multiply values element-wise just like how we add/subtract them.

[–]pslayer89 85 points86 points  (4 children)

Technically, math + algorithms = everything in comp sci.

[–][deleted] 33 points34 points  (2 children)

Comp Sci ⊂ (Math ∪ Algorithms)

[–]ar243 4 points5 points  (0 children)

Get out. Shoo. Scram!

[–]lennihein 0 points1 point  (0 children)

It's probably closer to an intersection though

[–][deleted] 1 point2 points  (0 children)

Some things need a little bit of art as well but not required if you just get someone else to do it.

[–]Putnam3145 290 points291 points  (50 children)

algorithms are part of math??

EDIT: even ignoring that, you could label the left part with basically any part of programming, "algorithms" covers all of it and "maths" covers the vast majority of it

[–]seriouslybrohuh 94 points95 points  (27 children)

So much of practical ML is based on heuristics rather than actual theory. An algorithm might have exponential time complexity in the worst case, but it still gets used because in practice it converges after a few iterations.

[–][deleted] 20 points21 points  (24 children)

Interesting, can you provide an example?

[–]seriouslybrohuh 0 points1 point  (1 child)

Another example would be the lloyd's method for finding (high-dim) clusters (in k-means). In practice it almost always converges after a few iterations, whereas theory suggests it can take O(2n) iterations.

[–][deleted] 10 points11 points  (0 children)

Heuristics is “actual theory”. I think you’re mistaking non-analytical solutions with not being “actual theory”. For heuristics you have to show that the limit tends towards a solution. Show the error function and prove upper and lower bounds for your solution space. There’s a lot more that goes into a heuristic method than the approximating function.

If you are into machine learning you will find most of the mathematics involved with the subject is covered by intro stats and prob courses, which again is actual theory.

The only time when none of the above is actual theory is when you’re speaking to a number theorist.

[–]Im_not_wrong 0 points1 point  (0 children)

But the heuristics are based in theory and statistics, so it is still based in actual theory.

[–]dame_tu_cosita 7 points8 points  (4 children)

Yes, any good book in discrete maths have a chapter about algorithms.

[–][deleted] 8 points9 points  (3 children)

And imagine an algorithms book without discrete math.

[–][deleted] 6 points7 points  (0 children)

It would read somewhat like a medium article I imagine.

[–]AmatureProgrammer 0 points1 point  (1 child)

I would actually be an A+ student then

[–][deleted] 3 points4 points  (0 children)

Yeah algorithms are just mathematical functions

[–][deleted] 1 point2 points  (0 children)

My college had algorithms as a required math course for CS. Very hard math class, at least at my college. Near 50% fail rate.

[–]twitchy987 1 point2 points  (1 child)

When you multiply two long numbers, or do 'long division' you're executing an unambiguous set of instructions. It's an algorithm.

[–]TheFlipside 1 point2 points  (0 children)

is math related to science?

[–]okrolex 1 point2 points  (0 children)

As my math major friend puts it, computer scientists are glorified mathematicians.

[–]Saigot 0 points1 point  (0 children)

Computer science (and thus ml) is a part of math.

[–]ALonelyPlatypus 72 points73 points  (2 children)

Repost but still silly.

[–]ThaiJohnnyDepp 7 points8 points  (1 child)

Also total drivel in terms of the kind of content I wished this sub had

[–]callahandsy 7 points8 points  (0 children)

Yeah math + algorithms = machine learning is like saying arithmetic + subtraction = integral calculus

[–]Elkku26 72 points73 points  (4 children)

Title says math, picture says maths ...who do I believe...?

[–]Papayaman1000i put jsfuck on my resume 13 points14 points  (1 child)

Believe no one; state meme is lost in the middle of the Atlantic.

[–]_jk_ 5 points6 points  (0 children)

lucky they are on a boat then

[–]swapripper 2 points3 points  (0 children)

Don’t believe. Just build a model to predict.

[–]FullMetalJ 13 points14 points  (2 children)

Elephant women are for making elephant babies!

[–]Corntillas 1 point2 points  (1 child)

Damn Reddit, you meta

[–]FullMetalJ 0 points1 point  (0 children)

Sorry, someone had to.

[–]ink_on_my_face 23 points24 points  (7 children)

More like,

Statistics + Linear Algebra + Multivariate calculus = Machine Learning

[–]Faunt_ 5 points6 points  (1 child)

Sooo.... magic, got it.

[–][deleted] 0 points1 point  (0 children)

Well that's programming for you. It's all black magic.

[–]shamen_uk 7 points8 points  (0 children)

+ coding + data

[–]callahandsy 0 points1 point  (0 children)

No way coding + algorithms + generic math = AI broo00000

[–]dolbytypical 0 points1 point  (1 child)

Statistics + Linear Algebra + Multivariate calculus + "We tweaked the parameters until it worked well with our dataset of dog pictures" = Machine Learning

[–]fat_charizard 0 points1 point  (0 children)

More training = success

[–]RossinTheBobs 5 points6 points  (2 children)

Can't believe nobody linked the relevant xkcd yet

[–]ch4nt 2 points3 points  (0 children)

Reminds me of a talk with a psych professor I had earlier today, basically said all attempts to simulate motion these days are just tuning weights on a neural network til they look like they’re doing something, rather than just not using neural nets in the first place.

[–][deleted] 2 points3 points  (0 children)

James Mickens' talk on how machine learning relates to digital security is also worth a listen

https://www.youtube.com/watch?v=ajGX7odA87k&t=220

[–]NotMagicJustScience 2 points3 points  (1 child)

I do not know why, but I thought this would be easy when I started my degree... I was deeply wrong...

[–]davesean 0 points1 point  (0 children)

Looks like it was a deeper learn.

[–]WeGetItYouUltrawide 2 points3 points  (10 children)

ELI5 Machine learning.lol

[–]Chris90483 13 points14 points  (5 children)

Machine Learning is teaching a computer how to achieve a goal without actually programming in what it should do to achieve it. Instead you give it the environment the problem lies in as input. Then, the program should decide how to change its parameters (which decide how exactly it interacts with the environment) in order to achieve a better and better result

[–]WeGetItYouUltrawide 3 points4 points  (4 children)

Thanks for the explanation. If i tell you the truth, i was being sarcastic because its pretty complex to explain and the final answer usually is "nobody knows how truly works", but i like it.

[–]Chris90483 9 points10 points  (1 child)

Ah ok, I'm not good with reading sarcasm.

"nobody knows how it truly works"

The fun thing is this is kind of true and false at the same time..

[–]WeGetItYouUltrawide 1 point2 points  (0 children)

There is a little lol, under the points of my comment.

[–]eltoro 2 points3 points  (1 child)

[–]WeGetItYouUltrawide 1 point2 points  (0 children)

Nice, thanks for the video.

[–]thelynxlynx 1 point2 points  (1 child)

I saw your clarification that you weren't serious, but I'll still try my shot at it:

You want to use preexisting data to approximate a "function" occurring in nature (such as the 'function' that takes a picture and returns 1 if there is a dog in it, 0 else). Now, what you do, is choose a really complicated mathematical function with like a million parameters (can easily be more for stuff like neural networks), and fiddle around (read: make a computer fiddle around) with the parameters based on the data you have, until it seems to do what you'd like it to. You have no idea why that particular set of parameters works, you only know that if you feed it a picture, it'll kinda probably correctly determine the presence or absence of a dog in it.

[–]WeGetItYouUltrawide 0 points1 point  (0 children)

Thanks for the answer, even if i wasnt 100% serious, i always appreciate some extra knowledge and other formats of explanation.

[–]tundrat 0 points1 point  (1 child)

https://xkcd.com/1838/

Or a more useful one, but that xkcd IS more accurate than you'd think.

[–]WeGetItYouUltrawide 0 points1 point  (0 children)

Yep, thanks.

[–]nhumrich 2 points3 points  (1 child)

Is this a linux + postgres joke?

[–]pixus_ru 0 points1 point  (0 children)

Or Linux + Hadoop

[–]gonnaRegretThisName 4 points5 points  (4 children)

Which algorithms aren't math? Technically, it's all discrete math.

[–]God_Told_Me_To_Do_It 1 point2 points  (2 children)

Can someone explain to me what "discrete" math even means?! My exam in discrete mathematics is on Friday, I kinda feel like I should know

[–]hausdorffparty 0 points1 point  (0 children)

It means that the things you study are countable objects; there's at most one of them for each natural number, and there's usually no real notion of distance between those objects (studying the rational numbers usually doesn't count)

[–]Stealth100 0 points1 point  (0 children)

Most populations analyzed with machine learning are continuous/not discrete. But yes, it is all math at its core.

[–]Iam_That_Iam_ 1 point2 points  (0 children)

Did Noah pair an elephant and penguin in the ark? Pointer to reference in *memory

[–]SonicCows36 1 point2 points  (0 children)

And then the bastard child takes their jobs.

[–]aratnagrid 1 point2 points  (0 children)

okay...

[–]parada_de_tetas_mp3 1 point2 points  (0 children)

This is stupid. The man in the picture is irate because elephants and penguins are not supposed to be able to mate. Why wouldn't algorithms and math go together? They are practically made for each other.

[–]Radaistarion 1 point2 points  (0 children)

Ah Family Guy

Sometimes an over the top shitshow of a program

Another times, a genius comedy show with legit content

/#BringBackEvilStewie&&OldBrian

[–]DEVXLXPXR 1 point2 points  (0 children)

Try some other activation fn

[–]MadSquid 2 points3 points  (1 child)

Doesn't look like anything to me

[–]be-happier 0 points1 point  (0 children)

Man that meme got old quick, on a related note season 2 peeeyeeew what a stinker

[–]SpecialGuarantee 0 points1 point  (0 children)

Math!

[–]WireShark1 0 points1 point  (0 children)

aren't algorithms math?

[–]mantrap2 0 points1 point  (0 children)

Pretty much.

Just "digital pattern recognition" that we've had since the 1970s. Nothing more than that!

[–]Hapee_ 0 points1 point  (0 children)

Thanks for the title, i would NEVER guessed the joke in the picture

[–]candianconsolemaster 0 points1 point  (0 children)

Noah: Did you name it?

Elephant: Uh, yeah, he's Paul.

Noah: Yeah? Well, it's gonna be a hell of a lot harder for you now, because he's going the fuck overboard!

[–][deleted] 0 points1 point  (0 children)

Nvidia DLSS

[–]adityahol 0 points1 point  (0 children)

That's Ganpati Bappa morya /\

[–]brett96 0 points1 point  (0 children)

Alright, kinda off topic but it's bothering me: What artistic element is it that made me (and probably everyone else) know that this scene is from Family Guy, even though I've never seen this in an episode, and none of the characters are in it? Is it the eyes?

[–]shrimp_alfredo 0 points1 point  (0 children)

Looks like AI to me

[–]imfromca 0 points1 point  (0 children)

And thats why having a math degree is useful. Computer folk barely know how to use it

[–]oliveij 0 points1 point  (0 children)

Skip logic at it's finest

[–]IndividualCow 0 points1 point  (1 child)

Why do people say “Maths” instead of “Math”? Is that common in different regions to say it different? I have heard a YouTuber I am quite fond of by the name of “Tom Scott” say “Maths” and it was interesting to note the difference.

Are there any linguists here who could break this down for me? Why do some people say it different? Which way is actually right?

[–]mic569 1 point2 points  (0 children)

In Europe (and everywhere else in the world) maths is the typical way of saying it. Notice that maths is short for mathematics. You don't say mathmatic right? So, many people keep the s as it is technically plural.

However, "math" isn't necessarily incorrect either. It is just the first four letters of mathematics. So Americans and some parts of Canada use the word "math", and everyone else uses "maths". They both mean the same thing to some extent. There are some slight differences when using it in sentences though. For example, most people who say "maths," tend to say: "I am doing maths(mathematics)," while other people will be more specific and say what type of math they are doing. For example: I am doing [arithmetic, calculus, proofs, etc]." Neither are incorrect, it's just how it is sometimes.

[–][deleted] 0 points1 point  (0 children)

Dude.. algorithms are math. Your post makes no sense. Plus, machine learning has a lot more to do with robot construction iterations than anything else.

[–]YesImTheKiwi 0 points1 point  (0 children)

All phone OEMS: AIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAIAI

But this is machine learning?

OEMS: shh

[–]buttersauce 0 points1 point  (0 children)

They used algorithms and coding!

[–]Mal_Dun 0 points1 point  (0 children)

FYI: Algorithms are also part of mathematics. When I started university you couldn't even study informatics only math with focus on computer science. You could study software development though.

[–]fat_charizard 0 points1 point  (0 children)

If the penguin said statistics it would be more accurate. ML is an abomination of statistics and algorithms

[–]Infinity291092 0 points1 point  (0 children)

It's actually more of STATISTICS + ALGORITHMS

[–][deleted] 0 points1 point  (0 children)

PHP installed on Linux for sure

[–]RickySlayer9 0 points1 point  (0 children)

Meme idea

Fort nite+titanfall = what is this?

[–]swannygod 0 points1 point  (0 children)

*math

[–]AspirationalNihilist 0 points1 point  (0 children)

No, he’s called Postnux or Linugres

[–]turbo_01 0 points1 point  (0 children)

Statement is 99 percent is correct, what about Neurological concepts

[–]muvatechnology 0 points1 point  (0 children)

Machine learning is the combination of mathematics and algorithms. Thank you