Neural network fun with DCS

[The LT]

Yes, yes, you have all fooled us with your Russian nationality. As a side note, I was raised as a youth with a tribe in the Bolivian rainforest. Your next entree will be?

I can shoot a video with a sheet of A4 with your name on it. :) In the middle of the Red Square or other landmark. :)

[The LT]

Hold on, I will release my pinky so you can begin filming .... (I'll wait a moment while you grab some random Russian vid)

Why, I can write that latin gibberish on that sheet, or whatever you may wish. :) How would you like that done? :)

[AeriaGloria]

I looked it up it’s Arabic for “how noble of you LT.”

 

Feel sorry for all the people who want your book google your name and see this...

[David OC]

Pro's do not act like this. Come on guy's.

 

If you are going to say your "this" make sure you backup any statements with real facts and documentation. There are many pro's in many fields here on this forum.

 

An example of how a real pro posts and behaves. See all Curly's post with the appropriate references with them. No one's questions him about being an engineer. Why?

[The LT]

Why I am not a pro in those fields I am just a passerby. But this is just comedy gold.

Edited March 7, 2020 by The LT

[The LT]

Would you like my pinky to be released from the back of your scalp yet?

Not just yet, my friend.

[AeriaGloria]

Great, now you can continue using your real identity instead of the fake account.

 

What about your theory that they are a disgruntled student you gave a bad grade to?

[AeriaGloria]

And how do we know Aeria that LT is not simply texting his buddy in Russia who is part of his squad? Get serious ....

 

Hey you’re the skeptical one. You really think all these people on the internet are one person with a personal vendetta against you becuase you gave them a bad grade or you got a research grant they didn’t, out of all the people on the internet? You’re an engineer, I’m sure you can look up the statistical improbability. Look at his damn posting history, they’re not kidding where they are from

 

I would think someone about you who professes to only care about facts you would look for the most likely answer, not the most random...

[The LT]

Tomorrow LT, we will play a little game, .... your gonna like it ....

Looking forward to it, have a Good Night, sir!

[The LT]

Google is not going to be able to help you much in the game ....

I have faith in my squadmat... errr, forum community.

[eaglecash867]

Any chance the next episode of this drama could play out in PMs? This thread is now 11 pages long, and only the first page was on-topic. :helpsmilie:

[dburne]

This thread reminds me of something - some threads do not need to be read...

[Someone]

Wow. Big night for @Aurelius....

 

I think the evidence speaks for itself, but just to drive the point home: this is not the way that professors of engineering, media lab directors, authors, or even adults conduct themselves in the face of criticism.

 

@dburne Perhaps so, although hopefully my very long post re: neural networks and software development generally was of some interest.

 

In a world full of internet charlatans where facts no longer matter, if even a single person read this thread and now sees this guy for who he really is, then it's been worth it. Although I cant lie, I did enjoy it :).

 

We probably ought to give this thread a rest.

[*Rage*]

Aurelius you've really lost all credibility already and now you're basically trolling.

 

I've found Someones posts informative.

[The Falcon]

Can you summarize this topic for me pls?

[LASooner]

Can you summarize this topic for me pls?

The internet is a terrible place.

 

Sent from my Pixel 3a XL using Tapatalk

[Someone]

@Aurelius What is happening? A showdown in the streets? I am so confused.

[AeriaGloria]

Lol Buford. I totally believe you now mate, swivel over your ass crack all you want about a time no one agreed upon or talked about. I’m pretty sure all you said was “when I wake up from my American sleep.”

 

Yeah I’m happy to leave it here, our work is done:D

 

Glad about the unicorns you have! Rest easy. I’ll admit this thread did help me realize your VKB review thread by an “engineer” was just a review and probably wasn’t by an actual engineer, I thought it just must’ve been an off day for your “skeptical engineering.” So yeah you can rest easy someone, Buford can take it from here

 

I mean, I was curious, but shouldn’t ask probably, but I can’t resist. What’s the whole “skeptical” thing about?

Edited March 8, 2020 by AeriaGloria

[lobo]

This thread... it's like a really bad soap opera... that should have been cancelled a long time ago.

[fearlessfrog]

 

@Anklebiter, I'm glad I've found an audience. As to who is the fraud here, I think it should be pretty clear by the end of this post :)

 

So, I'm going to split this response up into two sections:

1) a final response to @Aurelius, and

2) A discussion of how ML/AI research actually works, the relationship between that research and open source software, and the nature of value as it pertains to machine learning applications. I promise that this will be more interesting than it sounds :)

 

 

 

Section 1

@Aurelius, my goodness, we've come a long way! Let's examine how we got here.

 

First, @Aurelius posted some irrelevant gobbelygook about Hamiltonian Operators, and discussed neural networks in a way that bore no resemblance to the way that researchers in the field discus them. Given that he had previously represented himself as an electrical engineer running a media lab, I raised an eyebrow at his insistence that he is "a neural network specialist." (Note: Again, not the way people discuss such things... a person who does this work would characterize themselves as being an AI researcher, who may or may not employ neural networks in their work, but I digress).

 

In response to his post, I pointed out the above: that @Aurelius is very clearly not a neural network specialist, even per his own previous statements. I also directed readers to a strange page on his website where he gives thanks to anonymous experts for assistance in the writing of a yet-to-be-completed book, but goes to otherwise great lengths to ensure that the logos of these anonymous expert's institutions are pictured.

 

Across the next few messages @Aurelius:

- Calls me a troll

- Implies that I am simply angry about being shot down by his AI bot (I still find this part of the exchange just incredible. Life really can be stranger than fiction)

- Writes some weird stuff about moustaches, St Judes, and childrens toys

- Claims that I could easily google my way to his identity (You can't, I tried. Occam's would conclude that it's because he's, you know, not who he says he is)

- Crucially, fails to dispute any of the assertions of my original post: specifically, that he has represented himself as a member of an entirely different field, and has most certainly not produced the AI bot described in his first post.

 

Attempting to offer you a way out, I propose the following mechanism for verification:

1) Show me the code that was used to train the bot

2) Disclose which university he is affiliated with, so that we can verify that he does in fact run a media lab, and

3) Demonstrate that the bot exists. Preferably by slaughtering me in aerial combat.

 

@Aurelius then pivots, citing the need to protect valuable proprietary software, imply I want to steal his code, weirdly introduces the name of my employer (while simultaneously questioning whether that company does in fact employ me), and asserts that unless I am Mark Zuckerberg (which, maybe I am :)), he will not share his work product.

 

Side note to readers: @Aurelius, not I, introduced the fact that I work at Google. He knows this information because some time ago, he posted a request for qualified collaborators on yet-to-be-defined DCS software projects. I messaged him, privately, and by way of qualification shared my employer and first name. After the first exchange, I never heard back.

It's also worth pointing out here that, despite what @Aurelius is trying to argue: I am not the person who is making extraordinary claims here and my identity is not really relevant.

Finally: my pseudonym is neither more nor less opaque than that of everyone else here.

 

At this point, we're a few thousand words in, and @Aurelius has still offered zero explanation or response to the central argument of my original post.

Which... weird, right? I mean, who spills that much ink in self defense, while not actually offering a defense? And why go to such lengths to re-categorize what was originally described as a hobby project into something so secretive? And also valuable? When all he's gotta do is show the receipts?

I don't know, but I'd expect that the commercial value of a DCS AI bot is exactly zero dollars to anyone not employed by Eagle Dynamics.

 

There's a saying that extraordinary claims demand extraordinary evidence, and though I generally agree with this principle, I am only requesting ordinary evidence. And yet, we've got nothing.

 

So who the hell is this guy? Here's my guess:

 

@Aurelius IS:

A) Probably an electrical engineer of some type. I read his review of the VKB joystick and he seems to have at least some expertise in that field. How much, I am not qualified to say.

B) Probably a staff member, though not a researcher or faculty member, at a university media lab. He's been pretty consistent on this point, and it would be a weird lie.

 

@Aurelius IS NOT:

A) A person who knows a damn thing about neural networks.

 

 

I recognize however, that to some readers the discussion of sharing code, the value of such code, and the need to protect "proprietary information" may seem, on the surface at least, compelling. Following his blanket refusal to produce a shred of evidence, @Aurelius wrote a longer follow up post to @Anklebiter wherein he characterized the state of AI research as "a bit like the guilds of medieval times in Western Europe" and stated that often engineers at places like Apple will steal a piece of code and then collect license fees from the derivative work. He also writes that the value of such models is a function of "mathematics and physics behind the network and how it is implemented exactly", and that a company like Google would be interested in running such things on "large mainframes" or "supercomputers."

 

It would be difficult, if I were trying to do so, for me to conjure a more misinformed view of how AI research works, the appropriateness of sharing code, the physical machines upon which such models run, and the nature of the US patent system.

 

So, this is the going to be our focus in Section 2: Disassembling the characterization of AI research, and the reasonableness of sharing one's code, as offered by @Aurelius.

 

 

Section 2

 

Let's start with a question: what, exactly, is a neural network?

We know there's code involved, but what else?

As it turns out, the process of training a neural network to predict something is somewhat straightforward.

The reason for this is that, despite what Aurelius writes regarding "exact implementations", all AI researchers today use one of two open source frameworks (there are a few others, but these are the only two that really matter).

They are:

a) Tensorflow, a project funded, open sourced, and given away for free by.... you guessed it: Google. https://www.tensorflow.org/

b) Pytorch, a project funded, open sourced, and given away fo free by.... you guessed it again: Facebook! https://pytorch.org/

So when a researcher has an idea for a different type of neural network, the basic building blocks that they use to assemble it are very standardized. To be clear on this point: no one is re-implementing anything. That's the job of the framework.

 

Every once in a while though, someone comes along and advances the state of the art in the field. Which might sound a little bit like what @Aurelius is describing, and ya know, maybe he's got a point?

Maybe researchers are really worried about their work being stolen and appropriated by others?

 

The good news is that, to answer this question, we don't actually have to guess at all!

We can just look at what happens when these advances are made, who makes them, and in what way they are disclosed!

 

And you know what? It turns out that everyone does the same thing:

1)Publish a paper in an academic journal describing what you did, why its different, and how good it is, and how much smarter than everyone else you, the author, are.

2) The code used to train the model.

3) The model itself.

 

But don't just take my word for it: Google researchers, in late 2018, made a giant advancement in a subfield of AI called NLP. NLP stands for Natural Language Processing and is basically the field whose work allows Siri or Alexa to understand and answer your questions (note: I don't mean the part where the speach gets turned into text. that's called Speech Recognition). This new, groundbreaking model architecture was named BERT (a nerdy joke... the previous state of the art model was named ELMO...so yea.... AI researchers love Sesame Street, I guess).

 

And you know what the researchers did: Immediately published a paper disclosing all the details, shared the model, and put the code on Github for anyone to see.

You can look at it here: https://github.com/google-research/bert

 

And if you think that this advance maybe was less recent than Google was letting on, and that Bert was old news by the time they told the rest of the world about it, that would be wrong too.

Here's an article from a few months ago announcing that Google Search engineers had JUST finished incorporating the Bert language model in the core search algorithm: https://www.theverge.com/2019/10/25/20931657/google-bert-search-context-algorithm-change-10-percent-langauge

To be clear about what happened here: Google spilled the beans about a game-changing AI advance a full year before their own co-workers could even put it to use! On purpose!

 

And this is not a weird anomaly. It literally happens all the time. A few months later, researchers at Facebook announced they'd improved upon the Bert model with a new variation called RoBERTa (I know, the names...ugh), and did the same thing: shared the code, the model, and a paper about the details.

Code here: https://github.com/pytorch/fairseq/tree/master/examples/roberta

 

This is just how science works.

 

But hey, I get it, nobody likes to give away valuable stuff for free, so maybe @Aurelius has a point, and sharing his code would be the same as giving away something really valuable.

So do we square this with the fact that Google and Facebook are constantly giving away their code?

Aren't they profit motivated businesses?

Surely they aren't just doing this out of the goodness of their hearts!

 

And you're right! They aren't! The thing is: the code is not worth all that much, and that's why they share it.

What's valuable, and what these companies would not share, is the data that they used to train their models.

And you will notice that I did NOT ask @Aurelius to share his data, either.

 

So what's the relationship between the data, the code, and the thing we call the neural network?

 

Here's an analogy; it might seem a little weird at first, but stick with me.

 

Imagine you are in a kitchen, and you'd like to cook yourself a hamburger. You know what hamburger is and how one should taste, but you don't know how to make it. So you open up a cookbook, turn to the Hamburger Section, and take look at the recipe. And the recipe tells you all sorts of information about how the end product should operate: it should be juicy, topped with pickles, tomato, and lettuce, and served on a bun, etc. Easy!

 

That is the code: the recipe.

 

Having the code/recipe, does not mean you have a hamburger though.

 

To actually make the hamburger, you'll need the ingredients: the meat, tomato, lettuce, pickles, and bun.

That's the data: the ingredients.

 

To make the actual hamburger/neural net, you need both.

And different data/ingredients, processed using the same receipe/code, will produce different tasting hamburgers/neural nets.

 

Or maybe totally different things entirely: imagine you substitute turkey for ground beef! You could still follow the hamburger recipe!

 

So, the code is the commodity, and not worth all that much. AI code is shared freely, and written using the same frameworks. Only the data is sacred.

To drive this point home, consider: If I posted the entire source code of Google search right here, you would be any closer to building a competing search engine because to do so you would need to have the zillions of terabytes of data that google has collected about web search over the past 15 years (not that I'd know....I would be in jail). And that data is not the code.

 

A few small notes, to wrap up:

1) Machine learning/AI models/neural networks do not run on "Mainframes" or "Supercomputers". All work in this field is done either using GPU's (literally the same kind of GPU as the ones you use to run DCS), or specialized processors designed exclusively for these applications. E.g: Google TPU's: .https://cloud.google.com/tpu/

There are lots of technical reasons why this is the case (ie: that we don't train these models using normal CPU's). If anyone cares to know more, PM me and I'm more than happy to elaborate it.

 

2) Regarding @Aurelius claim that, e.g. Apple regularly takes free code, modifies it some, patents it, and then "licenses" the final product: Despite the fact that the US patent system is a horror show, you cannot patent math. And neural networks are math. And all of this code is written using open source frameworks, which are not patentable. If someone, anyone, can show me a single example of a company that has patented and is successfully licensing a neural network building block I will, I dunno, eat my hat, or something.

 

...And that's all I've got. I hope this was at least somewhat interesting.

But even if it wasn't, in world of internet charlatans, at least we've caught one.

 

:)

[AeriaGloria]

Lol Aurelius you have a chance to make this guy eat a hat

[Someone]

:)

[MilesD]

I started reading this thread with great interest. Leaning about and implementing new technology has enriched the second act of my life. I am not an Engineer, but I am motivated by this supportive, diverse, and extremely knowledgeable community, who has a common interest.

 

Speaking for myself only, I feel when people visit our house, “these forums” our post, and how we conduct ourselves reflects on our whole community. I know tempers can flare; I became frustrated once when a forum member said I had “stole” his Idea. But it’s probably time to close this thread.

 

Thanks Someone for the informative post. The whole making a hamburger analogy was perfect for me. I learned a lot from your clear and concise post, which were obviously written for the uneducated masses like me.

 

@someone, I would love to see you start a new thread about neural networks. I am curious about how the results derived from the iterative process are then put into, or not, a newly generated algorithm, If that is even how it works.

 

Miles

[*Rage*]

@someone, I would love to see you start a new thread about neural networks. I am curious about how the results derived from the iterative process are then put into, or not, a newly generated algorithm, If that is even how it works.

 

Miles

 

+1