The REAL Reason Putin is Invading Ukraine [video with transcript]
Transcript:
[Reporter] The Russian invasion of Ukraine.
Momentum is building for a war between Ukraine and Russia.
[Reporter] Tensions between Russia and the West
are growing rapidly.
[Reporter] President Biden considering deploying
thousands of troops to Eastern Europe.
There are now 100,000 troops
on the Eastern border of Ukraine.
Russia is setting up field hospitals on this border.
Like this is what preparation for war looks like.
A legitimate war.
Ukrainian troops are watching and waiting,
saying they are preparing for a fight.
The U.S. has ordered the families of embassy staff
to leave Ukraine.
Britain has sent all of their nonessential staff home.
And now the U.S. is sending tons of weapons and munitions
to Ukraine's army.
And we're even considering deploying
our own troops to the region.
I mean, this thing is heating up.
Meanwhile, Russia and the West have been in Geneva
and Brussels trying to talk it out,
and sort of getting nowhere.
The message is very clear.
Should Russia take further aggressive actions
against Ukraine the costs will be severe
and the consequences serious.
It's a scary, grim momentum that is unpredictable.
And the chances of miscalculation
and escalation are growing.
I want to explain what's going on here,
but I want to show you that this isn't just
typical geopolitical behavior.
Stuff that can just be explained on the map.
Instead, to understand why 100,000 troops are camped out
on Ukraine's Eastern border, ready for war,
you have to understand Russia
and how it's been cut down over the ages
from the Slavic empire that dominated this whole region
to then the Soviet Union,
which was defeated in the nineties.
And what you really have to understand here
is how that history is transposed
onto the brain of one man.
This guy, Vladimir Putin.
This is a story about regional domination
and struggles between big powers,
but really it's the story about
what Vladimir Putin really wants.
[Reporter] Russian troops moving swiftly
to take control of military bases in Crimea.
[Reporter] Russia has amassed more than 100,000 troops
and a lot of military hardware
at the border with Ukraine.
Let's dive back in.
Okay. Let's get up to speed on what's happening here.
And I'm just going to quickly give you the highlight version
of like the news that's happening,
because I want to get into the juicy part,
which is like why, the roots of all of this.
So let's go.
A few months ago, Russia started sending
more and more troops to this border.
It's this massive border between Ukraine and Russia.
They said they were doing a military exercise,
but the rest of the world was like,
"Yeah, we totally believe you Russia. Pshaw."
This was right before this big meeting
where North American and European countries
were coming together to talk about a lot
of different things, like these countries often do
in these diplomatic summits.
But soon, because of Russia's aggressive behavior
coming in and setting up 100,000 troops
on the border with Ukraine,
the entire summit turned into a whole, "WTF Russia,
what are you doing on the border of Ukraine," meeting.
Before the meeting Putin comes out and says,
"Listen, I have some demands for the West."
And everyone's like, "Okay, Russia, what are your demands?
You know, we have like, COVID19 right now.
And like, that's like surging.
So like, we don't need your like,
bluster about what your demands are."
And Putin's like, "No, here's my list of demands."
Putin's demands for the summit were this:
number one, that NATO, which is this big military alliance
between U.S., Canada, and Europe stop expanding,
meaning they don't let any new members in, okay.
So, Russia is like, "No more new members to your, like,
cool military club that I don't like.
You can't have any more members."
Number two, that NATO withdraw all of their troops
from anywhere in Eastern Europe.
Basically Putin is saying,
"I can veto any military cooperation
or troops going between countries
that have to do with Eastern Europe,
the place that used to be the Soviet Union."
Okay, and number three, Putin demands that America vow
not to protect its allies in Eastern Europe
with nuclear weapons.
"LOL," said all of the other countries,
"You're literally nuts, Vladimir Putin.
Like these are the most ridiculous demands, ever."
But there he is, Putin, with these demands.
These very, very aggressive demands.
And he sort of is implying that if his demands aren't met,
he's going to invade Ukraine.
I mean, it doesn't work like this.
This is not how international relations work.
You don't just show up and say like,
"I'm not gonna allow other countries to join your alliance
because it makes me feel uncomfortable."
But what I love about this list of demands
from Vladimir Putin for this summit
is that it gives us a clue
on what Vladimir Putin really wants.
What he's after here.
You read them closely and you can grasp his intentions.
But to grasp those intentions
you have to understand what NATO is.
and what Russia and Ukraine used to be.
(dramatic music)
Okay, so a while back I made this video
about why Russia is so damn big,
where I explain how modern day Russia started here in Kiev,
which is actually modern day Ukraine.
In other words, modern day Russia, as we know it,
has its original roots in Ukraine.
These places grew up together
and they eventually became a part
of the same mega empire called the Soviet Union.
They were deeply intertwined,
not just in their history and their culture,
but also in their economy and their politics.
So it's after World War II,
it's like the '50s, '60s, '70s, and NATO was formed,
the North Atlantic Treaty Organization.
This was a military alliance between all of these countries,
that was meant to sort of deter the Soviet Union
from expanding and taking over the world.
But as we all know, the Soviet Union,
which was Russia and all of these other countries,
collapsed in 1991.
And all of these Soviet republics,
including Ukraine, became independent,
meaning they were not now a part
of one big block of countries anymore.
But just because the border's all split up,
it doesn't mean that these cultural ties actually broke.
Like for example, the Soviet leader at the time
of the collapse of the Soviet Union, this guy, Gorbachev,
he was the son of a Ukrainian mother and a Russian father.
Like he grew up with his mother singing him
Ukrainian folk songs.
In his mind, Ukraine and Russia were like one thing.
So there was a major reluctance to accept Ukraine
as a separate thing from Russia.
In so many ways, they are one.
There was another Russian at the time
who did not accept this new division.
This young intelligence officer, Vladimir Putin,
who was starting to rise up in the ranks
of postSoviet Russia.
There's this amazing quote from 2005
where Putin is giving this stateoftheunionlike address,
where Putin declares the collapse of the Soviet Union,
quote, "The greatest catastrophe of the 20th century.
And as for the Russian people, it became a genuine tragedy.
Tens of millions of fellow citizens and countrymen
found themselves beyond the fringes of Russian territory."
Do you see how he frames this?
The Soviet Union were all one people in his mind.
And after it collapsed, all of these people
who are a part of the motherland were now outside
of the fringes or the boundaries of Russian territory.
First off, fact check.
Greatest catastrophe of the 20th century?
Like, do you remember what else happened
in the 20th century, Vladimir?
(ominous music)
Putin's worry about the collapse of this one people
starts to get way worse when the West, his enemy,
starts showing up to his neighborhood
to all these exSoviet countries that are now independent.
The West starts selling their ideology
of democracy and capitalism and inviting them
to join their military alliance called NATO.
And guess what?
These countries are totally buying it.
All these exSoviet countries are now joining NATO.
And some of them, the EU.
And Putin is hating this.
He's like not only did the Soviet Union divide
and all of these people are now outside
of the Russia motherland,
but now they're being persuaded by the West
to join their military alliance.
This is terrible news.
Over the years, this continues to happen,
while Putin himself starts to chip away
at Russian institutions, making them weaker and weaker.
He's silencing his rivals
and he's consolidating power in himself.
(triumphant music)
And in the past few years,
he's effectively silenced anyone who can challenge him;
any institution, any court,
or any political rival have all been silenced.
It's been decades since the Soviet Union fell,
but as Putin gains more power,
he still sees the region through the lens
of the old Cold War, Soviet, Slavic empire view.
He sees this region as one big block
that has been torn apart by outside forces.
"The greatest catastrophe of the 20th century."
And the worst situation of all of these,
according to Putin, is Ukraine,
which was like the gem of the Soviet Union.
There was tons of cultural heritage.
Again, Russia sort of started in Ukraine,
not to mention it was a very populous
and industrious, resourcerich place.
And over the years Ukraine has been drifting west.
It hasn't joined NATO yet, but more and more,
it's been electing proWestern presidents.
It's been flirting with membership in NATO.
It's becoming less and less attached
to the Russian heritage that Putin so adores.
And more than half of Ukrainians say
that they'd be down to join the EU.
64% of them say that it would be cool joining NATO.
But Putin can't handle this. He is in total denial.
Like an exboyfriend who handle his exgirlfriend
starting to date someone else,
Putin can't let Ukraine go.
He won't let go.
So for the past decade,
he's been trying to keep the West out
and bring Ukraine back into the motherland of Russia.
This usually takes the form of Putin sending
secret soldiers from Russia into Ukraine
to help the people in Ukraine who want to like separate
from Ukraine and join Russia.
It also takes the form of, oh yeah,
stealing entire parts of Ukraine for Russia.
Russian troops moving swiftly to take control
of military bases in Crimea.
Like in 2014, Putin just did this.
To what America is officially calling
a Russian invasion of Ukraine.
He went down and just snatched this bit of Ukraine
and folded it into Russia.
So you're starting to see what's going on here.
Putin's life's work is to salvage what he calls
the greatest catastrophe of the 20th century,
the division and the separation
of the Soviet republics from Russia.
So let's get to present day. It's 2022.
Putin is at it again.
And honestly, if you really want to understand
the mind of Vladimir Putin and his whole view on this,
you have to read this.
"On the History of Unity of Russians and Ukrainians,"
by Vladimir Putin.
A blog post that kind of sounds
like a ninth grade history essay.
In this essay, Vladimir Putin argues
that Russia and Ukraine are one people.
He calls them essentially the same historical
and spiritual space.
Kind of beautiful writing, honestly.
Anyway, he argues that the division
between the two countries is due to quote,
"a deliberate effort by those forces
that have always sought to undermine our unity."
And that the formula they use, these outside forces,
is a classic one: divide and rule.
And then he launches into this super indepth,
like 10page argument, as to every single historical beat
of Ukraine and Russia's history
to make this argument that like,
this is one people and the division is totally because
of outside powers, i.e. the West.
Okay, but listen, there's this moment
at the end of the post,
that actually kind of hit me in a big way.
He says this, "Just have a look at Austria and Germany,
or the U.S. and Canada, how they live next to each other.
Close in ethnic composition, culture,
and in fact, sharing one language,
they remain sovereign states with their own interests,
with their own foreign policy.
But this does not prevent them
from the closest integration or allied relations.
They have very conditional, transparent borders.
And when crossing them citizens feel at home.
They create families, study, work, do business.
Incidentally, so do millions of those born in Ukraine
who now live in Russia.
We see them as our own close people."
I mean, listen, like,
I'm not in support of what Putin is doing,
but like that, it's like a pretty solid like analogy.
If China suddenly showed up and started like
coaxing Canada into being a part of its alliance,
I would be a little bit like, "What's going on here?"
That's what Putin feels.
And so I kind of get what he means there.
There's a deep heritage and connection between these people.
And he's seen that falter and dissolve
and he doesn't like it.
He clearly genuinely feels a brotherhood
and this deep heritage connection
with the people of Ukraine.
Okay, okay, okay, okay. Putin, I get it.
Your essay is compelling there at the end.
You're clearly very smart and wellread.
But this does not justify what you've been up to. Okay?
It doesn't justify sending 100,000 troops to the border
or sending cyber soldiers to sabotage
the Ukrainian government, or annexing territory,
fueling a conflict that has killed
tens of thousands of people in Eastern Ukraine.
No. Okay.
No matter how much affection you feel for Ukrainian heritage
and its connection to Russia, this is not okay.
Again, it's like the boyfriend
who genuinely loves his girlfriend.
They had a great relationship,
but they broke up and she's free to see whomever she wants.
But Putin is not ready to let go.
[Man In Blue Shirt] What the hell's wrong with you?
I love you, Jessica.
What the hell is wrong with you?
Dude, don't fucking touch me.
I love you. Worldstar!
What is wrong with you? Just stop!
Putin has constructed his own reality here.
One in which Ukraine is actually being controlled
by shadowy Western forces
who are holding the people of Ukraine hostage.
And if that he invades, it will be a swift victory
because Ukrainians will accept him with open arms.
The great liberator.
(triumphant music)
Like, this guy's a total romantic.
He's a history buff and a romantic.
And he has a hill to die on here.
And it is liberating the people
who have been taken from the Russian motherland.
Kind of like the abusive boyfriend, who's like,
"She actually really loves me,
but it's her annoying friends
who were planting all these ideas in her head.
That's why she broke up with me."
And it's like, "No, dude, she's over you."
[Man In Blue Shirt] What the hell is wrong with you?
I love you, Jessica.
I mean, maybe this video should be called
Putin is just like your abusive exboyfriend.
[Man In Blue Shirt] What the hell is wrong with you?
I love you, Jessica!
Worldstar! What's wrong with you?
Okay. So where does this leave us?
It's 2022, Putin is showing up to these meetings in Europe
to tell them where he stands.
He says, "NATO, you cannot expand anymore. No new members.
And you need to withdraw all your troops
from Eastern Europe, my neighborhood."
He knows these demands will never be accepted
because they're ludicrous.
But what he's doing is showing a false effort to say,
"Well, we tried to negotiate with the West,
but they didn't want to."
Hence giving a little bit more justification
to a Russian invasion.
So will Russia invade? Is there war coming?
Maybe; it's impossible to know
because it's all inside of the head of this guy.
But, if I were to make the best argument
that war is not coming tomorrow,
I would look at a few things.
Number one, war in Ukraine would be incredibly costly
for Vladimir Putin.
Russia has a far superior army to Ukraine's,
but still, Ukraine has a very good army
that is supported by the West
and would give Putin a pretty bad bloody nose
in any invasion.
Controlling territory in Ukraine would be very hard.
Ukraine is a giant country.
They would fight back and it would be very hard
to actually conquer and take over territory.
Another major point here is that if Russia invades Ukraine,
this gives NATO new purpose.
If you remember, NATO was created because of the Cold War,
because the Soviet Union was big and nuclear powered.
Once the Soviet Union fell,
NATO sort of has been looking for a new purpose
over the past couple of decades.
If Russia invades Ukraine,
NATO suddenly has a brand new purpose to unite
and to invest in becoming more powerful than ever.
Putin knows that.
And it would be very bad news for him if that happened.
But most importantly, perhaps the easiest clue
for me to believe that war isn't coming tomorrow
is the Russian propaganda machine
is not preparing the Russian people for an invasion.
In 2014, when Russia was about to invade
and take over Crimea, this part of Ukraine,
there was a barrage of state propaganda
that prepared the Russian people
that this was a justified attack.
So when it happened, it wasn't a surprise
and it felt very normal.
That isn't happening right now in Russia.
At least for now. It may start happening tomorrow.
But for now, I think Putin is showing up to the border,
flexing his muscles and showing the West that he is earnest.
I'm not sure that he's going to invade tomorrow,
but he very well could.
I mean, read the guy's blog post
and you'll realize that he is a romantic about this.
He is incredibly idealistic about the glory days
of the Slavic empires, and he wants to get it back.
So there is dangerous momentum towards war.
And the way war works is even a small little, like, fight,
can turn into the other guy
doing something bigger and crazier.
And then the other person has to respond
with something a little bit bigger.
That's called escalation.
And there's not really a ceiling
to how much that momentum can spin out of control.
That is why it's so scary when two nuclear countries
go to war with each other,
because there's kind of no ceiling.
So yeah, it's dangerous. This is scary.
I'm not sure what happens next here,
but the best we can do is keep an eye on this.
At least for now, we better understand
what Putin really wants out of all of this.
Thanks for watching.
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3 years ago
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And why we must keep arming Ukraine
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Read this from Nadin Brzezinski. She's not a native English speaker, so there are grammar errors, but her tale smells true.
Terrible truth.
There's much more that reveals Russia's grim reality.
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It lets me write/publish.
Russian friends are shocked. Many are here because their parents escaped Russian anti-semitism and authoritarian oppression. A Russian cultural legacy says a strongman's methods are admirable.
A legacy of a slavery history disguised as serfdom. Peasants and Princes.
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Will Lockett
3 years ago
Russia's nukes may be useless
Russia's nuclear threat may be nullified by physics.
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Here's Russia's issue.
A thermonuclear bomb needs deuterium (hydrogen with one neutron) and tritium (hydrogen with two neutrons). Because these two isotopes fuse at lower energies than others, the bomb works. One problem. Tritium is highly radioactive, with a half-life of only 12.5 years, and must be artificially made.
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Why does this affect Putin's nukes?
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Russia has a smaller economy than New York, yet they are running an invasion, fending off international sanctions, and refining tritium for 4,447 thermonuclear weapons.
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B Kean
2 years ago
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Monster.
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2 years ago
Creating Images on Your Local PC Using Stable Diffusion AI
Deep learning-based generative art is being researched. As usual, self-learning is better. Some models, like OpenAI's DALL-E 2, require registration and can only be used online, but others can be used locally, which is usually more enjoyable for curious users. I'll demonstrate the Stable Diffusion model's operation on a standard PC.
Let’s get started.
What It Does
Stable Diffusion uses numerous components:
A generative model trained to produce images is called a diffusion model. The model is incrementally improving the starting data, which is only random noise. The model has an image, and while it is being trained, the reversed process is being used to add noise to the image. Being able to reverse this procedure and create images from noise is where the true magic is (more details and samples can be found in the paper).
An internal compressed representation of a latent diffusion model, which may be altered to produce the desired images, is used (more details can be found in the paper). The capacity to fine-tune the generation process is essential because producing pictures at random is not very attractive (as we can see, for instance, in Generative Adversarial Networks).
A neural network model called CLIP (Contrastive Language-Image Pre-training) is used to translate natural language prompts into vector representations. This model, which was trained on 400,000,000 image-text pairs, enables the transformation of a text prompt into a latent space for the diffusion model in the scenario of stable diffusion (more details in that paper).
This figure shows all data flow:
The weights file size for Stable Diffusion model v1 is 4 GB and v2 is 5 GB, making the model quite huge. The v1 model was trained on 256x256 and 512x512 LAION-5B pictures on a 4,000 GPU cluster using over 150.000 NVIDIA A100 GPU hours. The open-source pre-trained model is helpful for us. And we will.
Install
Before utilizing the Python sources for Stable Diffusion v1 on GitHub, we must install Miniconda (assuming Git and Python are already installed):
wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.12.0-Linux-x86_64.sh
chmod +x Miniconda3-py39_4.12.0-Linux-x86_64.sh
./Miniconda3-py39_4.12.0-Linux-x86_64.sh
conda update -n base -c defaults condaInstall the source and prepare the environment:
git clone https://github.com/CompVis/stable-diffusion
cd stable-diffusion
conda env create -f environment.yaml
conda activate ldm
pip3 install transformers --upgradeDownload the pre-trained model weights next. HiggingFace has the newest checkpoint sd-v14.ckpt (a download is free but registration is required). Put the file in the project folder and have fun:
python3 scripts/txt2img.py --prompt "hello world" --plms --ckpt sd-v1-4.ckpt --skip_grid --n_samples 1Almost. The installation is complete for happy users of current GPUs with 12 GB or more VRAM. RuntimeError: CUDA out of memory will occur otherwise. Two solutions exist.
Running the optimized version
Try optimizing first. After cloning the repository and enabling the environment (as previously), we can run the command:
python3 optimizedSD/optimized_txt2img.py --prompt "hello world" --ckpt sd-v1-4.ckpt --skip_grid --n_samples 1Stable Diffusion worked on my visual card with 8 GB RAM (alas, I did not behave well enough to get NVIDIA A100 for Christmas, so 8 GB GPU is the maximum I have;).
Running Stable Diffusion without GPU
If the GPU does not have enough RAM or is not CUDA-compatible, running the code on a CPU will be 20x slower but better than nothing. This unauthorized CPU-only branch from GitHub is easiest to obtain. We may easily edit the source code to use the latest version. It's strange that a pull request for that was made six months ago and still hasn't been approved, as the changes are simple. Readers can finish in 5 minutes:
Replace if attr.device!= torch.device(cuda) with if attr.device!= torch.device(cuda) and torch.cuda.is available at line 20 of ldm/models/diffusion/ddim.py ().
Replace if attr.device!= torch.device(cuda) with if attr.device!= torch.device(cuda) and torch.cuda.is available in line 20 of ldm/models/diffusion/plms.py ().
Replace device=cuda in lines 38, 55, 83, and 142 of ldm/modules/encoders/modules.py with device=cuda if torch.cuda.is available(), otherwise cpu.
Replace model.cuda() in scripts/txt2img.py line 28 and scripts/img2img.py line 43 with if torch.cuda.is available(): model.cuda ().
Run the script again.
Testing
Test the model. Text-to-image is the first choice. Test the command line example again:
python3 scripts/txt2img.py --prompt "hello world" --plms --ckpt sd-v1-4.ckpt --skip_grid --n_samples 1The slow generation takes 10 seconds on a GPU and 10 minutes on a CPU. Final image:
Hello world is dull and abstract. Try a brush-wielding hamster. Why? Because we can, and it's not as insane as Napoleon's cat. Another image:
Generating an image from a text prompt and another image is interesting. I made this picture in two minutes using the image editor (sorry, drawing wasn't my strong suit):
I can create an image from this drawing:
python3 scripts/img2img.py --prompt "A bird is sitting on a tree branch" --ckpt sd-v1-4.ckpt --init-img bird.png --strength 0.8It was far better than my initial drawing:
I hope readers understand and experiment.
Stable Diffusion UI
Developers love the command line, but regular users may struggle. Stable Diffusion UI projects simplify image generation and installation. Simple usage:
Unpack the ZIP after downloading it from https://github.com/cmdr2/stable-diffusion-ui/releases. Linux and Windows are compatible with Stable Diffusion UI (sorry for Mac users, but those machines are not well-suitable for heavy machine learning tasks anyway;).
Start the script.
Done. The web browser UI makes configuring various Stable Diffusion features (upscaling, filtering, etc.) easy:
V2.1 of Stable Diffusion
I noticed the notification about releasing version 2.1 while writing this essay, and it was intriguing to test it. First, compare version 2 to version 1:
alternative text encoding. The Contrastive LanguageImage Pre-training (CLIP) deep learning model, which was trained on a significant number of text-image pairs, is used in Stable Diffusion 1. The open-source CLIP implementation used in Stable Diffusion 2 is called OpenCLIP. It is difficult to determine whether there have been any technical advancements or if legal concerns were the main focus. However, because the training datasets for the two text encoders were different, the output results from V1 and V2 will differ for the identical text prompts.
a new depth model that may be used to the output of image-to-image generation.
a revolutionary upscaling technique that can quadruple the resolution of an image.
Generally higher resolution Stable Diffusion 2 has the ability to produce both 512x512 and 768x768 pictures.
The Hugging Face website offers a free online demo of Stable Diffusion 2.1 for code testing. The process is the same as for version 1.4. Download a fresh version and activate the environment:
conda deactivate
conda env remove -n ldm # Use this if version 1 was previously installed
git clone https://github.com/Stability-AI/stablediffusion
cd stablediffusion
conda env create -f environment.yaml
conda activate ldmHugging Face offers a new weights ckpt file.
The Out of memory error prevented me from running this version on my 8 GB GPU. Version 2.1 fails on CPUs with the slow conv2d cpu not implemented for Half error (according to this GitHub issue, the CPU support for this algorithm and data type will not be added). The model can be modified from half to full precision (float16 instead of float32), however it doesn't make sense since v1 runs up to 10 minutes on the CPU and v2.1 should be much slower. The online demo results are visible. The same hamster painting with a brush prompt yielded this result:
It looks different from v1, but it functions and has a higher resolution.
The superresolution.py script can run the 4x Stable Diffusion upscaler locally (the x4-upscaler-ema.ckpt weights file should be in the same folder):
python3 scripts/gradio/superresolution.py configs/stable-diffusion/x4-upscaling.yaml x4-upscaler-ema.ckptThis code allows the web browser UI to select the image to upscale:
The copy-paste strategy may explain why the upscaler needs a text prompt (and the Hugging Face code snippet does not have any text input as well). I got a GPU out of memory error again, although CUDA can be disabled like v1. However, processing an image for more than two hours is unlikely:
Stable Diffusion Limitations
When we use the model, it's fun to see what it can and can't do. Generative models produce abstract visuals but not photorealistic ones. This fundamentally limits The generative neural network was trained on text and image pairs, but humans have a lot of background knowledge about the world. The neural network model knows nothing. If someone asks me to draw a Chinese text, I can draw something that looks like Chinese but is actually gibberish because I never learnt it. Generative AI does too! Humans can learn new languages, but the Stable Diffusion AI model includes only language and image decoder brain components. For instance, the Stable Diffusion model will pull NO WAR banner-bearers like this:
V1:
V2.1:
The shot shows text, although the model never learned to read or write. The model's string tokenizer automatically converts letters to lowercase before generating the image, so typing NO WAR banner or no war banner is the same.
I can also ask the model to draw a gorgeous woman:
V1:
V2.1:
The first image is gorgeous but physically incorrect. A second one is better, although it has an Uncanny valley feel. BTW, v2 has a lifehack to add a negative prompt and define what we don't want on the image. Readers might try adding horrible anatomy to the gorgeous woman request.
If we ask for a cartoon attractive woman, the results are nice, but accuracy doesn't matter:
V1:
V2.1:
Another example: I ordered a model to sketch a mouse, which looks beautiful but has too many legs, ears, and fingers:
V1:
V2.1: improved but not perfect.
V1 produces a fun cartoon flying mouse if I want something more abstract:
I tried multiple times with V2.1 but only received this:
The image is OK, but the first version is closer to the request.
Stable Diffusion struggles to draw letters, fingers, etc. However, abstract images yield interesting outcomes. A rural landscape with a modern metropolis in the background turned out well:
V1:
V2.1:
Generative models help make paintings too (at least, abstract ones). I searched Google Image Search for modern art painting to see works by real artists, and this was the first image:
I typed "abstract oil painting of people dancing" and got this:
V1:
V2.1:
It's a different style, but I don't think the AI-generated graphics are worse than the human-drawn ones.
The AI model cannot think like humans. It thinks nothing. A stable diffusion model is a billion-parameter matrix trained on millions of text-image pairs. I input "robot is creating a picture with a pen" to create an image for this post. Humans understand requests immediately. I tried Stable Diffusion multiple times and got this:
This great artwork has a pen, robot, and sketch, however it was not asked. Maybe it was because the tokenizer deleted is and a words from a statement, but I tried other requests such robot painting picture with pen without success. It's harder to prompt a model than a person.
I hope Stable Diffusion's general effects are evident. Despite its limitations, it can produce beautiful photographs in some settings. Readers who want to use Stable Diffusion results should be warned. Source code examination demonstrates that Stable Diffusion images feature a concealed watermark (text StableDiffusionV1 and SDV2) encoded using the invisible-watermark Python package. It's not a secret, because the official Stable Diffusion repository's test watermark.py file contains a decoding snippet. The put watermark line in the txt2img.py source code can be removed if desired. I didn't discover this watermark on photographs made by the online Hugging Face demo. Maybe I did something incorrectly (but maybe they are just not using the txt2img script on their backend at all).
Conclusion
The Stable Diffusion model was fascinating. As I mentioned before, trying something yourself is always better than taking someone else's word, so I encourage readers to do the same (including this article as well;).
Is Generative AI a game-changer? My humble experience tells me:
I think that place has a lot of potential. For designers and artists, generative AI can be a truly useful and innovative tool. Unfortunately, it can also pose a threat to some of them since if users can enter a text field to obtain a picture or a website logo in a matter of clicks, why would they pay more to a different party? Is it possible right now? unquestionably not yet. Images still have a very poor quality and are erroneous in minute details. And after viewing the image of the stunning woman above, models and fashion photographers may also unwind because it is highly unlikely that AI will replace them in the upcoming years.
Today, generative AI is still in its infancy. Even 768x768 images are considered to be of a high resolution when using neural networks, which are computationally highly expensive. There isn't an AI model that can generate high-resolution photographs natively without upscaling or other methods, at least not as of the time this article was written, but it will happen eventually.
It is still a challenge to accurately represent knowledge in neural networks (information like how many legs a cat has or the year Napoleon was born). Consequently, AI models struggle to create photorealistic photos, at least where little details are important (on the other side, when I searched Google for modern art paintings, the results are often even worse;).
When compared to the carefully chosen images from official web pages or YouTube reviews, the average output quality of a Stable Diffusion generation process is actually less attractive because to its high degree of randomness. When using the same technique on their own, consumers will theoretically only view those images as 1% of the results.
Anyway, it's exciting to witness this area's advancement, especially because the project is open source. Google's Imagen and DALL-E 2 can also produce remarkable findings. It will be interesting to see how they progress.
Stephen Moore
3 years ago
Trading Volume on OpenSea Drops by 99% as the NFT Boom Comes to an End
Wasn't that a get-rich-quick scheme?
OpenSea processed $2.7 billion in NFT transactions in May 2021.
Fueled by a crypto bull run, rumors of unfathomable riches, and FOMO, Bored Apes, Crypto Punks, and other JPEG-format trash projects flew off the virtual shelves, snatched up by retail investors and celebrities alike.
Over a year later, those shelves are overflowing and warehouses are backlogged. Since March, I've been writing less. In May and June, the bubble was close to bursting.
Apparently, the boom has finally peaked.
This bubble has punctured, and deflation has begun. On Aug. 28, OpenSea processed $9.34 million.
From that euphoric high of $2.7 billion, $9.34 million represents a spectacular decline of 99%.
OpenSea contradicts the data. A trading platform spokeswoman stated the comparison is unfair because it compares the site's highest and lowest trading days. They're the perfect two data points to assess the drop. OpenSea chooses to use ETH volume measures, which ignore crypto's shifting price. Since January 2022, monthly ETH volume has dropped 140%, according to Dune.
Unconvincing counterargument.
Further OpenSea indicators point to declining NFT demand:
Since January 2022, daily user visits have decreased by 50%.
Daily transactions have decreased by 50% since the beginning of the year in the same manner.
Off-platform, the floor price of Bored Apes has dropped from 145 ETH to 77 ETH. (At $4,800, a reduction from $700,000 to $370,000). Google search data shows waning popular interest.
It is a trend that will soon vanish, just like laser eyes.
NFTs haven't moved since the new year. Eminem and Snoop Dogg can utilize their apes in music videos or as 3D visuals to perform at the VMAs, but the reality is that NFTs have lost their public appeal and the market is trying to regain its footing.
They've lost popularity because?
Breaking records. The technology still lacks genuine use cases a year and a half after being popular.
They're pricey prestige symbols that have made a few people rich through cunning timing or less-than-savory scams or rug pulling. Over $10.5 billion has been taken through frauds, most of which are NFT enterprises promising to be the next Bored Apes, according to Web3 is going wonderfully. As the market falls, many ordinary investors realize they purchased into a self-fulfilling ecosystem that's halted. Many NFTs are sold between owner-held accounts to boost their price, data suggests. Most projects rely on social media excitement to debut with a high price before the first owners sell and chuckle to the bank. When they don't, the initiative fails, leaving investors high and dry.
NFTs are fading like laser eyes. Most people pushing the technology don't believe in it or the future it may bring. No, they just need a Kool-Aid-drunk buyer.
Everybody wins. When your JPEGs are worth 99% less than when you bought them, you've lost.
When demand reaches zero, many will lose.
KonstantinDr
3 years ago
Early Adopters And the Fifth Reason WHY
Product management wizardry.
Early adopters buy a product even if it hasn't hit the market or has flaws.
Who are the early adopters?
Early adopters try a new technology or product first. Early adopters are interested in trying or buying new technologies and products before others. They're risk-tolerant and can provide initial cash flow and product reviews. They help a company's new product or technology gain social proof.
Early adopters are most common in the technology industry, but they're in every industry. They don't follow the crowd. They seek innovation and report product flaws before mass production. If the product works well, the first users become loyal customers, and colleagues value their opinion.
What to do with early adopters?
They can be used to collect feedback and initial product promotion, first sales, and product value validation.
How to find early followers?
Start with your immediate environment and target audience. Communicate with them to see if they're interested in your value proposition.
1) Innovators (2.5% of the population) are risk-takers seeking novelty. These people are the first to buy new and trendy items and drive social innovation. However, these people are usually elite;
Early adopters (13.5%) are inclined to accept innovations but are more cautious than innovators; they start using novelties when innovators or famous people do;
3) The early majority (34%) is conservative; they start using new products when many people have mastered them. When the early majority accepted the innovation, it became ingrained in people's minds.
4) Attracting 34% of the population later means the novelty has become a mass-market product. Innovators are using newer products;
5) Laggards (16%) are the most conservative, usually elderly people who use the same products.
Stages of new information acceptance
1. The information is strange and rejected by most. Accepted only by innovators;
2. When early adopters join, more people believe it's not so bad; when a critical mass is reached, the novelty becomes fashionable and most people use it.
3. Fascination with a novelty peaks, then declines; the majority and laggards start using it later; novelty becomes obsolete; innovators master something new.
Problems with early implementation
Early adopter sales have disadvantages.
Higher risk of defects
Selling to first-time users increases the risk of defects. Early adopters are often influential, so this can affect the brand's and its products' long-term perception.
Not what was expected
First-time buyers may be disappointed by the product. Marketing messages can mislead consumers, and if the first users believe the company misrepresented the product, this will affect future sales.
Compatibility issues
Some technological advances cause compatibility issues. Consumers may be disappointed if new technology is incompatible with their electronics.
Method 5 WHY
Let's talk about 5 why, a good tool for finding project problems' root causes. This method is also known as the five why rule, method, or questions.
The 5 why technique came from Toyota's lean manufacturing and helps quickly determine a problem's root cause.
On one, two, and three, you simply do this:
We identify and frame the issue for which a solution is sought.
We frequently ponder this question. The first 2-3 responses are frequently very dull, making you want to give up on this pointless exercise. However, after that, things get interesting. And occasionally it's so fascinating that you question whether you really needed to know.
We consider the final response, ponder it, and choose a course of action.
Always do the 5 whys with the customer or team to have a reasonable discussion and better understand what's happening.
And the “five whys” is a wonderful and simplest tool for introspection. With the accumulated practice, it is used almost automatically in any situation like “I can’t force myself to work, the mood is bad in the morning” or “why did I decide that I have no life without this food processor for 20,000 rubles, which will take half of my rather big kitchen.”
An illustration of the five whys
A simple, but real example from my work practice that I think is very indicative, given the participants' low IT skills. Anonymized, of course.
Users spend too long looking for tender documents.
Why? Because they must search through many company tender documents.
Why? Because the system can't filter department-specific bids.
Why? Because our contract management system requirements didn't include a department-tender link. That's it, right? We'll add a filter and be happy. but still…
why? Because we based the system's requirements on regulations for working with paper tender documents (when they still had envelopes and autopsies), not electronic ones, and there was no search mechanism.
Why? We didn't consider how our work would change when switching from paper to electronic tenders when drafting the requirements.
Now I know what to do in the future. We add a filter, enter department data, and teach users to use it. This is tactical, but strategically we review the same forgotten requirements to make all the necessary changes in a package, plus we include it in the checklist for the acceptance of final requirements for the future.
Errors when using 5 why
Five whys seems simple, but it can be misused.
Popular ones:
The accusation of everyone and everything is then introduced. After all, the 5 why method focuses on identifying the underlying causes rather than criticizing others. As a result, at the third step, it is not a good idea to conclude that the system is ineffective because users are stupid and that we can therefore do nothing about it.
to fight with all my might so that the outcome would be exactly 5 reasons, neither more nor less. 5 questions is a typical number (it sounds nice, yes), but there could be 3 or 7 in actuality.
Do not capture in-between responses. It is difficult to overestimate the power of the written or printed word, so the result is so-so when the focus is lost. That's it, I suppose. Simple, quick, and brilliant, like other project management tools.
Conclusion
Today we analyzed important study elements:
Early adopters and 5 WHY We've analyzed cases and live examples of how these methods help with product research and growth point identification. Next, consider the HADI cycle.
