More on Current Events
Johnny Harris
3 years ago
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.
Erik Engheim
3 years ago
You Misunderstand the Russian Nuclear Threat
Many believe Putin is simply sabre rattling and intimidating us. They see no threat of nuclear war. We can send NATO troops into Ukraine without risking a nuclear war.
I keep reading that Putin is just using nuclear blackmail and that a strong leader will call the bluff. That, in my opinion, misunderstands the danger of sending NATO into Ukraine.
It assumes that once NATO moves in, Putin can either push the red nuclear button or not.
Sure, Putin won't go nuclear if NATO invades Ukraine. So we're safe? Can't we just move NATO?
No, because history has taught us that wars often escalate far beyond our initial expectations. One domino falls, knocking down another. That's why having clear boundaries is vital. Crossing a seemingly harmless line can set off a chain of events that are unstoppable once started.
One example is WWI. The assassin of Archduke Franz Ferdinand could not have known that his actions would kill millions. They couldn't have known that invading Serbia to punish them for not handing over the accomplices would start a world war. Every action triggered a counter-action, plunging Europe into a brutal and bloody war. Each leader saw their actions as limited, not realizing how they kept the dominos falling.
Nobody can predict the future, but it's easy to imagine how NATO intervention could trigger a chain of events leading to a total war. Let me suggest some outcomes.
NATO creates a no-fly-zone. In retaliation, Russia bombs NATO airfields. Russia may see this as a limited counter-move that shouldn't cause further NATO escalation. They think it's a reasonable response to force NATO out of Ukraine. Nobody has yet thought to use the nuke.
Will NATO act? Polish airfields bombed, will they be stuck? Is this an article 5 event? If so, what should be done?
It could happen. Maybe NATO sends troops into Ukraine to punish Russia. Maybe NATO will bomb Russian airfields.
Putin's response Is bombing Russian airfields an invasion or an attack? Remember that Russia has always used nuclear weapons for defense, not offense. But let's not panic, let's assume Russia doesn't go nuclear.
Maybe Russia retaliates by attacking NATO military bases with planes. Maybe they use ships to attack military targets. How does NATO respond? Will they fight Russia in Ukraine or escalate? Will they invade Russia or attack more military installations there?
Seen the pattern? As each nation responds, smaller limited military operations can grow in scope.
So far, the Russian military has shown that they begin with less brutal methods. As losses and failures increase, brutal means are used. Syria had the same. Assad used chemical weapons and attacked hospitals, schools, residential areas, etc.
A NATO invasion of Ukraine would cost Russia dearly. “Oh, this isn't looking so good, better pull out and finish this war,” do you think? No way. Desperate, they will resort to more brutal tactics. If desperate, Russia has a huge arsenal of ugly weapons. They have nerve agents, chemical weapons, and other nasty stuff.
What happens if Russia uses chemical weapons? What if Russian nerve agents kill NATO soldiers horribly? West calls for retaliation will grow. Will we invade Russia? Will we bomb them?
We are angry and determined to punish war criminal Putin, so NATO tanks may be heading to Moscow. We want vengeance for his chemical attacks and bombing of our cities.
Do you think the distance between that red nuclear button and Putin's finger will be that far once NATO tanks are on their way to Moscow?
We might avoid a nuclear apocalypse. A NATO invasion force or even Western cities may be used by Putin. Not as destructive as ICBMs. Putin may think we won't respond to tactical nukes with a full nuclear counterattack. Why would we risk a nuclear Holocaust by launching ICBMs on Russia?
Maybe. My point is that at every stage of the escalation, one party may underestimate the other's response. This war is spiraling out of control and the chances of a nuclear exchange are increasing. Nobody really wants it.
Fear, anger, and resentment cause it. If Putin and his inner circle decide their time is up, they may no longer care about the rest of the world. We saw it with Hitler. Hitler, seeing the end of his empire, ordered the destruction of Germany. Nobody should win if he couldn't. He wanted to destroy everything, including Paris.
In other words, the danger isn't what happens after NATO intervenes The danger is the potential chain reaction. Gambling has a psychological equivalent. It's best to exit when you've lost less. We humans are willing to take small risks for big rewards. To avoid losses, we are willing to take high risks. Daniel Kahneman describes this behavior in his book Thinking, Fast and Slow.
And so bettors who have lost a lot begin taking bigger risks to make up for it. We get a snowball effect. NATO involvement in the Ukraine conflict is akin to entering a casino and placing a bet. We'll start taking bigger risks as we start losing to Russian retaliation. That's the game's psychology.
It's impossible to stop. So will politicians and citizens from both Russia and the West, until we risk the end of human civilization.
You can avoid spiraling into ever larger bets in the Casino by drawing a hard line and declaring “I will not enter that Casino.” We're doing it now. We supply Ukraine. We send money and intelligence but don't cross that crucial line.
It's difficult to watch what happened in Bucha without demanding NATO involvement. What should we do? Of course, I'm not in charge. I'm a writer. My hope is that people will think about the consequences of the actions we demand. My hope is that you think ahead not just one step but multiple dominos.
More and more, we are driven by our emotions. We cannot act solely on emotion in matters of life and death. If we make the wrong choice, more people will die.
Read the original post here.
Claire Berehova
3 years ago
There’s no manual for that
| Kyiv oblast in springtime. Photo by author. |
We’ve been receiving since the war began text messages from the State Emergency Service of Ukraine every few days. They’ve contained information on how to comfort a child and what to do in case of a water outage.
But a question that I struggle to suppress irks within me: How would we know if there really was a threat coming our away? So how can I happily disregard an air raid siren and continue singing to my three-month-old son when I feel like a World War II film became reality? There’s no manual for that.
Along with the anxiety, there’s the guilt that always seems to appear alongside dinner we’re fortunate to still have each evening while brave Ukrainian soldiers are facing serious food insecurity. There’s no manual for how to deal with this guilt.
When it comes to the enemy, there is no manual for how to react to the news of Russian casualties. Every dead Russian soldier weakens Putin, but I also know that many of these men had wives and girlfriends who are now living a nightmare.
So, I felt like I had to start writing my own manual.
The anxiety around the air raid siren? Only with time does it get easier to ignore it, but never completely.
The guilt? All we can do is pray.
That inner conflict? As Russia continues to stun the world with its war crimes, my emotions get less gray — I have to get used to accommodating absurd levels of hatred.
Sadness? It feels a bit more manageable when we laugh, and a little alcohol helps (as it usually does).
Cabin fever? Step outside in the yard when possible. At least the sunshine is becoming more fervent with spring approaching.
Slava Ukraini. Heroyam slava. (Glory to Ukraine. Glory to the heroes.)
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Dmitrii Eliuseev
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.
Thomas Huault
3 years ago
A Mean Reversion Trading Indicator Inspired by Classical Mechanics Is The Kinetic Detrender
DATA MINING WITH SUPERALGORES
Old pots produce the best soup.
Science has always inspired indicator design. From physics to signal processing, many indicators use concepts from mechanical engineering, electronics, and probability. In Superalgos' Data Mining section, we've explored using thermodynamics and information theory to construct indicators and using statistical and probabilistic techniques like reduced normal law to take advantage of low probability events.
An asset's price is like a mechanical object revolving around its moving average. Using this approach, we could design an indicator using the oscillator's Total Energy. An oscillator's energy is finite and constant. Since we don't expect the price to follow the harmonic oscillator, this energy should deviate from the perfect situation, and the maximum of divergence may provide us valuable information on the price's moving average.
Definition of the Harmonic Oscillator in Few Words
Sinusoidal function describes a harmonic oscillator. The time-constant energy equation for a harmonic oscillator is:
With
Time saves energy.
In a mechanical harmonic oscillator, total energy equals kinetic energy plus potential energy. The formula for energy is the same for every kind of harmonic oscillator; only the terms of total energy must be adapted to fit the relevant units. Each oscillator has a velocity component (kinetic energy) and a position to equilibrium component (potential energy).
The Price Oscillator and the Energy Formula
Considering the harmonic oscillator definition, we must specify kinetic and potential components for our price oscillator. We define oscillator velocity as the rate of change and equilibrium position as the price's distance from its moving average.
Price kinetic energy:
It's like:
With
and
L is the number of periods for the rate of change calculation and P for the close price EMA calculation.
Total price oscillator energy =
Given that an asset's price can theoretically vary at a limitless speed and be endlessly far from its moving average, we don't expect this formula's outcome to be constrained. We'll normalize it using Z-Score for convenience of usage and readability, which also allows probabilistic interpretation.
Over 20 periods, we'll calculate E's moving average and standard deviation.
We calculated Z on BTC/USDT with L = 10 and P = 21 using Knime Analytics.
The graph is detrended. We added two horizontal lines at +/- 1.6 to construct a 94.5% probability zone based on reduced normal law tables. Price cycles to its moving average oscillate clearly. Red and green arrows illustrate where the oscillator crosses the top and lower limits, corresponding to the maximum/minimum price oscillation. Since the results seem noisy, we may apply a non-lagging low-pass or multipole filter like Butterworth or Laguerre filters and employ dynamic bands at a multiple of Z's standard deviation instead of fixed levels.
Kinetic Detrender Implementation in Superalgos
The Superalgos Kinetic detrender features fixed upper and lower levels and dynamic volatility bands.
The code is pretty basic and does not require a huge amount of code lines.
It starts with the standard definitions of the candle pointer and the constant declaration :
let candle = record.current
let len = 10
let P = 21
let T = 20
let up = 1.6
let low = 1.6Upper and lower dynamic volatility band constants are up and low.
We proceed to the initialization of the previous value for EMA :
if (variable.prevEMA === undefined) {
variable.prevEMA = candle.close
}And the calculation of EMA with a function (it is worth noticing the function is declared at the end of the code snippet in Superalgos) :
variable.ema = calculateEMA(P, candle.close, variable.prevEMA)
//EMA calculation
function calculateEMA(periods, price, previousEMA) {
let k = 2 / (periods + 1)
return price * k + previousEMA * (1 - k)
}The rate of change is calculated by first storing the right amount of close price values and proceeding to the calculation by dividing the current close price by the first member of the close price array:
variable.allClose.push(candle.close)
if (variable.allClose.length > len) {
variable.allClose.splice(0, 1)
}
if (variable.allClose.length === len) {
variable.roc = candle.close / variable.allClose[0]
} else {
variable.roc = 1
}Finally, we get energy with a single line:
variable.E = 1 / 2 * len * variable.roc + 1 / 2 * P * candle.close / variable.emaThe Z calculation reuses code from Z-Normalization-based indicators:
variable.allE.push(variable.E)
if (variable.allE.length > T) {
variable.allE.splice(0, 1)
}
variable.sum = 0
variable.SQ = 0
if (variable.allE.length === T) {
for (var i = 0; i < T; i++) {
variable.sum += variable.allE[i]
}
variable.MA = variable.sum / T
for (var i = 0; i < T; i++) {
variable.SQ += Math.pow(variable.allE[i] - variable.MA, 2)
}
variable.sigma = Math.sqrt(variable.SQ / T)
variable.Z = (variable.E - variable.MA) / variable.sigma
} else {
variable.Z = 0
}
variable.allZ.push(variable.Z)
if (variable.allZ.length > T) {
variable.allZ.splice(0, 1)
}
variable.sum = 0
variable.SQ = 0
if (variable.allZ.length === T) {
for (var i = 0; i < T; i++) {
variable.sum += variable.allZ[i]
}
variable.MAZ = variable.sum / T
for (var i = 0; i < T; i++) {
variable.SQ += Math.pow(variable.allZ[i] - variable.MAZ, 2)
}
variable.sigZ = Math.sqrt(variable.SQ / T)
} else {
variable.MAZ = variable.Z
variable.sigZ = variable.MAZ * 0.02
}
variable.upper = variable.MAZ + up * variable.sigZ
variable.lower = variable.MAZ - low * variable.sigZWe also update the EMA value.
variable.prevEMA = variable.EMA
Conclusion
We showed how to build a detrended oscillator using simple harmonic oscillator theory. Kinetic detrender's main line oscillates between 2 fixed levels framing 95% of the values and 2 dynamic levels, leading to auto-adaptive mean reversion zones.
Superalgos' Normalized Momentum data mine has the Kinetic detrender indication.
All the material here can be reused and integrated freely by linking to this article and Superalgos.
This post is informative and not financial advice. Seek expert counsel before trading. Risk using this material.
Steffan Morris Hernandez
2 years ago
10 types of cognitive bias to watch out for in UX research & design
10 biases in 10 visuals
Cognitive biases are crucial for UX research, design, and daily life. Our biases distort reality.
After learning about biases at my UX Research bootcamp, I studied Erika Hall's Just Enough Research and used the Nielsen Norman Group's wealth of information. 10 images show my findings.
1. Bias in sampling
Misselection of target population members causes sampling bias. For example, you are building an app to help people with food intolerances log their meals and are targeting adult males (years 20-30), adult females (ages 20-30), and teenage males and females (ages 15-19) with food intolerances. However, a sample of only adult males and teenage females is biased and unrepresentative.
2. Sponsor Disparity
Sponsor bias occurs when a study's findings favor an organization's goals. Beware if X organization promises to drive you to their HQ, compensate you for your time, provide food, beverages, discounts, and warmth. Participants may endeavor to be neutral, but incentives and prizes may bias their evaluations and responses in favor of X organization.
In Just Enough Research, Erika Hall suggests describing the company's aims without naming it.
Third, False-Consensus Bias
False-consensus bias is when a person thinks others think and act the same way. For instance, if a start-up designs an app without researching end users' needs, it could fail since end users may have different wants. https://www.nngroup.com/videos/false-consensus-effect/
Working directly with the end user and employing many research methodologies to improve validity helps lessen this prejudice. When analyzing data, triangulation can boost believability.
Bias of the interviewer
I struggled with this bias during my UX research bootcamp interviews. Interviewing neutrally takes practice and patience. Avoid leading questions that structure the story since the interviewee must interpret them. Nodding or smiling throughout the interview may subconsciously influence the interviewee's responses.
The Curse of Knowledge
The curse of knowledge occurs when someone expects others understand a subject as well as they do. UX research interviews and surveys should reduce this bias because technical language might confuse participants and harm the research. Interviewing participants as though you are new to the topic may help them expand on their replies without being influenced by the researcher's knowledge.
Confirmation Bias
Most prevalent bias. People highlight evidence that supports their ideas and ignore data that doesn't. The echo chamber of social media creates polarization by promoting similar perspectives.
A researcher with confirmation bias may dismiss data that contradicts their research goals. Thus, the research or product may not serve end users.
Design biases
UX Research design bias pertains to study construction and execution. Design bias occurs when data is excluded or magnified based on human aims, assumptions, and preferences.
The Hawthorne Impact
Remember when you behaved differently while the teacher wasn't looking? When you behaved differently without your parents watching? A UX research study's Hawthorne Effect occurs when people modify their behavior because you're watching. To escape judgment, participants may act and speak differently.
To avoid this, researchers should blend into the background and urge subjects to act alone.
The bias against social desire
People want to belong to escape rejection and hatred. Research interviewees may mislead or slant their answers to avoid embarrassment. Researchers should encourage honesty and confidentiality in studies to address this. Observational research may reduce bias better than interviews because participants behave more organically.
Relative Time Bias
Humans tend to appreciate recent experiences more. Consider school. Say you failed a recent exam but did well in the previous 7 exams. Instead, you may vividly recall the last terrible exam outcome.
If a UX researcher relies their conclusions on the most recent findings instead of all the data and results, recency bias might occur.
I hope you liked learning about UX design, research, and real-world biases.