Nvidia i Anthropic xoquen pels models de pesos oberts: què defensen realment

I think Anthropic just made a new big

enemy. And for once, it's not me. It's

Jensen, the CEO of Nvidia, who made a

Twitter account and his first ever post

mostly to call out Anthropic. And I know

this doesn't look like that because this

is a generic letter from Nvidia, but the

letter is about openweight models. And

this letter has been signed by pretty

much everyone you could think of in the

AI and AI adjacent space from Amazon and

AMD to Cloudflare and Bolt to Comcast.

Obviously Google snuck in here.

Companies like Mistral of course they

want to be in here. They're open weight.

Microsoft, Meta, Nouse, Nvidia, they

wrote it. But most importantly, we got

Open AI in here. Hell, even SpaceX AI is

in here. But OpenAI is, and that's the

important one because you might notice

one company that isn't here despite

pretty much every other AI or AI

adjacent company sneaking in. The one

that's not is of course Anthropic. And

that means we need to have a talk. Why

the hell is IBM a chiller company than

Anthropic? What do they have against

openweight models? We could spend a

bunch of time trying to infer their

positions, but thankfully we don't have

to because Dario put out a public letter

addressing the controversy and it's a,

as is most writing from Daario, it's an

interesting one. So, you have any

interest in openweight models, where

they are going, how inference gets

cheaper, and what's going on at the

frontier. I'm sure you will love this.

If you like me on anthropic, you'll like

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We got a couple steps to go through here

to understand why Jensen made this

letter. The first is what was going on

that made open weights a conversation.

Second is why Jensen specifically wanted

to come out and talk. Third is of course

what Jensen said. And then we have the

follow-up. Why everyone agrees with him

and most importantly why Anthropic

doesn't. In the interest of not wasting

your guys' time, I would recommend you

watch the video I recently posted about

why the labs are scared of Kimmy because

K3 is a great model and the government

is now coming out and taking a stance on

it. Assistant to the president Michael

Katzios shared the following last week

and this is the start of a huge [ __ ]

show. We have information that

Moonshotai distilled anthropics fable

for the development of its K3 model. To

do this they developed a sophisticated

internal platform to conduct largecale

distillation against US models allowing

them to quickly switch between multiple

methods of access to avoid detection.

Moonshot has also acquired GB300

equipped servers and has accessed GB300s

in Thailand likely to train its AI

models. The US strongly supports the

free and fair development of AI,

including a thriving competitive

ecosystem that spans frontier models,

specialized systems, open source

frameworks, and openweight models.

Legitimate AI distillation used to

create smaller, more efficient models

plays a vital role in the open

innovation ecosystem. However,

large-scale covert industrial

distillation aimed at stealing

proprietary US technologies and

undermining American research is

unacceptable. This one post and all of

the things that happened around it have

started quite a fire in the model

hosting landscape. And to be real here,

the only companies relevant in this post

directly are of course Moonshot. They're

talking about Moonshot's model K3 as

well as Anthropic. But there is one more

company that's product is mentioned in

this GB300. That's Nvidia chips. Both

Anthropic and Moonshot rely heavily on

Nvidia hardware to actually train their

models and also host those same models.

Which means that Nvidia benefits greatly

when more people are training, more

people are hosting, and more people are

doing more things with AI. Nvidia

benefits a ton because the vast majority

of training happens on AI, like 99%. And

to this day, the majority of inference

is also still happening on Nvidia.

Despite all the attempts to move to

other things, Nvidia has absolutely

crushed in both research and hosting of

models. This isn't a screw Nvidia or

even a screw moonshot post. This is a

attempt to cause a loss of faith in

openweight models from China because for

various reasons, China is where the

majority of openweight models are coming

from. Again, watch my video about the

labs being scared of Kimmy to better

understand all of this. There's a lot of

reasons that the Chinese labs are

choosing to go openweight with their

models, and China itself is definitely

part of that strategy, but this post can

and often was interpreted as an

anti-openweight post, which is why

everyone cooked him in the replies. I

don't remember letting Anthropic scrape

my GitHub profile as well as all of my

online writing, citing the fact that

Anthropic copied a lot of content from

the internet, so why can't other labs

copy from their work? Lol. Apparently,

the show still continues even when we're

all aware of how you are fed these lines

by anthropic funded lobbyists. Can you

describe what distillation is to me? And

of course, a personal favorite, given

that Fable 5 refuses to do much of the

tasks that Kimmy K3 does, I find this

exceptionally hard to believe. Also, the

fact that K3 came out just a few weeks

after Fable went G again, there's no way

they had enough data to do proper like

distillation off of Fable. And now that

I've used Opus 5 so much and have grown

to hate it, I can say confidently that

distilling Fable is not enough to make a

good model. So with all of that said and

all of the comms around this catching

fire, 2 days later, Jensen made this

public letter. For my first post, I'm

sharing a letter Nvidia signed on why

open models matter. AI will transform

every industry, power every company, and

be built by every country. Open models

strengthen safety and cyber security,

accelerate innovation and diffusion, and

enable sovereignty. The world needs both

frontier closed models and frontier open

models. I'm so excited that Jensen is a

believer in open source now. Looking

forward to the CUDA and GPU driver open

source release. Oh boy. And then we get

the whole letter open weights and

American AI leadership. This is a direct

call out to the American government to

not do anything stupid because there

have been talks about potentially

banning Chinese openweight models in the

US which is really really bad. In the

1980s, early open-source software

pioneers challenged the prevailing

belief that software would advance only

if companies kept tight control over

their code. This movement pushed for a

transparent ecosystem where developers

around the world could study, modify,

and improve software. Software developed

by the open-source community now

supports most of the internet and

underly systems used by the world's

largest technology companies as well as

the US military and federal agencies

conducting scientific research, cyber

security, and other critical missions.

Open source did more than lower the cost

of software. It created a shared

foundation of knowledge on which

generations of American engineers and

entrepreneurs built their institutional

sovereignty. I say this a lot, open

source is good for pretty much everyone.

It makes it easier for businesses to be

successful and compete. It makes it

easier for nonprofits to have quality of

software that is similar scales to that

of like big wellunded businesses. Open

source is great. It enables a much more

level playing field for everyone who

wants to put in the effort to play. And

I love that. Back to the letter. The US

now faces a similar choice with

artificial intelligence. Our AI

leadership will be judged not by one

frontier AI model, but by whether the US

builds a strong and open ecosystem that

diffuses into every sector. Interesting

use of the word diffuses. that feel

strategic. This is essential for

creating opportunities for innovation

and prosperity across the country. It

requires expanding access to AI,

encouraging competition, robust

application layers, and giving Americans

greater control over the technology that

they rely on. Openweight models, Mdash,

AI models that anyone can download,

inspect, modify, and run on their own

infrastructure, close mdash, are

important parts of the foundation

because they make advanced AI more

accessible, adaptable, and widely

available. There's also an underline

here that's not included, like a hidden

between the lines piece here that

openweight models give more people

reasons to buy our chips. I also do

actually like they put a definition of

open weight so that they don't have to

fight the whole but it's not really open

source because remember Nvidia publishes

actual open source models. They aren't

just publishing the weights that they

created. They're also publishing the

data, the tools they use to train the

models and everything you need to

recreate the model yourself. That is

true open source. I don't think that

matters that much in the world of models

because nobody's going to spend millions

on GPUs to recreate this from scratch

themselves, but you can, which is cool.

But they are not saying we're better cuz

we're real open source. They're saying

all openweight models matter and are

trying to like advocate for that here.

It is kind of ironic that Nvidia

supports open source and openweight AI

as much as they do though because

they've historically been rough to the

open source world.

>> So Nvidia, [ __ ] you.

Yeah, Nvidia has not supported things

like Linux as well as they should have.

Open Weights expanded access to the AI

economy. Startups, established

businesses, universities, and public

institutions can build on advanced

models without training one from scratch

or paying frontier model prices for

every task. Open Weights let every

organization match the right model to

the right job at the right cost,

reserving frontier scale capability for

genuine frontier problems and running

efficient specialized models everywhere

else. I don't necessarily believe this

is where we're actually going to go, but

it is where a lot of businesses are now,

so reasonable to put it in. That

discipline is what will make AI

economically sustainable as its use

scales into the billions of everyday

tasks. America wins the AI era by

diffusing it into the workflows of

factories, hospitals, farms, classrooms,

and mainstream businesses. And the

ability not to send all your data to

anthropic or open AAI is worth calling

out too. Open weights also strengthen

competition and competition is what

keeps the gains of AI broadly shared

rather than concentrated into a few

hands. By allowing many orgs to build,

adapt and deploy advanced models, open

weights create rivalry not only among

model developers but across cloud chips,

applications and services. That

competition spurs innovation, drives

down costs and distributes the benefits

of AI broadly across our economy. Open

weights also give customers greater

control. As orgs invest in AI, they want

to know that they will not become locked

into a single provider or lose the

knowledge and capabilities that they

build over time. Openweight models help

provide that assurance by allowing

organizations to control their own data,

evaluate and adapt models to their own

needs, and deploy them whenever their

business requirements demand. And as

orgs create value with AI, open weights

allow them to own that value through

self-improving models, specialized

capabilities, and accumulated knowledge

that drive American sovereignty and

prosperity. feel like they're using the

word sovereignty a bunch here just to

appease the current admin. And now we

get to the security and safety section.

To be sure, open weights carry real and

distinct risks. Once released, the

weights are beyond the original

developers control and modified versions

are difficult to trace or reverse. I

know a couple people at a couple labs

that have been haunted by this in

particular because normally when you're

at OpenAI or Anthropic, you have a layer

in between the model and the user that

can filter things before the request

goes in or the response goes out, which

makes it a lot easier to protect. Once

the weights are out there, you can't

unrelease the files. People have them.

So if you think that your model is

incapable of doing anything really

really dangerous like manufacturing

nuclear weapons or drugs and then it

turns out somebody found a way to make

it do that, you can't take that back.

You can't remove that capability. The

weights are out. And I know a lot of

people who have struggled with this in

particular, making sure that their

testing is thorough enough that anything

really dangerous isn't possible with the

weights that they release. I also

suspect this is part of the reason why

the open weight releases for recent

models have been delayed. things like K3

taking what was it like a week and a

half from initial availability to the

weights being public. That was because

they wanted to be extra sure that all of

the risks were addressed. At least I

would assume as much. Yeah, as they say

in this letter, that is a real concern.

You need to make sure that these weights

don't have horrible capabilities before

they are released. But the right

response to this risk is not to prohibit

open weights. In a world where cyber

security attackers are using advanced

AI, defenders need access to models with

comparable capabilities so that they can

detect, simulate, and respond to

emerging threats, open models broaden

defensive capability, increase

transparency, and allow vulnerabilities

to be discovered and remediated across

many teams. I used to not super love

this point because I did kind of like

the direction both Anthropic and OpenAI

went with their whitelisted

access programs for the companies

building the foundations we rely on

every day and the open source

maintainers doing the same so that they

could audit things like Windows and Mac

OS and Linux. audit layers we rely on

heavily, things like FFmpeg or OpenSSL,

and find as many of these things as

possible early with unrestricted models

from the major labs, so that when the

more restricted versions come out or

open weight versions come out that the

likelihood that the these things can be

poned goes down because they've been

secured using the same technologies. I

like the idea of early access to these

capabilities going to the maintainers of

the things that we all rely on. But

we're now seeing the weird in between

where things like the OpenAI hugging

face hack occurred where OpenAI

accidentally let GPT6 break out of an

isolated offline sandbox through

multiple exploits. It found get into

another sandbox with internet access and

then route through that to pone external

services like HuggingFace. And then when

HuggingFace tried to use 56 to defend

themselves, they got rejections and

errors from the OpenAI APIs. And the

same with Anthropics when they tried

Fable. So they had to rely on an

internal GLM52 instance that was

unrestricted in order to defend

themselves from GPT6. That's insane.

Like it's happened. We have now crossed

the threshold and the frontier labs are

not providing enough access to enough

people with enough speed to keep

themselves safe. So open weights as a in

between protection method are

effectively necessary now because the

labs move too slow since anthropic and

open AI didn't do enough with this early

access program. We now have to lean on

these open weight models to protect

ourselves from even them which is kind

of crazy. It's almost the thing OpenAI

feared initially which is why I'm

thankful that they're being reasonable

about all of this. They're being

reasonably supportive of openweight

stuff and they even signed this letter.

The letter goes as far as saying that

openness may be one of the most

important paths to AI safety and

security. Relying solely on closed

models is not inherently safe. They can

be breached, misused, or fail in ways

that outsiders cannot detect. Yeah, we

just saw all that. And concentrating

advanced AI capabilities behind a small

number of closed models compounds that

risk. It results in a smaller number of

single points of failure weakens

competition and it leaves critical

technology in the hands of just a few

providers. OpenWeight models on the

other hand allow a broad community of

researchers and developers to examine

their behavior, identify

vulnerabilities, develop safeguards, and

improve them over time. Just as open-

source software demonstrated that

transparency can be more secure than

obscurity, AI safety may depend on

giving more people the ability to test

and strengthen the models on which

society relies. It allows for rigorous

benchmarking and evaluation, red

teaming, and protections tied to real

and demonstrated harms rather than

assuming that closed systems are safer

by default. A strong AI ecosystem is not

a foregone conclusion. Policymakers have

an important opportunity to act. This

includes expanding access to compute for

startups and researchers, investing in

shared training assets like data sets,

tools, evaluation frameworks, and more,

and keeping the frontier plural by

avoiding premature restrictions on open

models that stifle competition or drive

innovation overseas. These measures must

also look at how strong application

layers can expand sovereign use of AI

across the economy. I do have to call

out that this section feels kind of

written to boost their sales because if

you get the government to expand access

to compute for startups and researchers,

they are getting the government to pay

Nvidia for chips. If they invest in

shared training assets like data sets,

tools, and eval frameworks, more people

are training models. And if they're

training models, they're probably doing

it on Nvidia. So, they're selling more

as well. And if they prevent the

restriction of openweight models, there

are more companies that are trying to

host these models that need NVIDIA

chips. All of this is we want to sell

more chips, but it is for the better of

the technology. In shaping this

ecosystem, policy makers should be

careful not to conflate legitimate model

development techniques with

misappropriation. Distillation or the

practice of using one model's output to

help train or improve others is a widely

used technique for model improvement,

eval, and validation. It reflects a long

tradition of learning from, building

upon, and improving existing

technologies. a tradition that has

helped drive innovation since the rise

of the open-source software movement. By

contrast, unlawful efforts to extract

value from closed models raise

legitimate concerns. Those concerns

should be addressed through targeted

legal and commercial frameworks rather

than sweeping restrictions on techniques

that play an important role in AI

innovation. This whole paragraph here is

a very kindly worded middle finger to

the policy makers and government

officials that have been saying stupid

things about banning openweight models

because they're from China. This is them

saying, "You're using that word

distillation wrong. It's actually okay.

Stop freaking out about this." And I'm

happy they did that. The age of AI can

be one of prosperity. With the right

choices, openweight AI can expand

opportunity, strengthen competition,

extend American technological

leadership, mitigate risk, and ensure

that the benefits of this technology are

shared broadly across our economy. That

future is worth building, and the United

States should lead in building it. Yep,

this last sentence I totally agree with.

My American pride will show a bit here,

but I do think we are the best home for

AI. At least we should be now that we

have these weird restrictions coming

from the government and that is being

combined with a potential

anti-openweight policy. I would not be

surprised if we see people starting to

move somewhere like I don't know Canada.

America should be the place where this

all happens. And it seems like a lot of

companies agree and are petitioning to

get the government to do the right thing

here. Again, including OpenAI who signed

this. So, let's see how the [ __ ]

Anthropic chose to defend themselves.

Oh, wait. This is Microsoft publishing

the same letter.

Yeah, Microsoft themselves put the

letter on their own website to make sure

it was very clear by putting on the

Microsoft corporate responsibility site

that this is their beliefs. So, let's

see how Daario spins this one. Our

position on open weights models. For

what it is worth, there have been rumors

at Anthropic that doing so much as

mentioning openweight models in a

positive light in your interviews could

meaningfully affect the likelihood you

were hired, which is crazy. I don't know

how true those are cuz I don't have

direct like first party accounts, but

I've heard enough times that it would

not surprise me. Over the last few days,

there's been a lot of discussion about

openweight models, especially those from

China. Reports suggest that some US

officials are considering banning the

use of Chinese openweight models by US

companies. In response, many tech

companies have signed a letter

supporting openweight models. And some

people have even accused Anthropic of

wanting to ban openweight models as a

means of protecting our business. I

don't think you're necessarily doing it

just to protect your business. I think

you just have weird beliefs. But go off,

king. Anyone who has read my past

writing should know that I don't regard

such bans as useful measures. But let me

state it clearly so that there is no

doubt. Enthropic has never advocated for

a ban on openweight models. Okay, so why

haven't you signed openweight models

that don't have dangerous capabilities

are a public good? Oh, there we go. You

don't want good openweight models in

propic. They don't cost anything beside

the compute needed to run them, and they

provide values to businesses,

developers, and researchers.

Protectionist bands would not address

Daario's most serious national security

concerns. Specifically, he's worried

about two nightmare scenarios. He laid

them out in his essay, The Adolescence

of Technology, 6 months ago. He's held

these positions consistently for many

years. Scenario one is that his concern

is the risk that authoritarian

governments, not solely the Chinese

Communist Party, although the CCP is

clearly the most capable threat. He's

concerned that they are building AI

models that are more powerful than those

built by the US, and that they can use

them to achieve permanent military

superiority or to perpetuate incredibly

deep repressions of their own people.

Concern is widely shared within the US

government. Vice President Vance warned

in Paris last year that authoritarian

regimes have stolen and used AI to

strengthen their military intelligence

and surveillance capabilities. And the

intelligence community's 2026 annual

threat assessment found that quote other

global powers robust progress in AI is

challenging US economic competitiveness

and national security advantages. End

quote. It is irrelevant whether these

models are released with open weights

and certainly irrelevant whether they

are used by US businesses. In fact, the

most dangerous model may be one that is

trained in secret and handed only to the

People's Liberation Army for use in

drones in the Ministry of State

Securities for surveillance and

repression. This is fair. I don't think

this will happen simply because like

it's so expensive to create these models

and they have so much value outside of

like private military use that that

won't happen. But I get why you're

concerned. It is hard for me to validate

those concerns though because your

complaint isn't about openweight models

or these evil companies or these evil

countries leapfrogging. Your biggest

complaint is distillation. You're not

mad that they can get ahead. You're mad

that they're catching up because you

pulled the ladder up behind you.

Anyways, let's hear the second concern.

Dario's secondary concern is the risk

that powerful AI models may be misused

to carry out cyber attacks or biological

attacks and that may have serious

alignment problems. And I love that he

specifically links the OpenAI hugging

face article from Time about this, not

the official OpenAI coms. He links to

the time article here that is strategic.

That is a dig at his previous employer.

Open weights models. There god there's

how many M dashes are on this page? 38 M

dashes. Okay, it's counting the non-M

dash ones in open weights, but that's

only 14 of them. Cool. So, that means

there are 24 m dashes on this page.

That's great. Anyways, maybe Daario is

the reason that models like Mdash so

much. Also, I hate the formatting here.

Open weights models, it does not matter

whether they come from China or anywhere

else, do potentially present a higher

risk than closed models because it's

very difficult to apply guard rails to

them or monitor their usage. And once

the weights are released, they cannot be

withdrawn. Banning the use of these

models by US businesses does nothing to

address this risk because bad actors are

unlikely to be legitimate US businesses.

It would protect US AI companies from

competition, but that has never been his

goal. Okay, he called it out directly

here. For what it is worth, I don't

actually think Daario is scared of

openweight models taking away his

business or their success. I think he is

scared of people having access to good

AI if it's not through Anthropic servers

because he's genuinely so convinced he

is the only one and his company's the

only one doing it right and safe. We

might end up in a weird position where

Anthropic gets really close with the US

admin and OpenAI slowly gets pushed out.

I know Sam is currently in DC doing

something so we'll see where that all

goes. Here are the measures that Dario

does support and he has continued to

advocate for throughout his time at

Anthropic. First, he says that we should

not sell powerful chips or chipmaking

equipment to China. And we also have to

crack down on the smuggling that has

been going on. Links to a justice.gov

site, the Office of Public Affairs,

where there are people who are being

charged, just three random individuals

trying to divert high performance

computer servers assembled in the US

integrating sophisticated US AI

technology to China. One was a US

citizen, one was a Taiwanese citizen.

Third person is still a fugitive,

possibly at large. Interesting. Kind of

crazy to link an article from March from

the US government about three random

people trying to sneak GPUs out of the

US, but sure. China has limited domestic

production capacity and therefore due to

the scaling laws cannot build more

powerful models in the US without US

chips. US chips that are manufactured at

TSMC, by the way. Anyways, his next

policy belief is that we should crack

down on industrial scale distillation

operations. Distillation is a much more

compute efficient process than training

models from scratch. crazy because you

just did a big distillation pass on opus

and didn't seem to work too great. It

allows China to build much better models

than its number of chips would

ordinarily enable and thus partially

evade chip bands. Distillation does not

allow the CCB to obtain equivalent or

superior AI capabilities to the US, but

it can bring the Chinese frontier to

within a few months of the US frontier.

Yeah, and I think that's totally

reasonable and fine. It is true that

many of the companies carrying out these

distillation operations release

openweight models, but the open weights

are far less relevant than the fact that

the operations are backed by an

authoritarian state seeking to overtake

the US at the frontier. We should have

policy interventions to deter this

behavior. A blanket ban on openweight

models is neither the correct remedy nor

something that we have called for. Okay,

so again, he is mad that they don't get

to be the exclusive distillers of what

they have built with Fable. On that

note, I would highly recommend that

everybody listening right now turn on

permanent logging inside of their cloud

code, codecs, cursor, and everything

else and store all of those logs. If you

use something like CLI proxy API, which

I rely on heavily for all of my routing

for cloud models, you can set up a flag

in it to store all of the logs of every

request that comes in and out. So, if

you hypothetically wanted to refine an

open weight model to act more like Fable

the way you used it, you can. And in a

world where Enthropic is doing

everything they can to lock this data

down and prevent others from having it,

you should do your best to keep your own

because this might end up being much

more important in the future with the

direction things are going. His third

request is that all sufficiently capable

models, whether they're open or closed,

should go through mandatory safety

testing. The best way to address the

threats he is concerned about is to just

directly test the models for cyber,

biological, and alignment risks before

release. This idea is pretty close to a

consensus. He's been heartened both that

the Trump admin has moved in this

direction in recent months and by recent

industry proposals that would apply such

testing to the most capable models

regardless of their country of origin

whether they are open or closed while

exempting less capable models such as

those from startups in academia

entirely. Also a good call out. No

academic model with limited compute is

going to be a real risk. Whether open

models do or don't pose an increased

risk and whether the risk can be

mitigated is something that should

emerge from testing rather than be

decided in advance. And there may be

promising methods for improving the

safety of open weights models, including

recent research from AE Studio and

Enthropic on modular training

strategies. Note that to be effective,

testing would need to be global, which

means even the CCP would need to be on

board. We'll talk about this in a

follow-up video, too, because there's

another letter that went out recently

that has a lot of anthropic employees,

open eye employees, and deepse employees

that all signed it. Now, Dario directly

addresses the letter we read before. He

claims he agrees with much of it. Open

weights expand access to the AI economy.

They strengthen competition at least for

some use cases and they give customers

greater control. Remember they weren't

first, second, or even third place for

doing reasoning. So it's funny because

they advanced meaningfully thanks to the

work of one of these openweight labs in

China and now is saying that for at

least some use cases that they are

useful. Come on, man. Concerns about

distillation should be addressed through

targeted legal and commercial

frameworks, the same measures he

described above. But he doesn't agree

with the letter's assertions that open

weight models necessarily make it easier

to develop safeguards or that broad

access to capabilities necessarily help

defenders more than attackers. It seems

at least as likely to him that the

opposite will be true. For example, he

worries that biology will have a strong

attacker defender asymmetry where

sufficiently capable models may be able

to quickly weaponize a pandemic level

virus with widely available materials.

Whereas defense against these agents is

a multi-year operational task in the

best case. Yeah, if they can make

viruses faster than they can cure them,

that would be really bad. He says that

questions like this should be

empirically answered by rigorous

pre-release testing not assumed in

advance. To summarize Dario and

Enthropic's position, they have not and

are not advocating for a ban on

openweight models as a category. They

should instead focus on keeping powerful

chips out of authoritarian hands,

stopping industrial scale distillation,

and requiring safety testing of all

sufficiently capable models, open and

closed.

Come on. It's it's it's this last

sentence is just so weird to read, man.

It's like to analogize the sentence and

how cringe it comes off to people who

get what's going on. Developers should

focus on making sure their applications

are accessible, that all users of Apple

computers are banned, and that their

programs work when they're opened. One

of those things is net positive for

sure. One of those things is obvious,

like, yes, we should all agree on this.

And one of those things stuck in the

middle there and is really, really

[ __ ] stupid. They need to just get

over this industrial scale distillation

attack language. It's like the Y2K of

the AI era. It just makes them look

stupid. Is it a real problem? Perhaps

some amount. But they've already done so

much to reduce it. And the labs are

still not just like catching up, but

exceeding in some places. The fact that

K3 could come out so close to Fable 5

and beat it in many ways shows that

these distillation attacks are not what

is driving this success. It just makes

them look petty and selfish to sneak

that in here. If they had just ended

this by saying we need to keep powerful

chips out of authoritarian hands and

make sure that all models are tested

properly whether or not they're open,

that's a great ending. Sneaking in this

[ __ ] distillation call out in the

middle is so goddamn cringe. And whether

or not they admit this here, that is the

real thing they hate about this article.

the second to last paragraph here that

calls out that distillation is a

legitimate practice that is widely used

for improving models and that it's

reflecting a long tradition of learning

from building upon and improving

existing technologies.

This is yeah like this is totally

reasonable and anthropic is just making

themselves look stupid by acting

otherwise. If you're looking for the

right moments to actually be scared of

anthropic, the moment to know anthropics

really changed and should be looked at

differently is if a new openweight model

drops and is really good and is

universally seen as really good and no

official anthropic comm's channel

mentions the word distillation for at

least 2 weeks. The moment that happens,

the moment Anthropic will shut the [ __ ]

up about distillation, that's when you

know real change is happening at that

company. And until then, they are a cult

with a really powerful model. And I'm

saying this as somebody who's currently

running four $200 tier accounts because

I love Fable so much. I like the model,

but I'm also realistic about the lab and

what they do and what they do well and

what they do poorly. And I hope that

this helps you guys understand all of

the sides here and come to your own

conclusions. Are you going to be on the

side that the vast majority of

businesses that the vast majority of

people in the AI world and even Nvidia,

who I don't necessarily love, are on?

Are you going to side with Anthropic

because they really hate the concept of

distillation being done by companies

that are not themselves? I may have led

you guys to a specific conclusion here,

but it's your decision if you make that

conclusion or if you go against it.

Curious how y'all feel. Leave some

comments letting me know how you feel

about open weight models, the

government's involvement, and

Anthropic's weird stance here. And until

next time, peace nerds.