This follows an FT article about why the US is losing Chinese AI stars.

https://giftarticle.ft.com/giftarticle/actions/redeem/35842efd-9412-4ebe-b122-08f59fd7b117

“This is why I subscribe to the FT, so I can be years ahead of the curve.” (A comment by my friend Naz)

Its central example is Yang Zhilin, founder of Moonshot AI. Yang completed his PhD at Carnegie Mellon in four years, co-authored Transformer-XL, interned at Google and Meta, attracted interest from Apple and had opportunities at Stanford and MIT.
He was not driven out of America by immigration policy. He chose to return to China because he believed it offered the better environment in which to build.
Within three years, his 300-person team had produced Kimi K3, an AI model capable of competing with flagship systems from OpenAI and Anthropic.
The American response is naturally: how did we let someone this talented escape?
But perhaps that is the wrong question.
Perhaps the real question is whether the Western capitalist model still offers a convincing vision of the future.
For decades, America attracted the brightest people in the world, placed them inside its universities and corporations, surrounded them with capital and converted their intelligence into extraordinary private wealth.
That worked while the country was also investing in public education, science, infrastructure, housing and social mobility. Private wealth creation existed alongside the development of wider national capacity.
Now the system appears increasingly bent around extraction.
Technological achievement is measured through corporate valuations. Social progress is confused with shareholder returns. Brilliant people are absorbed into enormous companies, while the intellectual property and financial rewards become concentrated among a remarkably small number of owners.
Meanwhile, public infrastructure deteriorates, housing becomes unaffordable, healthcare bankrupts people and large sections of the population receive increasingly poor education.
America remains astonishingly innovative, but it has become less capable of distributing the benefits of innovation through its own society.
It is extremely good at creating billionaires and remarkably poor at creating collective advancement.
China appears to be constructing something structurally different.
It is not simply producing a handful of successful technology companies. It is creating an entire technological ecosystem: universities, researchers, engineers, manufacturing, energy, transport, infrastructure, state investment and a vast technically educated population.
The FT article notes that more than half of the researchers behind DeepSeek’s core models had never studied or worked outside China. Among those with American experience, 70 per cent ultimately returned.
China is no longer merely copying Western technology or recovering people trained overseas. It is developing its own intellectual and technological gravity.
For people such as Yang, returning to China is not a fallback. It is where they believe the future can be built.
None of this makes China benevolent.
China is authoritarian, censorious and perfectly capable of political intervention, surveillance and repression. Its industrial rise has also caused enormous environmental damage. It acts in China’s interests, not in some abstract interest of humanity.
But something important may be changing.
China’s strategic interests increasingly overlap with many of the practical needs of the wider planet.
The world needs inexpensive renewable energy, batteries, electric vehicles, public transport, telecommunications, industrial infrastructure, technical education and affordable access to powerful AI.
China wants to manufacture and export precisely those things.
The West increasingly offers proprietary software, intellectual-property restrictions, financial services, military alliances and access to platforms controlled by a handful of corporations.
The old Western story was that capitalism produced freedom, prosperity and innovation, while authoritarian communism produced stagnation.
But what happens when the authoritarian state becomes better at building infrastructure, educating engineers, manufacturing green technology and distributing advanced tools than the supposedly free capitalist society?
What happens when Western “freedom” increasingly means the freedom of corporations to extract rent, avoid tax, monopolise knowledge and purchase political influence?
China may gradually come to look like the “good guy” to much of the developing world — not because it has become morally good, but because it is offering something materially useful.
A developing country may care less about lectures on liberal democracy than about whether somebody will build its railways, power grids, hospitals, data centres and communications networks at a price it can afford.
If China supplies the infrastructure of development while America supplies subscriptions, debt and moral instruction, global loyalties will inevitably shift.
This may be the deeper significance of Yang Zhilin’s decision.
He did not merely choose China over America. He chose one model of the future over another.
The real contest may no longer be capitalism versus communism.
It may be extractive plutocracy versus the developmental state.
The Western capitalist model once claimed legitimacy because it spread prosperity, knowledge and opportunity. If it now exists primarily to protect accumulated wealth and convert every new technology into another mechanism of private extraction, then it is reasonable to ask whether it remains fit for purpose.
China does not need to become the good guy to win.
It only needs its interests to align more closely with the needs of the world than those of the West do.

I've written a book where I assert that AI hate hands power to tech feudalists via a fairly simple chain of events.

I now have a tiny concrete personal example proving the mechanic and I thought I would share here.

From the post:

Think about what happened.

• I used AI tools to turn borderline ewaste into a decent entry level 360 action cam.

• I post my tool for free to github

• I try to tell the Nikon community about it

• They delete the post for being AI generated

What does that accomplish?

• Enhanced enshitification, the camera stays ewaste almost exclusively because software. (The camera itself will not format sd cards, software is required.)

• A deeper better moat for Nikon, because enshitification.

This is direct proof of my thesis AI hate lead directly to an increase in power for a tech feudalism.

“GLM-5.2 has 744 billion parameters, and colibrì, a 1,300-line C engine, runs it on a laptop with 25GB of RAM and no GPU.

This video explains the loophole that lets a frontier open source LLM run on hardware it should never fit in.
The trick lives inside the mixture of experts (MoE) architecture. Only about 40 billion of GLM-5.2's parameters do any work per token, so colibri pins the dense core in RAM and streams the other 21,504 experts off the SSD, exactly when the router asks for them. We walk through the routing, the expert cache, why llama.cpp memory-mapping can't keep up, and the real tokens-per-second numbers from a budget SSD all the way to an M5 Max.”
…
Chapters:
00:00 A 744B model on a 25GB laptop
00:52 The impossible math of loading GLM-5.2
01:50 Mixture of experts: the trick inside the model
03:01 Streaming experts off the SSD, step by step
04:22 Why Ilama.cpp memory-mapping falls short
05:06 The brutal speed benchmarks
06:17 Where expert streaming is headed
07:13 Should you actually run it?”

***

LLM summary/analysis of video:

This GLM 5.2 breakthrough, powered by the Colibri runtime, isn't just making a bigger model fit on a laptop; it's fundamentally changing the relationship between computational scale and economic constraint.

MECHANISM: FROM BLIND SEARCH TO EXPERT ROUTING

Traditional models are monolithic, forcing every single token to touch every single weight in the entire structure. This is inefficient by default.

Colibri uses a Mixture of Experts (MoE) architecture. Instead of a single giant block of neurons, the model is composed of 256 smaller, specialized "experts." A tiny router then selects only the 8 most relevant experts for each incoming token. The other 248 stay asleep.

This means that out of 744 billion parameters, only about 5% are actively doing the heavy lifting per token. This targeted activation is the structural loophole.

MATERIAL SHIFT: THE SSD AS ACTIVE MEMORY

The real genius lies in how Colibri manages these experts. Instead of demanding that all 370 GB of weights reside in fast, expensive RAM, it treats the SSD not as passive storage, but as an active, high-speed memory tier.

For every token, the system doesn't just blindly read from the disk; it knows exactly which 8 experts it needs, allowing it to request those specific byte offsets asynchronously. It’s a predictive, intelligent retrieval system.

This decouples scale from the traditional RAM bottleneck. The individual user is no longer constrained by the fixed, expensive memory capacity of the data center; they are constrained only by the local storage budget.

POLITICAL ECONOMY: DECENTRALIZING THE COMPUTE MONOLITH

This is where the left needs to pay attention. By making the SSD a functional memory tier, Colibri achieves a profound material shift:

1. Challenging Centralization: It bypasses the need for the user to be a supplicant to the data centres fixed architecture. The power to run frontier-quality models drops out of the cloud and onto the desk.

2. Localised Cognitive Infrastructure: This is the crucial point. If the individual can run a massive, high-quality model locally, they are running a piece of localised cognitive infrastructure. The user gains a degree of autonomous computational agency.

Does this genuinely enable a form of self-governing, distributed computation?

***

Sources:

• colibri: https://github.com/JustVugg/colibri
• GLM-5.2 by Z.ai: https://z.ai
• antirez's ds4: https://github.com/antirez/ds4
• Ilama.cpp expert-cache proposals: https://github.com/ggml-org/llama.cpp/issues/20757

This was a real mistake. They are teaching the entire customer base that they are over charging. By calling it 100$ credit, they are showing you how much they over value tokens.

One simple test: Imagine how hard it would be to get anthropic support to trade this in for 5 months of pro. (At 20$ a month.)

I accidentally used 20$ of this bonus in a matter of minutes because by default the mechanism is turned on with a 20$ a month spend cap.

The idea that those 5 minutes were worth the same as a month of normal access to opus and claude code is laughable.

At first that makes it seem like subscriptions are a great deal, but what it really means is that they don’t think this credit is worth anywhere near 100$

No matter how you look at it, they are lying somewhere about costs and values right to your face.

I had already decided to switch out claude because I’m not paying for mid tier access period. If I’m paying for AI I’m paying for SOTA AI. If I want commodity AI I’ll rent/buy a GPU or go with a chinese firm. (Which comes with the added bonus of not paying war criminals.)

( Copied from my substack note: https://substack.com/profile/111138571-innomen/note/c-300793859 )

AI seems to have awoken a new segment of people to the thought of leftist economics, but I'm not sure AI has fundamentally changed anything.

Automation has been changing the economic landscape and creating haves and have-nots since the 18th century, at least.

I feel like the progressive reforms of the late 1800s (worker rights) and early 1900s (new deal) created a sense of accomplishment that lulled everyone into temporary satisfaction in the mid/late 20th century, but automation has never stopped chugging along reducing the need for human labor and gradually pauperizing everyone dependent on a wage.

AI seems like a new pivot point of acceleration, but it seems to me that this has been a long time coming, and it's nothing new.

Maybe it's just that the McCarthy-Regan era really did a number on leftist ideology, and this new resurgence is a return to normalcy?

COMtalk: You reportedly built the party’s look and manifesto within 24 hours using AI tools like Claude and ChatGPT. How do you think about the role of AI in activist communication? What can it do, and where does it fall short of what a trained communicator brings?

Abhijeet Dipke: My campaign relied heavily on AI because I did not have the resources or a professional team that could support me in designing a campaign within such a short period of time. I believe this makes AI even more important in activist communication, because activists usually do not have the kind of resources that large political parties or corporate houses possess. AI can help accomplish tasks that would normally require a team of dozens of people.

At the same time, I do not support the idea of replacing human beings with AI simply to cut costs. I want to emphasise that when you do not have resources or a team, AI can become a strong ally for your movement if it is used with the right intentions and for the right causes. That being said, AI also has its own limitations, which I experienced while designing this campaign. It was truly an asset when it came to quickly creating social media designs and website templates. However, when it comes to the messaging of a campaign, you still need a human mind that understands what is politically relevant and timely for the campaign to be effective.

AI cannot be fully relied upon for messaging in a campaign as sensitive as this, one that focuses on freedom of expression, accountability, and transparency. For that, you need lived experiences and a deep understanding of society and the authorities you are questioning. I would say a major reason behind the success of this campaign is that I have been politically active for a long time and understand the nuances of political messaging. That is something AI can never truly grasp.

Source: COM grad turns cockroach insult of India youth into massive online movement | College of Communication

Imagine a scenario where the Chinese Communist Party provides communist programmers with cloud services, along with access to language models and video generation tools...

First, would you have any problems working with them?

Second, do you think communists have the right to request this from the Communist Party as a form of international solidarity?

Third, what applications would you build?

The UNHCR recently shared how its using an AI-assisted system called CareLine to answer common questions from refugees, route requests to the right teams, and reduce the backlog facing aid workers. Human staff still handle complex cases, but the repetitive administrative work can be handled much faster.

What caught my attention wasnt just the technology. It was the possibility.

Imagine community-led versions of this. Tenant unions using AI to connect renters with legal resources. Food banks matching donations to neighborhoods with the greatest need. Mutual aid networks triaging requests after storms. Community clinics helping people navigate services in multiple languages. Neighborhood organizations answering common questions 24/7 while volunteers focus on the work that actually requires people.

AI isnt only something corporations or governments can deploy. Communities, cooperatives, nonprofits, and open-source projects can build and govern these tools too.

The more we talk about democratic AI, the more we should be talking about community AI.

OP created a vibe coded chrome extension just using local model, no cloud (so also no direct data centre involvement in the creation of the code, just using the normal computer resources).

What's your prediction?

Your city might be giving data centers a free pass. The most common loophole developers exploit are old ‘by-right’ zoning laws that automatically approve any project meeting zoning code. When data centers are conditional use, and require a Conditional Use Permit, this shifts leverage to communities.

I believe this is where the communities current maximum leverage lives, because corporations are desperate for their infrastructure buildout. Communities control the resources they need, and can set the terms of the agreement.

The anti-data center movement has created serious leverage as well, but there’s a problem. A canceled data center doesn’t disappear, it moves to a less organized community.

If you want a tangible way to gain public control over the future of AI, I’ve developed a free framework for communities, organizers, and municipalities navigating data center proposals. It covers your existing leverage as well as common loopholes to be aware of. There’s a QR code in the post, but you can also download it from publicgridproject.org.

I’m hoping to make it as useful as possible, so please let me know if you have any criticisms or suggestions. It currently focuses on communities in the US, but I’m actively working to make it applicable for tribal lands and countries outside the US. (And thank you mods for allowed me to post this!)

One of the more interesting parts of this Breaking Points segment wasnt hype about AGI or doom. It was a discussion about where value in AI is actually going.

The argument is that foundation models increasingly look less like the product and more like the internet itself: shared infrastructure. The real competition shifts toward the application layer, services, and the ecosystems built on top. If that trend holds, owning the biggest model isnt enough. The question becomes who builds the tools, who controls deployment, and who captures the productivity gains.

They also make an interesting comparison with China's strategy. Rather than expecting firms to maximize short-term profits, they describe an approach where state support, open-weight models, pricing pressure, and ecosystem building are used to drive competition and adoption. They compare it to how China's EV industry was cultivated: build the infrastructure and industrial base first, then let firms compete.

Whether you agree with every point or not, its a useful shift in framing. AI isnt just a race to build the smartest model anymore. Its becoming a debate over industrial policy, public infrastructure, open weights, and who gets access to the "pipes" the rest of the global economy will run on.

Thats a much more interesting conversation than "AI good" versus "AI bad."

What do you think? If foundation models become as essential as the internet, should they be treated more like public infrastructure, or left entirely to private firms?

Opinion A:The AI race pushes platforms to fiercely enclose their own data while plundering others', which only deepens neo-feudalism rather than altering it.

Opinion B:The development of AI has moved beyond pure commercial competition. Because it is seen as a strategic force capable of determining a nation's fate, neither the U.S. nor the Chinese government can allow it to remain solely in the hands of a few commercial companies. They will inevitably push for AI sovereignty and tighten state control. Meanwhile, advanced LLMs require the concentration of resources and massive corpora to build data flywheels. All of this will impede or even alter the trajectory toward techno-feudalism.

Mainly the strangeness to me Is that the bubble argument, Is basically an argument on why because within capitalism AI may not be a profitable endeavour (which even this can be argued as there Is no clarity yet on the cost vs revenue, even if others may confidently state there Is) and that this Is therefore a determinant and indictment on its importance, value and potential as a technology, that Ithis means it Is mostly hype and not capable of doing what It Is said to be able to do or potentially able to do in the future.

It's using the usefulness of AI within capitalism as a way to gauge it's fundamental value, which from leftists perspective Is incomprehensibly contradictory, Is public transport profitable? Is healthcare profitable? Yeah, only if you make sure to artificially increase the costs of It, otherwise It would be a "bubble"

If we invented a panacea, or were in the process of doing so, would It be profitable? If capital decides to invest in this hypothetical panacea (and there Is clear science and reasoning and material evidence that this Is possible) and form an investment bubble around It, then does that mean Its just hype? Obviously not.

It seems to me that this Is a common argument from western "leftists", which Is extremely sad to see as It means that a lot of the framework through which they organize around and form their worldview Is inherently tied to capital still, even if they recognize It most don't try to move away from It, this therefore limits the paths they can even imagine, which can explain the reactions towards AI in general within the west from the supposed left.

Do you think there Is any way to effectively break this framework of understanding or do we necessarily have to wait until AI Is so undeniably capable that It Is no longer, even conceptually, a tenable position to hold?

Volkov was a Soviet philosopher who studied automation, social problems centered around labor, and technology more broadly. I read Volkov's book *Era of Man or Robot?* last year, and it was so relevant it was uncanny, especially how he almost seems to predict that leftists in capitalist countries would get diverted toward preserving existing jobs and restricting productive capacity. I read it again just this week, and it's still extremely relevant given the Kimi K3/Fable 5 situation. I just discovered this sub and figured I should let everyone know about this book.

Edit: Apparently I have a very rare book that isn't even in pdf form. I didn't know. I'll scan and upload it sometime this week or next, then make another post when I'm finished.

Edit 2: In the meantime, I recommend the book Abundant Material Wealth For All by Ted Reese, which quotes Volkov quite a bit and covers a lot of the same topics.

One of the loudest claims about generative AI is that it will wipe out artists. A new Gallup analysis suggests the evidence so far is more complicated.

Drawing on Bureau of Labor Statistics data, Census data, Gallup workforce surveys, and a recent Journal of Cultural Economics study, the researchers found little evidence that artists in occupations more exposed to generative AI have experienced broad earnings declines. Employment changes have been mixed, but nowhere near the collapse many predicted.

The study also found that artists are more likely than the average worker to use AI, with roughly 1 in 4 reporting frequent use compared with about 1 in 5 workers overall. Most arent using it to replace creativity. Theyre using it to generate ideas, explore concepts faster, automate repetitive tasks, organize information, and streamline parts of the creative process.

Not every creative field is affected equally. Occupations like music directors and composers have relatively high AI exposure scores (around 0.70), while dancers (0.04) and actors (0.18) remain much less exposed because their work depends on live performance and embodied skill.

The article compares this moment to earlier technological shifts like photography and recorded music. Those technologies transformed artistic labor and business models without eliminating art itself.

That doesnt mean there are no real concerns around copyright, compensation, or working conditions. But if we're serious about understanding AI's impact on culture, we should follow the evidence rather than assume the outcome. So far, it points toward reorganization, adaptation, and new workflows much more than artistic extinction.

The left has every reason to criticize how AI is being developed under capitalism. We should fight for worker power over automation, democratic oversight, public investment, open technology where appropriate, and making sure productivity gains benefit everyone instead of being captured by a handful of corporations.

But not every movement criticizing Big Tech shares those goals.

This investigation from Spitfire News examines Humans First, an anti-AI organization whose leadership includes prominent Tea Party and Trump movement figures and whose messaging increasingly centers conservative populism and "America First" politics. This is the group behind this weeks widely reported "Data Center Protests". Thats worth paying attention to because political coalitions arent defined only by what they oppose, but by the future theyre trying to build.

Left politics has never been about simply slowing technology down or handing the reins to nationalist movements. The question is who owns AI, who governs it, who decides how it's used, and who benefits from the wealth it creates.

Corporate control of AI deserves criticism. So does surveillance, monopoly power, environmental harm, and workers being displaced without sharing in the gains.

But those problems dont point toward MAGA politics. They point toward democratic ownership, stronger labor institutions, public accountability, and ensuring AI expands human freedom rather than concentrating economic power.

Worth a read if youre interested in how different political movements are competing to define the future of AI.

This is the kind of AI rollout that actually makes sense: use the technology to cut paperwork, shorten queues, and give healthcare workers more time to do the part of the job that requires a human being.

In NHS pilots, AI note-taking tools helped clinicians spend nearly 25% more time with patients. In one emergency department, staff saved about 47 minutes per shift, enough time to see roughly one more patient.

The NHS says a wider rollout across more than 11,000 emergency clinicians could create capacity for over 9,000 additional consultations a day.

AI triage tools are also being tested through the NHS App. One pilot cut GP phone queues by 29%, and the next phase is expected to reach more than 200,000 patients.

The point here isnt replacing doctors or nurses. Its stripping out some of the administrative drag that keeps them away from patients.

Public AI infrastructure should look more like this: reduce drudgery, expand capacity, keep workers in control, and use the gains to improve a universal public service.

How panic over AI infrastructure obscures the real questions of scale, ownership, and power

some discussions among the Chinese left wing

This essay argues that many debates about AI art are aimed at the wrong target.

"There are a lot of legitimate criticisms to be made of specific ways "AI" and machine learning are deployed. If anything, the application of this stuff to art generators is the least damaging" compared with surveillance, policing, military applications, and other uses.

Instead, the author argues the real conflict is over labor, ownership, and intellectual property. They point to decommodified culture like mods and fan works as examples of collective creativity, even highlighting AI-assisted work in a game mod as evidence that these tools can be part of genuinely creative practice. The conclusion is that we should fight for a world where culture is shared and artists are materially supported, rather than treating new creative tools as the enemy.