Gary, I thought you might be interested in how fusion has in some respects failed in the same way as AI. My father was a professor of plasma physics for 30 years, and his opinion was that, instead of focusing on the tokamak, we still needed much more science to find a better model. In other words, the fusion sector jumped on the first technology that had some kind of return (eg, the ITAR project in France).
The same thing is happening in AI. Instead of trying many different paths, they jumped on one that, while very flawed, yielded some results, and since there was so much money sloshing around and venture capitalists like to hear good stories, the entire industry is wasting trillions on the wrong approach.
And the AI companies think they can use fusion to power their data centers! https://time.com/7328213/nuclear-fusion-energy-ai/. A technology that doesn't exist yet, to power a technology that has no long-term business plan. Great combination!
I'm not convinced that the comparison between fusion energy and LLMs is correct. The Tokamac approach being pursued by the international ITER collaboration is by no means unique, and the fundamental impediment- production of sufficiently strong magnetic fields- eluded researchers until the advent of superconducting magnets. I am not trying to minimize the difficulty of the task. The physics is basically understood. But as yet there is no consensus on what constitutes consciousness or6 thought, and moreover, unlike ML, for which error performance is characterizable, LLMs are fundamentally unpredictable.
Yann LeCun’s world model sounds interesting, and it certainly would fit your fusion analogy. The question is, how long will it take for this model to yield results?
LLMs, while imperfect can be improved with scaffolding even if they don’t have the capacity to achieveAGI.
I feel that LLMs can do useful work, as does Gary, if I understand him correctly. I have successfully used it for coding, and I think it has potential for information retrieval. It's the world-changing proclamations that I don't agree with.
In fact, since fusion has not led to any useful results, as far as I know -- except for scientifically interesting data -- I would have to say that LLMs are ahead of fusion at the moment, although again, I don't see the extreme expense as having been worth it.
I completely agree. I would place this current plateau of AI at the same scale as streaming video in terms of the potential amount of disruption. Still a huge opportunity but not an earth-shattering AGI paradigm shift.
A difference is that fusion projects have continued to evolve, such that net positive energy (a technical measurement, not a commercial possibility, see https://lift.llnl.gov/) has occurred at the Livermore facility. With advances in superconductors, the Commonwealth Fusion project (https://cfs.energy/) is moving at a pace and with a design that is far different and probably ahead of the ITAR. It is unfortunate that the US government is not pushing the development of fusion at anywhere near the pace of China.
The Livermore facility concentrates on simulating nuclear weapons, and they use lasers focused on a nodule (my technical understanding is general). They have tended, historically, to ocassionally announce breakthroughs that weren't really applicable, just a warning. But thanks for the info. It's certainly a field to keep an eye on, it's just that I am very skeptical. It is the quintessential 'we are 15 (or pick your number) years away' technology
Livermore showed that net positive energy is possible. That facility is not a commercial model in any manner. ITAR is a demonstration project, but it is flawed in being big and taking too long to develop. Fission works, yes, but there remains the waste problem and the issue of politics, the perception of danger to the public. We have no consensus on dealing with the nuclear waste. Small fission reactors hold promise, but they are still in development. I focus on fusion because it would likely not have the immediate danger issues (meltdown), although nuclear waste could still be a problem. We clearly have lots of room for more wind/solar/tidal and even some hydro, and with new battery tech, the issue of the sun going down is obviated. However, at regional scale, baseline power demand still benefits from centralized plants, and fusion would be a huge benefit.
There's no real waste problem with fission. Even with the ridiculous current generation of reactors in the US that operate with 3.5 percent U-235 and without any attempts reprocess spent fuel, we're talking about only 2000 tons per year produced by the entire US nuclear industry. (Compare that, for example, to the approximately 300 million tons of municipal solid waste produced every year, and which is far less dense than spent fuel. Or the 70 million tons of coal ash produced, for that matter.)
The only real issue is politics. It might have been reasonable' politically, to oppose water- cooled reactors operating at high pressure. There's no good reason to oppose a fission reactor operating at atmospheric pressure.
The problem is: there is no better model. Any system of atoms sufficiently complex and energetic to produce fusion is also going to have uncontrollable chaotic instabilities (like solar flares in the Sun). So controlled fusion as an energy source is just not happening.
Well frankly toward the end of his life my father felt fusion would never happen. It's worth pursuing, I think, just in case. It would be much better if it was based on deuterium, fwiw, which is very clean and very cheap, unlike tritium, which is being used now. But we just don't know how to control it at this point, as far as I can tell
How do we know enough about the Strong Force to prove this? I don't think we know enough about the Strong Force to say this for sure, or how we would even go about formalizing a theory for why there isn't a non-trivial range of ways to do so. Edit: especially given our uncertainty about the interactions between the Electroweak Force and the Strong Force at high temperature and density.
The strong force is not relevant to the instabilities, it's the magnetohydrodynamics of the plasma. But even if the strong force was relevant, complex many-body systems without exponentially growing unstable modes essentially do not exist except as ideallized mathematical models.
What would be even the kernel of a theory that could formalize a description that such stable many-bodied systems can never exist from now until the end of the universe? I don't doubt that there is a chance your point of view is the case. But I don't share your level of confidence which seems absolute.
You also seem very confident that the Strong Force doesn't have anything to do with the justification for why many-bodied systems of atoms cannot have some kind of stable manageable transition modes for a time-bounded period. I especially don't share your confidence here: https://www.sciencenews.org/article/nuclear-fusion-alpha-particles-reactor
I think the pundits in the West simply haven't got it when it comes to understanding how China has integrated the 1st, 2nd and 3rd Industrial revolutions. Whereas Western capitalism simply jettisoned the 1st and 2nd industrial revolutions largely through financialisation/export of production, driven by short-term profit goals, the 'secret' to China's success has been to possess the entire spectrum of the production process, of which AI is the culmination. After all, it's ALL ABOUT ECONOMICS! What's more, automation isn't leading to unemployment in China (AI is automation by another name), far from it, AI when applied humanely, opens up the possibility of upskilling, of transforming the relationship between labour and production, this is what socialism is all about.. Thus the CCP just passed a law making it illegal for AI to create redundancies. Two different worlds.
It’s not just an admirable goal, it is a choice. I’m not a big fan of CCP, but they do get some of their economics right in that they have a set of values that come first and then efficiency etc come next. They seem to recognize what the purpose of the economy is - to provision their society- and they have harnessed markets and private ownership (capitalism) to achieve that when it works best and state ownership when it doesn’t. They have screwed up their property markets, but have done well with renewables and EVs. I’m not an expert on china, but I do know my economics. This whole US AI debacle has been created by shortsighted greedy ah who want to replace the labor force they don’t want to pay for. It’s the dumbest purpose for technology. Now that doesn’t mean that AI is dumb, it is that the current companies developing it are well ah.
If it isn't automation leading to unemployment something else is
"Thus the CCP just passed a law making it illegal for AI to create redundancies"
And the PRC is a law-abiding society where no large company executive would pay bribes to enforcement officials, right? I mean that never ever happens...
I couldn’t agree with your closing thought more. I am excited about how Seed IQ’s active inference based AI agents acted as a control layer and created stability on IBM’s NISQ hardware. If Quantum leaps ahead we might not need all the data center compute.
Gary — I think this is the right diagnosis wearing the wrong frame. "Brute force, unreliable, easily replicated" reads like an indictment of the paradigm, but it's really a description of what happens to *any* technology once the people who built it stop being the only ones who can build it. That's not unique to LLMs — it's every fast-follower story since Japanese steel. The "moat" was never the architecture. It was the six-month head start, and head starts close.
Where I'd push further than the price-war framing: the "trillion-dollar IPO" math didn't fail because the paradigm is bad. It failed because it was underwritten on the assumption that the gap would stay proprietary long enough to extract monopoly rents from it — the same assumption every currency peg and labor-cost advantage in the postwar export economies ran on, until the moment someone else learned to do the thing and the story flipped overnight from "comparative advantage" to "unfair competition." I wrote about that pattern at length here, if it's useful: [The Forgotten Theater](https://freeparadox.substack.com/p/the-forgotten-theater-dollar-hegemony)
Wright's point about non-zero-sum games is the real exit, I agree — but it only works if the U.S. stops treating "we lost the price war" as proof the technology was always worthless, instead of proof the monopoly pricing was always temporary.
These IPO's will be interesting. SpaceX was fortunate and lucky to be first though its value seems absurd and its AI component dubious. Being 2nd is better than being third and if Anthropic can sort out its spat with the USG, which seems to be happening they are positioned to be 2nd.
but
agree this energy and capital intensive "boil the ocean" approach to AI seems low ROI.
In the standard marketing model, there's only room for two dominant brands in a category (the leader and the alternative to the leader, along with a few less-profitable wannabes, epitomized by the old Hertz vs. Avis rental car market, where the second player had to 'try harder'). This is due primarily to the bandwidth of human recall, so it'll be interesting to see how many of the current AI competitors can hang on and achieve profitability as an actual market emerges, and for how long...
I’m surprised that the reliability piece isn’t more appreciated. Sure tokens are expensive but fundamentally if you’re running a business and using a technology to do something for the business you want to know that it’s going to work well every time!
The valley is very, very good at the pitch. That's kind of been its sorter since the late 90s.
Not so great at the make money side of things. Worse yet, the tech is too expensive so you can't do VC subsidized dumping to eat someone else's lunch through scale like taxi, delivery, or lodging.
AI is a nice fantasy / plagiarism machine with some limited use cases that are good (copypasta opensource code and pray, templating whatever docs, proofreading, natural language search / OS, and docreview. Not worth trillions in investment costs.
China has now developped an engineering / production expertise which has no match in the western world, with a key component being a superb synergy between "physics" AI. Engineering does not tolerate halucinations or operates with fake begaviors.
The distillation story sharpens the no-moat point this week: GLM-5.2, the new best open model, is alleged to be heavily distilled from Claude. If that holds, the frontier labs aren't just facing cheap competitors — they're supplying the training signal for the models that undercut them. Which is what makes the trillion-dollar IPO math you describe so hard to defend: hard to price in a moat your own outputs keep dissolving.
There is a dangerous illusion shaping the digital future. the belief that our data infrastructure is secure, resilient, and future-proof.
It is not.
At the center of this illusion lies tokenization a system designed to protect sensitive data, but one that is now becoming a hidden point of fragility at global scale.
Tokenization was built on a simple promise: separate sensitive data from its usage, reduce exposure, and contain risk.
But in reality, it has created a new concentration of power and vulnerability.
The token vault the core of this system is now one of the most critical and sensitive assets in the digital economy. If it fails, is compromised, or becomes inaccessible, entire systems can collapse. Financial networks, healthcare systems, identity infrastructures all depend on mappings that, if disrupted, can render data unusable or exposed.
This is not theoretical.
It is a structural risk.
At the same time, the rapid expansion of AI, cloud computing, and real-time data systems is pushing tokenization beyond its original design limits. The need for constant access, processing, and scale is forcing repeated detokenization increasing exposure, latency, and attack surfaces.
We are building faster systems on top of fragile foundations.
And the consequences of failure are no longer local . they are systemic.
Write on Medium
If tokenization architectures are improperly dismantled, migrated, or compromised without robust safeguards, the result could be catastrophic:
Permanent data loss
Large-scale exposure of sensitive information
Collapse of critical digital services
Loss of public trust in digital systems
This is no longer just a technical issue.
It is a matter of global stability.
The path forward demands urgent attention:
First, acknowledge that tokenization is not a complete solution. it is one layer in a broader security architecture.
Second, invest in resilient alternatives and complements. strong encryption, decentralized architectures, zero-trust systems, and secure computation models.
Third, establish global standards for the safe migration, decommissioning, and destruction of tokenized systems ensuring that data remains protected even as architectures evolve.
Finally, recognize that security decisions made today will define the resilience of tomorrow’s digital world.
The question is not whether our systems will be tested.
It is whether they will survive when they are.
The responsibility lies with you.
Act before the system is forced to reveal its weaknesses.
a match made in charlatan heaven?
https://www.telegraph.co.uk/business/2026/06/28/ai-boom-risks-global-financial-crash-central-bankers-warn/
Gary, I thought you might be interested in how fusion has in some respects failed in the same way as AI. My father was a professor of plasma physics for 30 years, and his opinion was that, instead of focusing on the tokamak, we still needed much more science to find a better model. In other words, the fusion sector jumped on the first technology that had some kind of return (eg, the ITAR project in France).
The same thing is happening in AI. Instead of trying many different paths, they jumped on one that, while very flawed, yielded some results, and since there was so much money sloshing around and venture capitalists like to hear good stories, the entire industry is wasting trillions on the wrong approach.
ASI also shares the claims made about fusion which are repeated ad nauseam : “We know how to build it. It’s only X years off. We just need more money”
And now the “promise” of fusion and ASI are joined at the hip, of course. “ASI will solve fusion, which will feed ASI to infinity and beyond”
And the AI companies think they can use fusion to power their data centers! https://time.com/7328213/nuclear-fusion-energy-ai/. A technology that doesn't exist yet, to power a technology that has no long-term business plan. Great combination!
Your father was in good company (with folks like Bob Rosner)
We need more actual scientists with a skeptical bent and far fewer charlatans making outlandish unsupported claims
https://thebulletin.org/premium/2024-11/ferreting-out-the-truth-about-fusion-interview-with-bob-rosner/
Thanks for the link!
I'm not convinced that the comparison between fusion energy and LLMs is correct. The Tokamac approach being pursued by the international ITER collaboration is by no means unique, and the fundamental impediment- production of sufficiently strong magnetic fields- eluded researchers until the advent of superconducting magnets. I am not trying to minimize the difficulty of the task. The physics is basically understood. But as yet there is no consensus on what constitutes consciousness or6 thought, and moreover, unlike ML, for which error performance is characterizable, LLMs are fundamentally unpredictable.
Yann LeCun’s world model sounds interesting, and it certainly would fit your fusion analogy. The question is, how long will it take for this model to yield results?
LLMs, while imperfect can be improved with scaffolding even if they don’t have the capacity to achieveAGI.
I feel that LLMs can do useful work, as does Gary, if I understand him correctly. I have successfully used it for coding, and I think it has potential for information retrieval. It's the world-changing proclamations that I don't agree with.
In fact, since fusion has not led to any useful results, as far as I know -- except for scientifically interesting data -- I would have to say that LLMs are ahead of fusion at the moment, although again, I don't see the extreme expense as having been worth it.
I completely agree. I would place this current plateau of AI at the same scale as streaming video in terms of the potential amount of disruption. Still a huge opportunity but not an earth-shattering AGI paradigm shift.
A difference is that fusion projects have continued to evolve, such that net positive energy (a technical measurement, not a commercial possibility, see https://lift.llnl.gov/) has occurred at the Livermore facility. With advances in superconductors, the Commonwealth Fusion project (https://cfs.energy/) is moving at a pace and with a design that is far different and probably ahead of the ITAR. It is unfortunate that the US government is not pushing the development of fusion at anywhere near the pace of China.
The Livermore facility concentrates on simulating nuclear weapons, and they use lasers focused on a nodule (my technical understanding is general). They have tended, historically, to ocassionally announce breakthroughs that weren't really applicable, just a warning. But thanks for the info. It's certainly a field to keep an eye on, it's just that I am very skeptical. It is the quintessential 'we are 15 (or pick your number) years away' technology
Why focus on fusion, when atmospheric pressure fission is already available?
Livermore showed that net positive energy is possible. That facility is not a commercial model in any manner. ITAR is a demonstration project, but it is flawed in being big and taking too long to develop. Fission works, yes, but there remains the waste problem and the issue of politics, the perception of danger to the public. We have no consensus on dealing with the nuclear waste. Small fission reactors hold promise, but they are still in development. I focus on fusion because it would likely not have the immediate danger issues (meltdown), although nuclear waste could still be a problem. We clearly have lots of room for more wind/solar/tidal and even some hydro, and with new battery tech, the issue of the sun going down is obviated. However, at regional scale, baseline power demand still benefits from centralized plants, and fusion would be a huge benefit.
There's no real waste problem with fission. Even with the ridiculous current generation of reactors in the US that operate with 3.5 percent U-235 and without any attempts reprocess spent fuel, we're talking about only 2000 tons per year produced by the entire US nuclear industry. (Compare that, for example, to the approximately 300 million tons of municipal solid waste produced every year, and which is far less dense than spent fuel. Or the 70 million tons of coal ash produced, for that matter.)
The only real issue is politics. It might have been reasonable' politically, to oppose water- cooled reactors operating at high pressure. There's no good reason to oppose a fission reactor operating at atmospheric pressure.
HAAJII COMEDY AI business
The return flag: https://github.com/space-bacon/SRT
The problem is: there is no better model. Any system of atoms sufficiently complex and energetic to produce fusion is also going to have uncontrollable chaotic instabilities (like solar flares in the Sun). So controlled fusion as an energy source is just not happening.
Well frankly toward the end of his life my father felt fusion would never happen. It's worth pursuing, I think, just in case. It would be much better if it was based on deuterium, fwiw, which is very clean and very cheap, unlike tritium, which is being used now. But we just don't know how to control it at this point, as far as I can tell
How do we know enough about the Strong Force to prove this? I don't think we know enough about the Strong Force to say this for sure, or how we would even go about formalizing a theory for why there isn't a non-trivial range of ways to do so. Edit: especially given our uncertainty about the interactions between the Electroweak Force and the Strong Force at high temperature and density.
The strong force is not relevant to the instabilities, it's the magnetohydrodynamics of the plasma. But even if the strong force was relevant, complex many-body systems without exponentially growing unstable modes essentially do not exist except as ideallized mathematical models.
What would be even the kernel of a theory that could formalize a description that such stable many-bodied systems can never exist from now until the end of the universe? I don't doubt that there is a chance your point of view is the case. But I don't share your level of confidence which seems absolute.
You also seem very confident that the Strong Force doesn't have anything to do with the justification for why many-bodied systems of atoms cannot have some kind of stable manageable transition modes for a time-bounded period. I especially don't share your confidence here: https://www.sciencenews.org/article/nuclear-fusion-alpha-particles-reactor
Yep. One gigantic uber costly machine that can do everything certainly does not sound like the most efficient way to do anything.
“Triv-AI-al Pursuit”
Triv-AI-al pursuit
Is all the rage, it seems
It’s played by men in suits
And tech bros wearing jeans
It’s played by CEOs
And played by public too
But AI-mperor’s got no clothes
And privates are in view
Wish I could like this 100 times!
I think the pundits in the West simply haven't got it when it comes to understanding how China has integrated the 1st, 2nd and 3rd Industrial revolutions. Whereas Western capitalism simply jettisoned the 1st and 2nd industrial revolutions largely through financialisation/export of production, driven by short-term profit goals, the 'secret' to China's success has been to possess the entire spectrum of the production process, of which AI is the culmination. After all, it's ALL ABOUT ECONOMICS! What's more, automation isn't leading to unemployment in China (AI is automation by another name), far from it, AI when applied humanely, opens up the possibility of upskilling, of transforming the relationship between labour and production, this is what socialism is all about.. Thus the CCP just passed a law making it illegal for AI to create redundancies. Two different worlds.
“AI when applied humanely, opens up the possibility of upskilling, of transforming the relationship between labour and production”
- beautiful thought and an admirable goal.
It’s not just an admirable goal, it is a choice. I’m not a big fan of CCP, but they do get some of their economics right in that they have a set of values that come first and then efficiency etc come next. They seem to recognize what the purpose of the economy is - to provision their society- and they have harnessed markets and private ownership (capitalism) to achieve that when it works best and state ownership when it doesn’t. They have screwed up their property markets, but have done well with renewables and EVs. I’m not an expert on china, but I do know my economics. This whole US AI debacle has been created by shortsighted greedy ah who want to replace the labor force they don’t want to pay for. It’s the dumbest purpose for technology. Now that doesn’t mean that AI is dumb, it is that the current companies developing it are well ah.
"automation isn't leading to unemployment in China "
Really? Lots of articles, X posts etc. about China having about 25% youth unemployment rate if the numbers are calculated accurately. E.g. https://asiasociety.org/policy-institute/19-percent-revisited-how-youth-unemployment-has-changed-chinese-society
If it isn't automation leading to unemployment something else is
"Thus the CCP just passed a law making it illegal for AI to create redundancies"
And the PRC is a law-abiding society where no large company executive would pay bribes to enforcement officials, right? I mean that never ever happens...
I couldn’t agree with your closing thought more. I am excited about how Seed IQ’s active inference based AI agents acted as a control layer and created stability on IBM’s NISQ hardware. If Quantum leaps ahead we might not need all the data center compute.
Gary — I think this is the right diagnosis wearing the wrong frame. "Brute force, unreliable, easily replicated" reads like an indictment of the paradigm, but it's really a description of what happens to *any* technology once the people who built it stop being the only ones who can build it. That's not unique to LLMs — it's every fast-follower story since Japanese steel. The "moat" was never the architecture. It was the six-month head start, and head starts close.
Where I'd push further than the price-war framing: the "trillion-dollar IPO" math didn't fail because the paradigm is bad. It failed because it was underwritten on the assumption that the gap would stay proprietary long enough to extract monopoly rents from it — the same assumption every currency peg and labor-cost advantage in the postwar export economies ran on, until the moment someone else learned to do the thing and the story flipped overnight from "comparative advantage" to "unfair competition." I wrote about that pattern at length here, if it's useful: [The Forgotten Theater](https://freeparadox.substack.com/p/the-forgotten-theater-dollar-hegemony)
Wright's point about non-zero-sum games is the real exit, I agree — but it only works if the U.S. stops treating "we lost the price war" as proof the technology was always worthless, instead of proof the monopoly pricing was always temporary.
"If we are victorious in one more battle with the Romans, we shall be utterly ruined."
King Pyrrhus of Epirus, 279 BCE
These IPO's will be interesting. SpaceX was fortunate and lucky to be first though its value seems absurd and its AI component dubious. Being 2nd is better than being third and if Anthropic can sort out its spat with the USG, which seems to be happening they are positioned to be 2nd.
but
agree this energy and capital intensive "boil the ocean" approach to AI seems low ROI.
In the standard marketing model, there's only room for two dominant brands in a category (the leader and the alternative to the leader, along with a few less-profitable wannabes, epitomized by the old Hertz vs. Avis rental car market, where the second player had to 'try harder'). This is due primarily to the bandwidth of human recall, so it'll be interesting to see how many of the current AI competitors can hang on and achieve profitability as an actual market emerges, and for how long...
Agreed. Also network effects. The losers never reach the critical mass to get virtuous circles going
Can this bot nonsense be blocked?
I’m surprised that the reliability piece isn’t more appreciated. Sure tokens are expensive but fundamentally if you’re running a business and using a technology to do something for the business you want to know that it’s going to work well every time!
Cool demo, mid-product.
The valley is very, very good at the pitch. That's kind of been its sorter since the late 90s.
Not so great at the make money side of things. Worse yet, the tech is too expensive so you can't do VC subsidized dumping to eat someone else's lunch through scale like taxi, delivery, or lodging.
AI is a nice fantasy / plagiarism machine with some limited use cases that are good (copypasta opensource code and pray, templating whatever docs, proofreading, natural language search / OS, and docreview. Not worth trillions in investment costs.
China has now developped an engineering / production expertise which has no match in the western world, with a key component being a superb synergy between "physics" AI. Engineering does not tolerate halucinations or operates with fake begaviors.
Even the AI optimists are now calling for doom...
If you thought the global financial crisis was bad…
https://www.economist.com/by-invitation/2026/06/28/if-you-thought-the-global-financial-crisis-was-bad
From The Economist
The distillation story sharpens the no-moat point this week: GLM-5.2, the new best open model, is alleged to be heavily distilled from Claude. If that holds, the frontier labs aren't just facing cheap competitors — they're supplying the training signal for the models that undercut them. Which is what makes the trillion-dollar IPO math you describe so hard to defend: hard to price in a moat your own outputs keep dissolving.
There is a dangerous illusion shaping the digital future. the belief that our data infrastructure is secure, resilient, and future-proof.
It is not.
At the center of this illusion lies tokenization a system designed to protect sensitive data, but one that is now becoming a hidden point of fragility at global scale.
Tokenization was built on a simple promise: separate sensitive data from its usage, reduce exposure, and contain risk.
But in reality, it has created a new concentration of power and vulnerability.
The token vault the core of this system is now one of the most critical and sensitive assets in the digital economy. If it fails, is compromised, or becomes inaccessible, entire systems can collapse. Financial networks, healthcare systems, identity infrastructures all depend on mappings that, if disrupted, can render data unusable or exposed.
This is not theoretical.
It is a structural risk.
At the same time, the rapid expansion of AI, cloud computing, and real-time data systems is pushing tokenization beyond its original design limits. The need for constant access, processing, and scale is forcing repeated detokenization increasing exposure, latency, and attack surfaces.
We are building faster systems on top of fragile foundations.
And the consequences of failure are no longer local . they are systemic.
Write on Medium
If tokenization architectures are improperly dismantled, migrated, or compromised without robust safeguards, the result could be catastrophic:
Permanent data loss
Large-scale exposure of sensitive information
Collapse of critical digital services
Loss of public trust in digital systems
This is no longer just a technical issue.
It is a matter of global stability.
The path forward demands urgent attention:
First, acknowledge that tokenization is not a complete solution. it is one layer in a broader security architecture.
Second, invest in resilient alternatives and complements. strong encryption, decentralized architectures, zero-trust systems, and secure computation models.
Third, establish global standards for the safe migration, decommissioning, and destruction of tokenized systems ensuring that data remains protected even as architectures evolve.
Finally, recognize that security decisions made today will define the resilience of tomorrow’s digital world.
The question is not whether our systems will be tested.
It is whether they will survive when they are.
The responsibility lies with you.
Act before the system is forced to reveal its weaknesses.
Part of me thinks this is the set up all along. What a way to crash an economy. China knows how America works.