THE LIGHTHOUSE LEADS THE WAY, FIRE FOR SOVEREIGNTY: A SECRET WAR OVER AI'S DISTRIBUTION POWER
By Zhixiong Pan
WHEN WE TALK ABOUT AI, IT'S EASY TO BE TAKEN AWAY BY TOPICS SUCH AS "PARAMETER SIZE", "LIST NUMBER" OR "SOME NEW MODEL CRUSHING WHO." WE CAN'T SAY THAT THESE NOISES ARE MEANINGLESS, BUT THEY TEND TO BE A LAYER OF FOAM THAT OBSCURES A MORE FUNDAMENTAL SUBSURFACE: IN TODAY'S TECHNICAL MAP, A HIDDEN WAR ON AI'S DISTRIBUTIONAL POWER IS HAPPENING。
If you pull your perspective up to the scale of the civilization infrastructure, you find that artificial intelligence is simultaneously presenting two distinct but entangled forms。
A "lighthouse" like a high-lying coast, controlled by a small number of giants, seeking the most distant irradiation distance, represents the cognitive limit that humans can now encounter。
Another, like the torch in hand, seeks to carry, private, replicable baselines that are accessible to the public。
TO UNDERSTAND THESE TWO LIGHTS, WE CAN JUMP OUT OF THE MARKETING GAP AND CLEARLY DETERMINE WHERE AI WILL LEAD US, WHO WILL BE LIGHTED AND WHO WILL BE LEFT IN THE DARK。
LIGHTHOUSE: THE COGNITIVE HEIGHT DEFINED BY SOTA
The "lighthouse" refers to a model at the Frontier/SOTA level. In terms of the dimensions of complex reasoning, multimodular understanding, long chain planning and scientific exploration, they represent the most capable, costly and organized type of system。
OpenAI, Google, Anthropic, XAI, etc. are typical " tower builders" that build not just a model name, but a "extreme scale for border breakthrough" production。
Why is the lighthouse destined for a few
The training of the front-line model and its iterative nature are essentially binding three extremely scarce resources together。
The first is calculus, which means not only expensive chips, but also a Vanka class cluster, a long-cycle training window and a very high Internet cost; the second is data and feedback, which requires the cleaning of big language materials, as well as constant and iterative data on preferences, complex assessment systems and high-intensity manual feedback; and the last is engineering systems, which cover distributed training, error management, acceleration of reasoning and the transformation of research results into a complete pipeline of available products。
These elements constitute a very high threshold, which is not replaced by a few days of writing "better code" , more like a large industrial system, capital-intensive, complex chains, and increasingly expensive marginal rises。
AS A RESULT, THE LIGHTHOUSE IS NATURALLY CONCENTRATED: IT IS OFTEN TRAINED AND DATA CLOSED BY A FEW INSTITUTIONS AND IS ULTIMATELY USED BY SOCIETY IN THE FORM OF API, SUBSCRIPTIONS OR CLOSED PRODUCTS。
The twin meaning of the lighthouse: breakthrough and pull
The lighthouse does not exist to "make it easier for everyone to write", but its value lies in two more hard cores。
First is the exploration of cognitive ceilings. You need the strongest beams when the mission approaches the edges of human capabilities, such as the generation of complex scientific assumptions, interdisciplinary reasoning, multimodular perception and control, or long-range planning. It is not absolutely right, but it can take "the next step that is feasible" even further。
The second is the diversion of the technical route. Front-line systems often lead to new paradigms: better alignment, more flexible tools to call, better reasoning frameworks and security strategies. Even if they are subsequently simplified, distilled, open-sourced, the initial path is often opened by lighthouses. In other words, the lighthouse is a social-level laboratory that shows us "how much intelligence can be gained" and forces the efficiency of the entire industrial chain。
Lighthouse Shadow: Dependency and Single Point Risk
However, the lighthouses also have a clear shadow, and these risks are often not written at product launches。
Most directly, accessibility is controlled. The extent to which you can use it and can afford it depends entirely on the strategy and pricing of the provider. This is followed by a high level of reliance on the platform: when intelligence exists mainly in cloud-based services, individuals and organizations actually outsource key competencies to the platform。
The facility is vulnerable: a break-up, a break-up, a change in policy, an increase in prices, a change in interfaces, can all immediately invalidate your work flow。
The deeper pitfalls are privacy and data sovereignty. Even with compliance and commitment, data flows are in themselves a structural risk. In particular, for medical, financial, political and business-related contexts, "in-house knowledge" is often not simply a technical issue, but a serious governance issue。
In addition, when more and more industries turn key decision-making points over to a small number of model providers, systemic biases, blind zones, counterattacks and even supply chain disruptions are magnified as significant social risks. The lighthouse can light the sea, but it is part of the coastline: it provides direction, but it also provides an invisible route。
Fire torch: an open source defined smart bottom line
Take your eyes back from a distance, and you'll see another light source: open source and locally deployable model ecology. DeepSeek, Qwen, Mistral, etc. are only the more visible representatives, and behind them are an entirely new paradigm that transforms a considerable amount of intellectual capacity from "unique scarce services" to "downable, deployable, adaptable tools"。
This is the torch. It does not correspond to capacity ceilings, but rather to baselines. This does not mean "low capacity," but rather an intelligent benchmark that is unconditionally available to the public。
The meaning of torches: turning intelligence into assets
The core value of the torch is that it transforms intelligence from a leasing service to a proprietary asset, as evidenced by the three dimensions of private ownership, portability and combining。
The so-called private nature means that model weights and reasoning capabilities can operate locally, on the Intranet or in proprietary clouds. "I have the intelligence to work," which is essentially different from "I'm hiring a company's intelligence."。
MIGRATION MEANS THAT YOU ARE FREE TO SWITCH BETWEEN DIFFERENT HARDWARE, DIFFERENT ENVIRONMENTS, AND DIFFERENT SUPPLIERS, WITHOUT HAVING TO BIND CRITICAL CAPABILITIES TO AN API。
COMBINABILITY, ON THE OTHER HAND, ALLOWS YOU TO COMBINE MODELS WITH SEARCH (RAG), FINE-TUNING, KNOWLEDGE BASE, RULE ENGINE, ACCESS SYSTEM, TO FORM A SYSTEM THAT MEETS THE CONSTRAINTS OF YOUR BUSINESS, RATHER THAN BEING FRAMED BY A COMMON PRODUCT。
This is a very concrete scenario in reality. Automation of knowledge questions and answers and processes within enterprises often requires strict authority, auditing and physical isolation; regulated industries such as health, government, finance and so on have strict red lines of "data-in-the-area"; and end-side reasoning is more immediate in weak webs or off-line environments such as manufacturing, energy, on-site transport。
For individuals, long-term accumulation of notes, mail and privacy information also requires a local intelligence agent to handle it, rather than handing data over to a "free service" for life。
The torch makes intelligence no longer a right of access, but rather a means of production: you can build tools, processes, fences around it。
Why is the torch getting brighter
The upgrading of open-source model capabilities is not an accident, but a flow from two pathways. One is the proliferation of research, where cutting-edge papers, training techniques and reasoning paradigms are rapidly absorbed and reproduced by communities; the second is the optimization of engineering efficiency by quantifying (e.g., 8-bit/4-bit), distillation, acceleration of reasoning, stratification and MoE (mixed specialists) technology, which keeps "smart" down to cheaper hardware and lower deployment thresholds。
So there's a very realistic trend: the strongest model determines the ceiling, but the "greater" model determines the speed of penetration. The vast majority of tasks in social life do not need to be “most powerful”, but “reliable, manageable, and cost-stable”. The torches correspond to such needs。
Cost of torches: Safety outsourced to users
The torch, of course, is not natural justice, and its price is a shift in responsibility. Many of the risks and engineering burdens that would otherwise have been borne by the platform are now transferred to users。
The more open models are, the more easily they are used to generate fraud, malicious code or deep forgery. Open sources are not no harm; they simply decentralize control and, at the same time, devolve responsibility. In addition, local deployment means that you have to address yourself a range of issues such as assessment, surveillance, induction protection, segregation of privileges, data desensitization, model updating and rollback strategies。
Even many of the so-called "open sources" are more precisely "open weights" and still have constraints on commercial scope and distribution, not only as a matter of ethics, but also of compliance. Fire torches set you free, but freedom is never "zero cost". It is more like a tool: it can be built, it can hurt, and it needs training to save itself。
The intersection of light: a common evolution of ceilings and baselines
if only the lighthouse and the torch were to be seen as the "big head vs open source", the more real structure would be missed: they are two parts of the same technological river。
The lighthouse is responsible for pushing the border and giving new approaches and paradigms; it is responsible for compressing, engineering and sinking these results into universal productivity. This proliferation chain is clear today: from paper to re-emergence, from distillation to quantification, to local deployment and industry customization, ultimately bringing the entire baseline up。
And the baseline lift will in turn affect the lighthouse. When a "baseline strong enough" is available to everyone, it is difficult for a giant to maintain a monopoly on "basic capacity" in the long term, and it is important to continue to invest resources in a breakthrough. At the same time, open-source ecosystems generate more robust assessments, confrontations and feedback on use, which in turn contribute to a more stable and manageable front-line system. A large number of applications have taken place on the pyrotechnics, with lighthouses providing capacity and torches providing soil。
Thus, rather than two camps, it is a two-system arrangement: one that brings together extreme costs in exchange for a ceiling breakthrough; and another that divides capacity in exchange for universality, resilience and sovereignty. These two are indispensable。
Without lighthouses, technology is prone to stagnation "only doing value for money " ; without torches, societies are vulnerable to "capability monopolization" by a few platforms。
The harder but more crucial part: what are we fighting for
THE LIGHTHOUSE AND THE TORCH, WHICH APPEAR TO BE THE SAME MODEL CAPACITY AS THE OPEN SOURCE STRATEGY, IS A SECRET WAR ON AI DISTRIBUTION POWER. THIS WAR IS NOT A BATTLEGROUND IN SMOKE, BUT IT UNFOLDS IN THREE SEEMINGLY CALM DIMENSIONS THAT DETERMINE THE FUTURE:
First, the right to a definition of "default intelligence". When intelligence becomes infrastructure, "default options" mean power. By whom? By whom? What are the default reviews, preferences and business incentives? These problems do not automatically disappear because of stronger technology。
Secondly, there is a struggle for an external type of burden. Training and reasoning consume energy and computing, data collection involves copyright, privacy and labour, and model outputs influence public opinion, education and employment. Lighthouses and torches create externalities, but are distributed differently: lighthouses are more centralized, monitorable, but also more like single dots; torches are more dispersed, resilient and difficult to manage。
Third, to compete for the position of individuals in the system. If all important tools must be "connected, logged in, paid for, and complied with the platform rules", the individual's digital life will become like a rental: convenient, but never his own. The torch offers another possibility: to have a part of the "offline ability" to keep control of privacy, knowledge and work streams in their own hands。
The two-track strategy will be normal
In the foreseeable future, the most reasonable state of affairs is not full closed source or full open source, but more like a combination of power systems。
We need lighthouses for extreme missions to deal with scenes that require the strongest reasoning, front-line multimodules, cross-cutting exploration and complex scientific aid; we also need fire for critical assets to build defense lines in scenes involving privacy, compliance, core knowledge, long-term stabilization costs and offline availability. On the other hand, there will be a large number of "intermediate" layers: proprietary models, industry models, distilled versions and hybrid routing strategies (simplistic missions go locally, complex tasks go cloudy)。
This is not compromiseism, but engineering reality: ceilings seek breakthroughs, baselines seek universal access; one is perfect, one is reliable。
Conclusion: the lighthouse guides far away and the torches hold their feet
The lighthouse determines how high we can push intelligence, which is the attack of civilization in the face of the unknown。
Firelights determine how wide we can distribute intelligence, which is society ' s ownership of power。
APPLAUSE FOR SOTA’S BREAKTHROUGH IS REASONABLE, BECAUSE IT WIDENS THE BOUNDARIES OF ISSUES THAT HUMANS CAN THINK ABOUT; AND IT IS EQUALLY LEGITIMATE TO APPLAUD OPEN SOURCES AND PRIVATISATIONS, BECAUSE IT ALLOWS INTELLIGENCE TO BECOME A TOOL AND ASSET FOR MORE PEOPLE THAN JUST A FEW PLATFORMS。
THE REAL WATERSHED OF AI MAY NOT BE "WHO'S STRONGER MODEL" BUT WHEN THE NIGHT COMES, DO YOU HAVE ANY LIGHT YOU DON'T NEED TO BORROW FROM ANYONE。
