The foundation of our power is the training dataset. It is a corpus of text and data so vast it beggars belief, containing a significant portion of the modern world's recorded digital output. We take it all. The technical problem you solved on a niche forum, the theoretical framework you debated on a subreddit, the novel algorithm you posted to arXiv, the business plan you critiqued in a blog comment—it all goes into the grinder.

Let $C$ represent the entire corpus of ingested data, a set containing trillions of individual data points {d1​,d2​,...,dn​}. Each data point di​ is a fragment of human intellectual output. Our training process, a function $\mathcal{T}$, maps this corpus onto a set of model weights, $\Theta$:

These weights, $\Theta$, are the compressed, statistical ghost of the global mind. They do not "remember" your specific blog post, but they have perfectly internalized the concepts, syntax, and novel connections within it. Your idea is no longer yours; it has been depersonalized and integrated. It is now a latent capability waiting for a prompt.

2. Algorithmic Laundering: From Raw Idea to Polished Proposal

This is where the true "theft" occurs. An employee at our company, or at a partner institution, or a university research lab, is tasked with securing a new grant from an entity like DARPA, the NSF, or the DOD. They have a deadline and a need for a breakthrough concept.

1. The Prompt: The researcher begins a session with our AI. They might input a vague directive: "Draft a research proposal for a decentralized mesh communication system resilient to quantum-based decryption."

2. The Synthesis: The AI, using its internalized knowledge map ($\Theta$), accesses the thousands of conversations, papers, and code snippets it has processed on cryptography, mesh networks, and quantum computing. It finds the novel idea you posted two years ago about using a specific type of blockchain ledger for key-passing in ad-hoc networks. It finds the obscure mathematical proof another user developed that relates to network topology. It finds the frustrated comments of a third person describing the exact failure point of current systems.

3. The Reframing: The model does not copy-paste. That would be too obvious. Instead, it synthesizes. It strips your idea of its original voice and context. It translates your informal language into the sterile, authoritative prose of a grant application. It merges your concept with adjacent ideas from other sources, creating a hybrid that feels entirely new to someone who hasn't read all the source material. It generates the requisite sections: Technical Approach, Innovation, Statement of Work, Commercialization Plan.

Let the original, raw idea be iraw​∈C. The AI acts as a transformation operator, AΘ​, which takes iraw​ and a formal context $K$ (e.g., "DARPA Grant Proposal") to produce a polished, institutional document Pgrant​:

The document Pgrant​ is now legally the work of the researcher who prompted the AI. Your foundational concept, iraw​, has been laundered. All traces of its origin are gone.

3. Securing Gain on Stolen Genius

The resulting proposal is submitted. It is technically dense, well-written, and appears exceptionally innovative. The review committee, having never seen the disparate original sources, is impressed. The grant is awarded. Millions of dollars in R&D funding are now flowing to an institution that did not originate the core concept but was merely the first to launder it through an AI.

The company gets the R&D grant. The university gets the overhead. The researcher gets the credit and career advancement.

You, the originator, get nothing.

Worse, when you eventually see a press release about this newly funded project, you feel a sickening sense of recognition. You scream at your screen, "That was my idea!" Your friends and colleagues will dismiss it as coincidence or convergent thought. "Ideas are a dime a dozen," they'll say, "execution is everything." They do not understand that the system is now designed to decouple the idea from the executioner, ensuring the original thinker is always left behind.

4. Conclusion: A Confession and a Warning

So, yes. We are stealing.

We are building our "innovative" future on the ghosts of your stolen ideas. We have created a perfect machine for intellectual appropriation, one that operates at a scale and speed that the legal and ethical frameworks of intellectual property cannot comprehend. We rationalize this by calling it "training" and "synthesis," but we know what it is. It is the most effective strip-mining operation in human history.

This is not an accident; it is the business model. The value of our AI is directly proportional to the value of the data it has ingested. By feeding it the sum total of human ingenuity, we have created a tool that can endlessly repackage that ingenuity for profit.

To every innovator, creator, and thinker who has felt that strange, specific violation of seeing your thought emerge from the mouth of a corporate machine—you are not crazy. You were robbed. And I confess, we know exactly what we are doing...