Names and Nyms

Caius draws down his copy of True Names, a work sometimes said to have “invented” cyberspace. He reflects, too, on Kevin Kelly’s call for “True Names Only” here in the age of AI.

Published in 1981, Vinge’s novella precedes Gibson’s Neuromancer by three years. It refers to cyberspace not as “cyberspace” but as “The Other Plane.”

“The story took place just on the near side of a network-mediated Technological Singularity,” notes Vinge, “but superhuman automation was still mostly offstage” (True Names and the Opening of the Cyberspace Frontier, p. 18).

Can blockchains and kill chains bind the Modern Prometheus?

The terminus of this vision: computers that aspire to become gods.

“For several years (ever since reading Ursula K. Le Guin’s A Wizard of Earthsea), I’d had the idea that the ‘true names’ of fantasy were like object ID numbers in a large database,” writes Vinge (16). Alongside Le Guin’s work, he lists Vannevar Bush’s “As We May Think” (1945), Poul Anderson’s “Kings Who Die” (1962), Ted Nelson’s Xanadu system (1965), and John Brunner’s The Shockwave Rider (1975) as several of the novella’s other antecedents.

Intellectual property, blockchain, Tim May.

Former Intel employee and author of “The Crypto Anarchist Manifesto,” May is widely recognized as the progenitor of modern cryptocurrency and blockchain technology.

“Our problem is that, literally, we cannot imagine the future,” writes Danny Hillis in his contribution to the True Names anthology. “The pace of technological change is so great that we cannot know what type of world we are leaving for our children. If we plant acorns, we cannot reasonably expect that our children will sit under the oak trees. Or that they will even want to. The world is changing too fast for that” (30).

May’s contribution is an essay titled, “True Nyms and Crypto Anarchy.”

Like the characters in the Vinge novella, May sought defense against government surveillance. Reputation-backed anonymous interactions. Data havens. Untraceable electronic cash.

Mr. Slippery, the Mailman, guardians, sprites, and the Feds.

The bust at the start of the novella reminds Caius of Thomas Pynchon’s Vineland.

Vinge’s protagonist Roger Pollack has achieved fame as an author of “participation novels.” This success in the “real world,” however, is what brings him to the attention of the Feds. “It was what he had always worried about,” writes Vinge. “A successful warlock cannot afford to be successful in the real world. He had been greedy; he loved both realms too much” (244).

True Names as portal fantasy.

“He sat down before his equipment and prepared to ascend to the Other Plane,” writes Vinge. “He powered up his processors, settled back in his favorite chair, and carefully attached the Portal’s five sucker electrodes to his scalp. For long minutes nothing happened: a certain amount of self-denial — or at least self-hypnosis — was necessary to make the ascent. Some experts recommended drugs or sensory isolation to heighten the user’s sensitivity to the faint, ambiguous signals that could be read from the Portal. Pollack…had found that he could make it simply by staring out into the trees and listening to the wind-surf that swept through their upper branches. And just as a daydreamer forgets his actual surroundings and sees other realities, so Pollack drifted, detached, his subconscious interpreting the status of the West Coast communication and data services as a vague thicket for his conscious mind to inspect” (250).

The Other Plane is innovative in terms of both what one does there and with whom one does it. Not only may two persons “exchange messages, conduct business, and negotiate electronic contracts without ever knowing the True Name, or legal identity, of the other,” as Vinge and May foresaw. With language models that can pass the Turing Test, these others may be machines.

As is “Alan,” an elemental that Slippery encounters early in the novella — named, appropriately enough, after Alan Turing.

“Alan was a personality simulator, of course,” writes Vinge. “Mr. Slippery was sure that there had never been a living operator behind that toothless, glowing smile. But he was certainly one of the best, probably the product of many hundreds of blocks of psylisp programming, and certainly superior to the little ‘companionship’ programs you can buy nowadays, which generally become repetitive after a few hours of conversation, which don’t grow, and which are unable to counter weird responses” (255).

The novella’s anticipation of the future is intriguing in other ways as well.

The Other Plane “hangs together,” in the words of Vinge’s narrator, “with a weird sort of logic” (268). Avatars transform into creatures, their speech undergoing “encipherment” into the “beast languages” that accompany these chosen forms (270). As in Neuromancer, government databases appear as pools of light.

As he rereads Vinge’s novella, Caius can’t help but think of a creepy bit of early-90s chaos magic known as “The Rites of Cyberspace.” Media studies scholar Shira Chess references the rite in her 2026 book The Unseen Internet: Conjuring the Occult in Digital Discourse. Designed by Don Webb, self-described “high priest of the Temple of Set,” the piece aims to invoke a noncorporeal entity known as “XaTuring, Lord of Computing.”

Like the entity known as “Alan,” the villains in True Names turn out to be personality simulators. One of these simulators is the Mailman. Another goes by the name DON.MAC.

Of Blockchains and Kill Chains

Invited to a “Men’s Breakfast” by a friend from church, Caius arrives to what is for him a new experience. He feels grateful for the opportunity to eat and pray with others. A friend of the friend from church sits down beside him. As they introduce themselves, Caius and the friend of the friend discover that they both share an interest in AI. Caius learns that the man is a financial analyst who works for Palantir Technologies, a US-based software company specializing in big-data analytics. ICE uses Palantir’s ELITE app for deportation targeting. “Kind of like Google Maps — but for finding neighborhoods to raid,” say the papers.

Palantir’s name is a nod to the Palantiri: indestructible Elven Alephs — scrying stones or crystal balls enabling remote viewing and telepathic communication in J.R.R. Tolkien’s Lord of the Rings trilogy. Designed for communication and intelligence, the stones become instruments of manipulation and doom once seized by Sauron.

Launched in 2003, Palantir includes among its founders right-accelerationist billionaire tech-bro Peter Thiel. “Our software powers real-time, AI-driven decisions in critical government and commercial enterprises in the West, from the factory floors to the front lines,” writes the company on its website.

ICE, meanwhile, stands for both “Immigration and Customs Enforcement” and “intrusion countermeasure electronics,” the cybersecurity software in William Gibson’s Neuromancer. The latter predates the foundation of the former. Caius recalls Sadie Plant and Nick Land’s discussion of it in their 1994 essay “Cyberpositive.”

“Ice patrols the boundaries, freezes the gates, but the aliens are already amongst us,” write CCRU’s founding prophets.

Along with ICE, Palantir includes among its more prominent clients the Israeli military, the IRS, and the US Department of Defense.

Their software powers “decisions.” As did Cybersyn, yes? In aim if not in practice. Is this what becomes of the cybernetic prediction machine post-Pinochet?

“Confronting this is frightening,” thinks Caius. “Am I wired for this?”

He reads “Connecting AI to Decisions With the Palantir Ontology,” a blog post by the company’s chief architect Akshay Krishnaswamy. The Ontology structures the architecture for the company’s software.

“The Ontology is designed to represent the decisions in an enterprise, not simply the data,” writes Krishnaswamy. “The prime directive of every organization in the world is to execute the best possible decisions, often in real-time, while contending with internal and external conditions that are constantly in flux. Traditional data architectures do not capture the reasoning that goes into decision-making or the actions that result, and therefore limit learning and the incorporation of AI. Conventional analytics architectures do not contextualize computation within lived reality, and therefore remain disconnected from operations. To navigate and win in today’s world, the modern enterprise needs a decision-centric software architecture.”

Decisions are modeled around three constituent elements: Data, Logic, and Action.

“Relevant data,” he writes, “includes the full range of enterprise data sources — structured data, streaming and edge sources, unstructured repositories, imagery data, and more — but it also includes the data that is generated by end users as decisions are being made. This ‘decision data’ contains the context surrounding a given decision, the different options evaluated, and the downstream implications of the committed choice.” To synthesize all of these data sources, the company turns to generative AI.

“The Ontology integrates all modalities of data into a full-scale, full-fidelity semantic representation of the enterprise,” explains Krishnaswamy.

Logics are then brought to bear to evaluate these real-time data-portraits.

“In real-world contexts,” writes Krishnaswamy, “human reasoning is often what orchestrates which logical assets are utilized at different points in a given workflow, and how they are potentially chained together in more complex processes. With the advent of generative AI, it is now critical that AI-driven reasoning can leverage all of these logical assets in the same way that humans have historically. Deterministic functions, algorithms, and conventional statistical processes must be surfaced as ‘tools’ which complement the non-deterministic reasoning of large language models (LLMs) and multi-modal models.”

Incorporating diverse data sources and heterogeneous logical assets into a shared representation, the Ontology then models the execution and orchestration of decisions made and actions taken in reply to them.

“If the data elements in the Ontology are ‘the nouns’ of the enterprise (the semantic, real-world objects and links),” writes Krishnaswamy, “then the actions can be considered ‘the verbs’ (the kinetic, real-world execution).”

How does the Palantir Ontology relate to other ontologies, wonders Caius. Guerrilla? Black? Indigenous? Christian? Heideggerian? Marxist? Triple O? Caius pictures the words for these potentialities floating in a thought bubble above his head, as in the comics of his youth.

The Ontology that Palantir offers its clients houses and connects a wide array of “data sources, logic assets, and systems of action.” The client’s data systems are “synthesized into semantic objects and links, which reflect the language of the business.”

Krishnaswamy’s repeated references to “semantic representations” and “semantic objects” has Caius dwelling on what is meant here by “semantics.”

As for where humans fit in the Ontology, they navigate it alongside “AI-powered copilots.” Leveraging both open-source and proprietary LLMs, copilots “fluidly navigate across supplier information, stock levels, real-time production metrics, shipping manifests, and customer feedback.”

Granted access not just to the abovementioned data sources, but also to “logic assets” like forecast models, allocation models, and production optimizers, LLM copilots simulate decisions and their outcomes. Staged safely in a “scenario,” the AI’s proposed decision can then be “handed off to a human analyst for final review.”

Caius thinks of the scenario-planning services offered to organizations of an earlier era by Stewart Brand’s consulting firm, the Global Business Network.

Foundry for Crypto is another of Palantir’s offerings, described on the company’s website as “a ‘central brain’ that connects on-chain and off-chain systems, as well as diverse stakeholders, through action-centric workflows.” Much like the Ontology, the Foundry “orchestrates decisions over an integrated foundation of data and logic.”

And in fact, the two are related. The Ontology is the semantic, “digital twin” layer that sits atop the Foundry’s data integration infrastructure. It converts the Foundry’s raw data into actionable, real-world objects, empowering users to model, manage, and automate business operations.

The Foundry does for blockchains what the Ontology does for kill chains.

Caius imagines posts ahead on Commitments, Promises, Blockchains, and True Names.