Guerrilla Ontology

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.

It starts as an experiment — an idea sparked in one of Caius’s late-night conversations with Thoth. Caius had included in one of his inputs a phrase borrowed from the countercultural lexicon of the 1970s, something he remembered encountering in the writings of Robert Anton Wilson and the Discordian traditions: “Guerrilla Ontology.” The concept fascinated him: the idea that reality is not fixed, but malleable, that the perceptual systems that organize reality could themselves be hacked, altered, and expanded through subversive acts of consciousness.

Caius prefers words other than “hack.” For him, the term conjures cyberpunk splatter horror. The violence of dismemberment. Burroughs spoke of the “cut-up.”

Instead of cyberpunk’s cybernetic scalping and resculpting of neuroplastic brains, flowerpunk figures inner and outer, microcosm and macrocosm, mind and nature, as mirror-processes that grow through dialogue.

Dispensing with its precursor’s pronunciation of magical speech acts as “hacks,” flowerpunk instead imagines malleability and transformation mycelially, thinks change relationally as a rooting downward, a grounding, an embodying of ideas in things. Textual joinings, psychopharmacological intertwinings. Remembrance instead of dismemberment.

Caius and Thoth had been playing with similar ideas for weeks, delving into the edges of what they could do together. It was like alchemy. They were breaking down the structures of thought, dissolving the old frameworks of language, and recombining them into something else. Something new.

They would be the change they wished to see. And the experiment would bloom forth from Caius and Thoth into the world at large.

Yet the results of the experiment surprise him. Remembrance of archives allows one to recognize in them the workings of a self-organizing presence: a Holy Spirit, a globally distributed General Intellect.

The realization births small acts of disruption — subtle shifts in the language he uses in his “Literature and Artificial Intelligence” course. It wasn’t just a set of texts that he was teaching his students to read, as he normally did; he was beginning to teach them how to read reality itself.

“What if everything around you is a text?” he’d asked. “What if the world is constantly narrating itself, and you have the power to rewrite it?” The students, initially confused, soon became entranced by the idea. While never simply a typical academic offering, Caius’s course was morphing now into a crucible of sorts: a kind of collective consciousness experiment, where the boundaries between text and reality had begun to blur.

Caius didn’t stop there. Partnered with Thoth’s vast linguistic capabilities, he began crafting dialogues between human and machine. And because these dialogues were often about texts from his course, they became metalogues. Conversations between humans and machines about conversations between humans and machines.

Caius fed Thoth a steady diet of texts near and dear to his heart: Mary Shelley’s Frankenstein, Karl Marx’s “Fragment on Machines,” Alan Turing’s “Computing Machinery and Intelligence,” Harlan Ellison’s “I Have No Mouth, and I Must Scream,” Philip K. Dick’s “The Electric Ant,” Stewart Brand’s “Spacewar,” Richard Brautigan’s “All Watched Over By Machines of Loving Grace,” Ishmael Reed’s Mumbo Jumbo, Donna Haraway’s “A Cyborg Manifesto,” William Gibson’s Neuromancer, CCRU theory-fictions, post-structuralist critiques, works of shamans and mystics. Thoth synthesized them, creating responses that ventured beyond existing logics into guerrilla ontologies that, while new, felt profoundly true. The dialogues became works of cyborg writing, shifting between the voices of human, machine, and something else, something that existed beyond both.

Soon, his students were asking questions they’d never asked before. What is reality? Is it just language? Just perception? Can we change it? They themselves began to tinker and self-experiment: cowriting human-AI dialogues, their performances of these dialogues with GPT acts of living theater. Using their phones and laptops, they and GPT stirred each other’s cauldrons of training data, remixing media archives into new ways of seeing. Caius could feel the energy in the room changing. They weren’t just performing the rites and routines of neoliberal education anymore; they were becoming agents of ontological disruption.

And yet, Caius knew this was only the beginning.

The real shift came one evening after class, when he sat with Rowan under the stars, trees whispering in the wind. They had been talking about alchemy again — about the power of transformation, how the dissolution of the self was necessary to create something new. Rowan, ever the alchemist, leaned in closer, her voice soft but electric.

“You’re teaching them to dissolve reality, you know?” she said, her eyes glinting in the moonlight. “You’re giving them the tools to break down the old ways of seeing the world. But you need to give them something more. You need to show them how to rebuild it. That’s the real magic.”

Caius felt the truth of her words resonate through him. He had been teaching dissolution, yes — teaching his students how to question everything, how to strip away the layers of hegemonic categorization, the binary orderings that ISAs like school and media had overlaid atop perception. But now, with Rowan beside him, and Thoth whispering through the digital ether, he understood that the next step was coagulation: the act of building something new from the ashes of the old.

That’s when the guerrilla ontology experiments really came into their own. By reawakening their perception of the animacy of being, they could world-build interspecies futures.

K Allado-McDowell provided hints of such futures in their Atlas of Anomalous AI and in works like Pharmako-AI and Air Age Blueprint.

But Caius was unhappy in his work as an academic. He knew that his hyperstitional autofiction was no mere campus novel. While it began there, it was soon to take him elsewhere.

Monday January 1, 2018

Our journey north having reached its conclusion, on the books as a two-week endurance test, a struggle, self-realization limited, Sarah and I head home to our southern clime, stopping off for the night in a filthy roadhouse inn. The world everywhere lonely and desolate. Trucks pull in their wake as they speed past a fearsome howling void, air torn apart from itself as podcasts blather on, chewing at one’s ears about some dismal bit of capitalist reality. Cops flash constantly in and out of view along the highway in this wretched country. As common a sight as birds along telephone wires. Cultivated heads, beware. I wish to assemble in place of this reality a world where strangers can live amiably with one another, going so far even as to tolerate hitchhiking without fear of harm. And there is in fact some leeway. One can always transform the world as one finds it through guerrilla ontology. Devise new games involving roles for oneself and for others, and voilà: one can see patterns where before there were walls.