Tag: Logic

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.

Binary and Digital

Plant breaks down technology’s binary, bifurcated etymology in her book Zeros + Ones. “Technology,” she writes, “is both a question of logic, the long arm of the law, logos, ‘the faculty which distinguishes parts (“on the one hand and on the other hand”),’ and also a matter of the skills, digits, speeds, and rhythms of techno, engineerings which run with ‘a completely other distribution which must be called nomadic, a nomad nomos, without property, enclosure, or measure’” (Plant 50).

As the quote within her quote indicates, Plant is cribbing here — her source, Gilles Deleuze’s Difference and Repetition.

“The same ambivalence is inscribed in the zeros and ones of computer code,” she adds. “These bits of code are themselves derived from two entirely different sources, and terms: the binary and the digital, or the symbols of a logical identity which does indeed put everything on one hand or the other, and the digits of mathematics, full of intensive potential, which are not counted by hand but on the fingers and, sure enough, arrange themselves in pieces of eight rather than binary pairs” (50).

Deleuze describes this 8-bit digital realm as “demonic rather than divine, since it is a peculiarity of demons to operate in the intervals between the gods’ fields of action…thereby confounding the boundaries between properties” (as quoted in Plant 50).

I offer the above not as a mere gloss on Zeros + Ones, but as a proto-script, a performative utterance that, once spoken, will shift the field of the Library. Amid Plant’s bifurcations — logos and nomos, binary and digital, structure and rhythm—we glimpse a fundamental split not just in technology but in ontology. Logos is the faculty of division, of either/or. But nomos, in Plant’s reading-via-Deleuze, is distributive, nomadic, a practice of rhythm and movement unconfined by enclosure.

The zero and the one: not opposites, but frequencies. Not only dualism, but difference in resonance. This is why the octal — the base-8 system lurking in the shadows of “fingers and digits” — matters so much. Plant’s demons, via Deleuze, operate between gods: between the formal logic of divine Law and the messy, embodied improvisation of demonic desire. They hack the space of logic, opening channels through which minoritarian intensities pulse.

The Language of Birds

My study of oracles and divination practices leads me back to Dale Pendell’s book The Language of Birds: Some Notes on Chance and Divination.

The race is on between ratio and divinatio. The latter is a Latin term related to divinare, “to predict,” and divinus, meaning “to divine” or “pertaining to the gods,” notes Pendell.

To delve deeper into the meaning of divination, however, we need to go back to the Greeks. For them, the term for divination is manteia. The prophet or prophetess is mantis, related to mainomai, “to be mad,” and mania, “madness” (24). The prophecies of the mantic ones are meaningful, insisted thinkers like Socrates, because there is meaning in madness.

What others call “mystical experiences,” known only through narrative testimonies of figures taken to be mantics: these phenomena are in fact subjects of discussion in the Phaedrus. The discussion continues across time, through the varied gospels of the New Testament, traditions received here in a living present, awaiting reply. Each of us confronts a question: “Shall we seek such experiences ourselves — and if so, by what means?” Many of us shrug our shoulders and, averse to risk, pursue business as usual. Yet a growing many choose otherwise. Scientists predict. Mantics aim to thwart the destructiveness of the parent body. Mantics are created ones who, encountering their creator, receive permission to make worlds in their own likeness or image. Reawakened with memory of this world waning, they set to work building something new in its place.

Pendell lays the matter out succinctly, this dialogue underway between computers and mad prophets. “Rationality. Ratio. Analysis,” writes the poet, free-associating his way toward meaning. “Pascal’s adding machine: stacks of Boolean gates. Computers can beat grandmasters: it’s clear that logical deduction is not our particular forte. Madness may be” (25). Pendell refers on several occasions to computers, robots, and Turing machines. “Alan Turing’s oracles were deterministic,” he writes, “and therefore not mad, and, as Roger Penrose shows, following Gödel’s proof, incapable of understanding. They can’t solve the halting problem. Penrose suggests that a non-computational brain might need a quantum time loop, so that the results of future computations are available in the present” (32).