Tag: Warfare

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.

Art Degraded, Imagination Denied, Spacewar Governed the Nations

Brand’s words, as always, are worth quoting at length.

“Spacewar as a parable is almost too pat,” he writes. “It was the illegitimate child of the mating of computers and graphic displays. It was part of no one’s grand scheme. It served no grand theory. It was the enthusiasm of irresponsible youngsters. It was disreputably competitive (‘You killed me, Tovar!’). It was an administrative headache. It was merely delightful” (78).

“Yet Spacewar, if anyone cared to notice,” he adds, “was a flawless crystal ball of things to come in computer science and computer use.”

From the game as parable and the parable as crystal ball, Brand extracts eight parameters, eight qualities of Spacewar that have been predictive of things to come:

  1. It was intensely interactive in real time with the computer.
  2. It encouraged new programming by the user.
  3. It bonded human and machine through a responsive broadband interface of live graphics display.
  4. It served primarily as a communication device between humans.
  5. It was a game.
  6. It functioned best on standalone equipment (and disrupted multiple-user equipment).
  7. It served human interest, not machine. (Spacewar is trivial to a computer.)
  8. It was delightful.

What about ChatGPT in the 2020s? Is it, too, a “flawless crystal ball,” predictive of things to come?

How quickly it all changes.

Brand publishes “Spacewar: Symbolic Life and Fanatic Death Among the Computer Bums” in the December 7, 1972 issue of Rolling Stone. Videogame journalism: the first of its kind. That same year, Atari manufactures Pong, the arcade sensation, and Magnavox releases the Magnavox Odyssey, the first commercial home video console.

What is Cybersyn’s “control room for technocrats” compared to Brand’s imagined future of “New Games” and personal computing, with its Bay Area rallying cry, “Computers for the people”?

CIA bests Cybersyn in a space war of a deadlier sort the following September.

Chicago Boys playtest neoliberal algorithms in post-coup Chile. Thatcher and Reagan universalize these programs, making them games people play worldwide.

William Gibson refines the “space” of Spacewar, rechristening it “cyberspace” in his novel Neuromancer.

Spacewar is thenceforth the enframing world-picture.

“Gibson contracts the thought of cyberspace from video-game arcades, watching the motor-stimulation feedback loops, self-designing kill patterns. Dark ecstasies in caverns of accelerating pixels. Before virtual reality became dangerous, it was already military simulation,” note Plant and Land in “Cyberpositive.”

Gibson himself has said as much, acknowledging in interviews that he coined the term ‘cyberspace’ after watching teenagers play Atari-era videogames in a Vancouver arcade. “Their posture seemed to indicate that they really, sincerely believed there was something beyond the screen,” he recalls. “I took that home and tried to come up with a name for it.”

“The matrix has its roots in primitive arcade games, in early graphics programs and military experimentation with cranial jacks,” says a voiceover early in Gibson’s novel, the book’s protagonist Case grokking a doc on “cyberspace” from some searchable multimedia encyclopedia of the future. Storying happens by way of a display screen. “On the Sony,” says the narrator, “a two-dimensional space war faded behind a forest of mathematically generated ferns, demonstrating the spatial possibilities of logarithmic spirals; cold blue military footage burned through, lab animals wired into test systems, helmets feeding into fire control circuits of tanks and war planes.” The voiceover returns to describe what we’ve witnessed:

“Cyberspace. A consensual hallucination experienced daily by billions of legitimate operators, in every nation, by children being taught mathematical concepts … A graphic representation of data abstracted from the banks of every computer in the human system. Unthinkable complexity. Lines of light ranged in the non-space of the mind, clusters and constellations of data. Like city lights, receding…” (Gibson 56-57).

“Spacewar serves Earthpeace,” claims Brand. But the “console cowboys” who settle in this new digital frontier are as competitive and combative as their Westworld forebears.

In trying to account for the violence of these visions, Caius thinks of Ernest Callenbach’s 1975 novel Ecotopia. “Imagine a future that works!” exhorts the blurb on the back of the paperback. Technological autonomy won by way of nuclear-armed secession, Silicon Valley erased from the Pacific Northwest of the book’s imagined future — yet even here, amid Ecotopia’s “steady-state system,” aggression remains ineradicable, remedied only by way of ritual war games and sacrificial violence.

“What about the cross?” asks the book’s narrator, an American journalist named Will Weston, observing the way the people of Ecotopia arrange the bloodied body of a man wounded in the games “in a startlingly crucifix-like way” (Callenbach 93).

“Well, Ecotopia came into existence with a Judeo-Christian heritage,” replies an Ecotopian. “We make the best of it” (96).