Tag: Scrying

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.

John Dee, as Imagined by Derek Jarman

Among the more fearsome of the precursors to what follows is John Dee, the great Renaissance spymaster, court magician and inventor of the British Empire. Filmmaker Derek Jarman is just one of several artists to have made much of Dee in recent decades. In fact, Dee appears repeatedly throughout Jarman’s oeuvre. We first meet Dee, for instance, in Jarman’s 1978 film Jubilee, where he operates as a kind of early-modern Doc Brown. At Her Majesty’s behest, the Dee of that film works up a spell that sends Queen Elizabeth I 400 years into the future–i.e., to London in the age of punk. And what begins in Jubilee continues in the films that follow, with Dee cropping up again the very next year by way of Shakespeare’s famous magician character Prospero. The latter wields a wand modeled upon Dee’s Monas Hieroglyphica in Jarman’s adaptation of The Tempest (1979). Nor is this the last of Dee’s appearances in Jarman’s catalog. He also turns up as muse, for example, in a film named after Dee and Kelley’s famous scrying experiments, The Angelic Conversation (1987). Nor was Jarman alone in thinking highly of Dee. The latter captured the imaginations of several of Jarman’s contemporaries. To mention just two examples: Dee appears as a character in Michael Moorcock’s Gloriana, or The Unfulfill’d Queen; and comics artist Alan Moore wrote a libretto about him. For Jarman’s own reflections on his interest in Dee and in related topics like alchemy, see his memoir Dancing Ledge.

Saturday February 23, 2019

Sun Ra’s “Space Is The Place” leads me into the mirror-world. I drop down into a seat and scry. One of the oldest known forms of divination. Our social media empires have attempted to capture the worlds on the other sides of our scrying mirrors. This is what shows like Black Mirror have tried to teach us. Students and I have returned to head culture’s first encounters with electronic black mirrors in the budding early days of videogames and personal computers as reflected in “Spacewar: Fanatic Life and Symbolic Death Among the Computer Bums,” a report Stewart Brand wrote for Rolling Stone magazine in December 1972. The piece begins with the conviction that the world is windblown and that change, technological modernity — in a word, “computers” — all of these have been foisted on “the people,” regardless of whether or not “the people” are prepared for it. Within less than half a century following the piece’s publication, most of us would be clutching these objects like gods. Brand’s advice was, “We are as gods and might as well get good at it.” This is the meaning of his Whole Earth Catalog. The medium in that case was indeed the message. The Catalog is significant primarily in terms of its form. A functional blueprint for Revolution is one that provides “Access to Tools.” But why was Brand so nonchalant, I wonder, as all of this began to unfold? Why was he so nonchalant about the effects on neighborhoods IRL as heads began to spend their night-time moments “out of their bodies, computer-projected onto cathode ray tube display screens” (39)?