Tag: Israel

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.

God Human Animal Machine

Wired columnist Meghan O’Gieblyn discusses Norbert Wiener’s God and Golem, Inc. in her 2021 book God Human Animal Machine, suggesting that the god humans are creating with AI is a god “we’ve chosen to raise…from the dead”: “the God of Calvin and Luther” (O’Gieblyn 212).

“Reminds me of AM, the AI god from Harlan Ellison’s ‘I Have No Mouth, and I Must Scream,’” thinks Caius. AM resembles the god that allows Satan to afflict Job in the Old Testament. And indeed, as O’Gieblyn attests, John Calvin adored the Book of Job. “He once gave 159 consecutive sermons on the book,” she writes, “preaching every day for a period of six months — a paean to God’s absolute sovereignty” (197).

She cites “Pedro Domingos, one of the leading experts in machine learning, who has argued that these algorithms will inevitably evolve into a unified system of perfect understanding — a kind of oracle that we can consult about virtually anything” (211-212). See Domingos’s book The Master Algorithm.

The main thing, for O’Gieblyn, is the disenchantment/reenchantment debate, which she comes to via Max Weber. In this debate, she aligns not with Heidegger, but with his student Hannah Arendt. Domingos dismisses fears about algorithmic determinism, she says, “by appealing to our enchanted past” (212).

Amid this enchanted past lies the figure of the Golem.

“Who are these rabbis who told tales of golems — and in some accounts, operated golems themselves?” wonders Caius.

The entry on the Golem in Man, Myth, and Magic tracks the story back to “the circle of Jewish mystics of the 12th-13th centuries known as the ‘Hasidim of Germany.’” The idea is transmitted through texts like the Sefer Yetzirah (“The Book of Creation”) and the Cabala Mineralis. Tales tell of golems built in later centuries, too, by figures like Rabbi Elijah of Chelm (c. 1520-1583) and Rabbi Loew of Prague (c. 1524-1609).

The myth of the golem turns up in O’Gieblyn’s book during her discussion of a 2004 book by German theologian Anne Foerst called God in the Machine.

“At one point in her book,” writes O’Gieblyn, “Foerst relays an anecdote she heard at MIT […]. The story goes back to the 1960s, when the AI Lab was overseen by the famous roboticist Marvin Minsky, a period now considered the ‘cradle of AI.’ One day two graduate students, Gerry Sussman and Joel Moses, were chatting during a break with a handful of other students. Someone mentioned offhandedly that the first big computer which had been constructed in Israel, had been called Golem. This led to a general discussion of the golem stories, and Sussman proceeded to tell his colleagues that he was a descendent of Rabbi Löw, and at his bar mitzvah his grandfather had taken him aside and told him the rhyme that would awaken the golem at the end of time. At this, Moses, awestruck, revealed that he too was a descendent of Rabbi Löw and had also been given the magical incantation at his bar mitzvah by his grandfather. The two men agreed to write out the incantation separately on pieces of paper, and when they showed them to each other, the formula — despite being passed down for centuries as a purely oral tradition — was identical” (God Human Animal Machine, p. 105).

Curiosity piqued by all of this, but especially by the mention of Israel’s decision to call one of its first computers “GOLEM,” Caius resolves to dig deeper. He soon learns that the computer’s name was chosen by none other than Walter Benjamin’s dear friend (indeed, the one who, after Benjamin’s suicide, inherits the latter’s print of Paul Klee’s Angelus Novus): the famous scholar of Jewish mysticism, Gershom Scholem.

When Scholem heard that the Weizmann Institute at Rehovoth in Israel had completed the building of a new computer, he told the computer’s creator, Dr. Chaim Pekeris, that, in his opinion, the most appropriate name for it would be Golem, No. 1 (‘Golem Aleph’). Pekeris agreed to call it that, but only on condition that Scholem “dedicate the computer and explain why it should be so named.”

In his dedicatory remarks, delivered at the Weizmann Institute on June 17, 1965, Scholem recounts the story of Rabbi Jehuda Loew ben Bezalel, the same “Rabbi Löw of Prague” described by O’Gieblyn, the one credited in Jewish popular tradition as the creator of the Golem.

“It is only appropriate to mention,” notes Scholem, “that Rabbi Loew was not only the spiritual, but also the actual, ancestor of the great mathematician Theodor von Karman who, I recall, was extremely proud of this ancestor of his in whom he saw the first genius of applied mathematics in his family. But we may safely say that Rabbi Loew was also the spiritual ancestor of two other departed Jews — I mean John von Neumann and Norbert Wiener — who contributed more than anyone else to the magic that has produced the modern Golem.”

Golem I was the successor to Israel’s first computer, the WEIZAC, built by a team led by research engineer Gerald Estrin in the mid-1950s, based on the architecture developed by von Neumann at the Institute for Advanced Study in Princeton. Estrin and Pekeris had both helped von Neumann build the IAS machine in the late 1940s.

As for the commonalities Scholem wished to foreground between the clay Golem of 15thC Prague and the electronic one designed by Pekeris, he explains the connection as follows:

“The old Golem was based on a mystical combination of the 22 letters of the Hebrew alphabet, which are the elements and building-stones of the world,” notes Scholem. “The new Golem is based on a simpler, and at the same time more intricate, system. Instead of 22 elements, it knows only two, the two numbers 0 and 1, constituting the binary system of representation. Everything can be translated, or transposed, into these two basic signs, and what cannot be so expressed cannot be fed as information to the Golem.”

Scholem ends his dedicatory speech with a peculiar warning:

“All my days I have been complaining that the Weizmann Institute has not mobilized the funds to build up the Institute for Experimental Demonology and Magic which I have for so long proposed to establish there,” mutters Scholem. “They preferred what they call Applied Mathematics and its sinister possibilities to my more direct magical approach. Little did they know, when they preferred Chaim Pekeris to me, what they were letting themselves in for. So I resign myself and say to the Golem and its creator: develop peacefully and don’t destroy the world. Shalom.”

GOLEM I