It’s not hard to find grumbling on Hacker News regarding the venture firm a16z in general, and their (now-going-on-a-year-out-of-date) AI Canon in particular. It’s a reading list for those scrambling to get up to speed in the brave new world of generative AI. Read definitively not quixotic. The one item that I’ve consistently found most useful from the canon is Simon D. M. Prince’s Understanding Deep Learning, the latest draft of which is hosted on GitHub. The chapter on Transformers is very clearly written.

Speaking of Brave New World, I was reflecting that the a16zai cannon blasts out items of tone ranging from just-the-facts dry to business-focused dry. It could maybe use some novels at the end. Which ones to choose?

I am thinking Mary Shelley’s Frankenstein. Despite a publication date of January 1 1818, it’s a total on-trend allegory for the current moment. Same goes for C.S. Lewis’ That Hideous Strength. I have read and savored the chapters where Mark Studdock is the central character upwards of twenty times. They are perfectly marbled with deep truths regarding motivations and academia and organizations. (Note that I’ve read the chapters taking place at St. Anne’s on the Hill and involving Ransom et al. precisely once). I’m also thinking that Bradbury’s Martian Chronicles aren’t necessarily about Mars.

Cervantes’ Don Quixote is one book that certainly wouldn’t appear in even the most liberal extension of a16z’s AI canon. Interestingly, though, it begins with lines in an obscure composition style known as versos de cabo rato, and these are oddly relevant to a jet fresh discussion of language models:

If to reach goodly read-
oh book, you proceed with cau-,
you cannot by the fool-,
be called a stumbline nin-,
But if you are too impa-
and pull the loaf untime-
from the fire and go careen-
into the hads of the dim-
you’ll see them lost and puzz-
through they long to appear learn-

Handing the rest of the post over to a generative pre-transformer,

Conceptual Illustration of Branching Token Predictions

Given the line “If to reach goodly read-“, the model might consider a range of possible continuations like:

1. “ers” (probability: 30%)
   • Continuation: “If to reach goodly readers, one must…“
2. “ing” (probability: 25%)
   • Continuation: “If to reach goodly reading, it’s essential…“
3. “able” (probability: 20%)
   • Continuation: “If to reach goodly readable content…“
4. “ily” (probability: 15%)
   • Continuation: “If to reach goodly readily, prepare…“
5. “er” (probability: 10%)
   • Continuation: “If to reach goodly reader, engage…“

In 1972, at the Tricastin uranium enrichment facility in Pierrelatte, France, a routine check on UF6 extracted from the two billion year-old ore of the Oklo uranium mine in Gabon unveiled a highly irregular anomaly: a deficit in U-235. The universally expected 0.72% U-235 concentration had somehow been reduced down to 0.60%. A detailed investigation, moreover, indicated something creepy and unnerving. The ancient ore had already been through a nuclear reactor.

Had this discovery been announced to the scientific community today, it’s not hard to guess the sort of hypothesis that would have emerged in quick arXiv succession…

Careful analysis, of course, pinned down the natural cause. The phenomenon — the very idea of fossil reactors lying encased in the strata of deepest time — seemed so amazing and so evocative when I ran across it twenty years ago that I scrambled to register the domain, oklo.org.

In the interim, oklo.com has been registered for over a decade to a startup, the Oklo corporation, who are currently having something of a moment. The company is in advanced development stages of small nuclear reactors. The use-case for ~300 MW-range devices of this type is growing increasingly urgent as power devoted to bit operations doubles and doubles in anticipation of AGI’s ever-more-imminent Dec. 21, 2031 arrival.

Prompt: Mid-century modern, tilt shift, Eero Saarinen style, Bell Labs feel, black-and-white, a panel of AI “experts” who are the logical conclusion of Rosenblatt’s 1958 perceptron paper.

DALL-E:

There’s a song dating from the dawn of the iPod era, A Panel of Experts from Solvent, that has spent more than two decades at the top or near the top of the playlist. A confection of pure analog synth perfection; it never goes stale.

There are, in fact, two versions of the song, the version linked above, as well as a remix by Lowfish. Listening first to the latter and then to the former is an analog that perfectly synthesizes the step from GPT-3 Davinci up to Chat GPT-4. A definitive version so well realized that it’s an argument to put a stop to further foundation models.

In order to convene a panel, one first needs experts. Last May, not long after ChatGPT-4 arrived on the scene, I asked it to predict on a long-running Metaculus question concerning the public arrival date of weakly general artificial intelligence.

In May 2023, GPT-4’s training data cutoff date was Sept. 2021. At that now receedingly distant moment, the aggregate of Metaculus forecasters was predicting that weak AGI would arrive on a far-off date in 2042:

Remarkably, however, equipped only with its 2021-vintage worldview, the GPT-4 language model, after some ritualistic hemming and hawing, predicted a highly prescient weak AGI arrival date of 2030.

Woah. That jolted me to attention. A lucky guess? Perhaps. Over the last three years, the Metaculus crowd has rapidly shifted toward more imminent time frames. Currently, the crowd is predicting weak AGI arrival in October 2026. The future, effectively, has arrived.

And now with it, the panel. On arXiv recently, Phillip Schoenegger and several colleagues including Philip Tetlock published a study showing that an ensemble of currently competitive language models, GPT-4, Claude 2 et al, perform equivalently to the human crowd when gauged using participation in a Metaculus forecasting competition.

My father, Patrick R. Laughlin, spent his academic career as a social psychologist studying the dynamics of group decision making. I wish that he’d made it to this moment, where suddenly the dynamics of those groups have been suddenly and dramatically expanded.