[1]Home [2]About [3]Moonbound From: Robin Sloan
To: the lab
Sent: March 2023

Phase change

An extremely close-up photograph of a snowflake, looking almost architectural. 
[4]Snowflake, Wilson Bentley, ca. 1910

Earlier this week, in [5]my main newsletter, I praised a new project from Matt
Webb. Here, I want to come at it from a different angle.

Briefly: Matt has built the [6]Braggoscope, a fun and useful application for
exploring the archives of the beloved BBC radio show In Our Time, hosted by the
inimitable Melvyn Bragg.

In Our Time only provides HTML pages for each episode — there’s no structured
data, no sense of “episode X is connected to episode Y because of shared
feature Z”.

As Matt explains [7]in his write-up, he fed the plain-language content of each
episode page into the GPT-3 API, cleverly prompting it to extract basic
metadata, along with a few subtler properties — including a Dewey
Decimal number!?

(Explaining how and why a person might prompt a language model is beyond the
scope of this newsletter; you can [8]read up about it here.)

Here’s [9]a bit of Matt’s prompt:

Extract the description and a list of guests from the supplied episode notes from a podcast.

Also provide a Dewey Decimal Classification code and label for the description

Return valid JSON conforming to the following Typescript type definition:

{
  "description": string,
  "guests": {"name": string, "affiliation": string | null}[]
  "dewey_decimal": {"code": string, "label": string},
}

Episode synopsis (Markdown):

{notes}

Valid JSON:

Important to say: it doesn’t work perfectly. Matt reports that GPT-3 doesn’t
always return valid JSON, and if you browse the Braggoscope, you’ll find plenty
of questionable filing choices.

And yet! What a technique. (Matt credits Noah Brier for [10]the insight.)

It fits into a pattern I’ve noticed: while the buzzy application of the
GPT-alikes is chat, the real workhorse might be text transformation.

As Matt writes:

    Sure Google is all-in on AI in products, announcing chatbots to compete
    with ChatGPT, and synthesised text in the search engine. BUT.

    Using GPT-3 as a function call.

    Using GPT-3 as a universal coupling.

    It brings a lot within reach.

    I think the magnitude of this shift … I would say it’s on the order of the
    web from the mid 90s? There was a radical simplification and democratisa
    tion of software (architecture, development, deployment, use) that took
    decades to really unfold.

For me, 2022 and 2023 have presented two thick strands of inquiry: the web and
AI, AI and the web. This is evidenced by the structure of these lab
newsletters, which have tended towards birfucation.

Matt’s thinking is interesting to me because it brings the strands together.

One of the pleasures of HTTP (the original version) is that it’s almost plain
language, though a very simple kind. You can execute an HTTP request “by hand”:
telnet www.google.com 80 followed by GET /.

Language models as universal couplers begin to suggest protocols that really
are plain language. What if the protocol of the GPT-alikes is just a bare TCP
socket carrying free-form requests and instructions? What if the RSS feed of
the future is simply my language model replying to yours when it asks, “What’s
up with Robin lately?”

I like this because I hate it; because it’s weird, and makes me
feel uncomfortable.

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

I think it’s really challenging to find the appropriate stance towards
this stuff.

On one hand, I find critical deflation, of the kind you’ll hear from Ted
Chiang, Simon Willison, and Claire Leibowicz in [11]this recent episode of KQED
Forum, appropriate and useful. The hype is so powerful that any corrective
is welcome.

However! On the critical side, the evaluation of what’s before us isn’t
sufficient; not even close. If we demand humility from AI engineers, then we
ought to match it with imagination.

An important fact about these language models — one that sets them apart from,
say, the personal computer, or the iPhone — is that their capabilities have
been surprising, often confounding, even to their creators.

AI at this moment feels like a mash-up of programming and biology. The program
ming part is obvious; the biology part becomes apparent when you see [12]AI
engineers probing their own creations the way you might probe a mouse in a lab.

The simple fact is: even at the highest levels of theory and practice, no one
knows how these language models are doing what they’re doing.

Over the past few years, in the evolution from GPT-2-alikes to GPT-3-alikes and
beyond, it’s become clear that the “returns to scale”—both in terms of (1) a
model’s size and (2) the scope of its training data — are exponential and
nonlinear. Simply adding more works better, and works weirder, than it should.

The nonlinearity is, to me, the most interesting part. As these models have
grown, they have undergone widely observed “phase changes” in capability, just
as sudden and surprising as water frozen or cream whipped.

At the moment, my deepest engagement with a language model is in a channel on a
Discord server, where our gallant host has set up a ChatGPT-powered bot and
laced a simple personality into its prompt. The sociability has been a 
revelation — multiplayer ChatGPT is much, MUCH more fun than single player — 
and, of course, the conversation tends towards goading the bot, testing its
boundaries, luring it into absurdities.

The bot writes poems, sure, and song lyrics, and movie scenes.

The bot also produces ASCII art, and SVG code, and [13]PICO-8 programs, though
they don’t always run.

I find myself deeply ambivalent, in the original sense of: thinking many things
at once. I’m very aware of the bot’s limitations, but/and I find myself stunned
by its fluency, its range.

Listen: you can be a skeptic. In some ways, I am! But these phase changes have
happened, and that probably means they will keep happening, and no one knows
(the AI engineers least of all) what might suddenly become possible.

As ever, [14]Jack Clark is my guide. He’s a journalist turned AI practioner,
involved in policy and planning at the highest levels, first at OpenAI, now at
Anthropic. And if he’s no longer a disinterested observer, he remains deeply
grounded and moral, which makes me trust him when he says, with confidence:
this is the biggest thing going, and we had all better brace for weird
times ahead.

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

What does that mean, to brace for it?

I’ve found it helpful, these past few years, to frame my anxieties and dissatis
factions as questions. For example, fed up with the state of social media, [15]
I asked: what do I want from the internet, anyway?

It turns out I had an answer to that question.

Where the GPT-alikes are concerned, a question that’s emerging for me is:

What could I do with a universal function — a tool for turning just about any X
into just about any Y with plain language instructions?

I don’t pose that question with any sense of wide-eyed expectation; a reason
able answer might be, nothing much. Not everything in the world depends on the
transformation of symbols. But I think that IS the question, and I think it
takes some legitimate work, some strenuous imagination, to push yourself to
believe it really will be “just about any X” into “just about any Y”.

I help operate [16]a small olive oil company, and I have spent a bit of time
lately considering this question in the context of our business. What might a
GPT-alike do for us? What might an even more capable system do?

My answer, so far, is indeed: nothing much! It’s a physical business, after
all, mainly concerned with moving and transforming matter. The “obvious” appli
cation is customer support, which I handle myself, and which I am unwilling to
cede to a computer or, indeed, anyone who isn’t me. The specific quality and
character of our support is important.

(As an aside: every customer support request I receive is a miniature puzzle,
usually requiring deduction across several different systems. Many of these
puzzles are challenging even to the general intelligence that is me; if it
comes to pass that a GPT-alike can handle them without breaking a sweat, I will
be very, very impressed.)

(Of course, it’s not going to happen like that, is it? Long before GPT-alikes
can solve the same problems Robin can, using the tools Robin has, the problems
themselves will change to meet the GPT-alikes halfway. The systems will all
learn to “speak GPT”, in some sense.)

The simple act of asking and answering the question was clarifying and calming.
It plucked AI out of the realm of abstract dread and plunked it down on
the workbench.

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Jack Clark includes, in all of his AI newsletters, a piece of original
micro-fiction. One of them, [17]sent in December, has stayed with me. I’ll
reproduce it here in full:

    Reality Authentication

    [The internet, 2034]

    “To login, spit into the bio-API”

    I took a sip of water and swirled it around my mouth a bit, then hawked
    some spit into the little cup on my desk, put its lid on, then flipped over
    the receptacle and plugged it into the bio-API system.

    “Authenticating … authentication successful, human-user identified. Enjoy
    your time on the application!”

    I spent a couple of hours logged-on, doing a mixture of work and pleasure.
    I was part of an all-human gaming league called the No-Centaurs; we came
    second in a mini tournament. I also talked to my therapist sans his
    augment, and I sent a few emails over the BioNet protocol.

    When I logged out, I went back to the regular internet. Since the AI models
    had got minituarized and proliferated a decade ago, the internet had
    radically changed. For one thing, it was so much faster now. It was also
    dangerous in ways it hadn’t been before - Attention Harvesters were every
    where and the only reason I was confident in my browsing was I’d paid for a
    few protection programs.

I think “brace for it” might mean imagining human-only spaces, online and off.
We might be headed, paradoxically, for a golden age of “get that robot out of
my face”.

In the extreme case, if AI doesn’t wreck the world, language models could
certainly wreck the internet, like Jack’s Attention Harvesters above. Maybe
we’ll look back at the Web Parenthesis, 1990-2030. It was weird and fun, though
no one in the future will quite understand the appeal.

We are living and thinking together in an interesting time. My recommendation
is to avoid chasing the ball of AI around the field, always a step behind.
Instead, set your stance a little wider and form a question that actually
matters to you.

It might be as simple as: is this kind of capability, extrapolated forward,
useful to me and my work? If so, how?

It might be as wacky as: what kind of protocol could I build around plain
language, the totally sci-fi vision of computers just TALKING to each other?

It might even be my original question, or a version of it: what do I want from
the internet, anyway?

From Oakland,

Robin

March 2023, Oakland

I'm [18]Robin Sloan, a fiction writer. You can sign up for my lab newsletter:

[19][                    ] [20][Subscribe]
This website doesn’t collect any information about you or your reading.
It aspires to the speed and privacy of the printed page.

Don’t miss [21]the colophon. Hony soyt qui mal pence


References:

[1] https://www.robinsloan.com/
[2] https://www.robinsloan.com/about/
[3] https://www.robinsloan.com/moonbound/
[4] https://publicdomainreview.org/essay/the-snowflake-man-of-vermont?utm_source=Robin_Sloan_sent_me
[5] https://www.robinsloan.com/newsletters/ring-got-good/?utm_source=Robin_Sloan_sent_me
[6] https://genmon.github.io/braggoscope/?utm_source=Robin_Sloan_sent_me
[7] https://interconnected.org/home/2023/02/07/braggoscope?utm_source=Robin_Sloan_sent_me
[8] https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-openai-api?utm_source=Robin_Sloan_sent_me
[9] https://news.ycombinator.com/item?id=35073824&utm_source=Robin_Sloan_sent_me
[10] https://brxnd.substack.com/p/the-prompt-to-rule-all-prompts-brxnd?utm_source=Robin_Sloan_sent_me
[11] https://www.kqed.org/forum/2010101892368/how-to-wrap-our-heads-around-these-new-shockingly-fluent-chatbots?utm_source=Robin_Sloan_sent_me
[12] https://www.anthropic.com/index/toy-models-of-superposition-2?utm_source=Robin_Sloan_sent_me
[13] https://www.lexaloffle.com/pico-8.php?utm_source=Robin_Sloan_sent_me
[14] https://importai.substack.com/?utm_source=Robin_Sloan_sent_me
[15] https://www.robinsloan.com/lab/specifying-spring-83/
[16] https://fat.gold/?utm_source=Robin_Sloan_sent_me
[17] https://us13.campaign-archive.com/?u=67bd06787e84d73db24fb0aa5&&id=a03ebcd500&utm_source=Robin_Sloan_sent_me
[18] https://www.robinsloan.com/about?utm_source=Robin_Sloan_sent_me
[21] https://www.robinsloan.com/colophon/
