WEBVTT
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Hi everyone!
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My name is Shane,
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and it's truly a real honor to be
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able to speak at EmacsConf.
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I love Emacs. I love Emacs Lisp,
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and this is also another topic
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that really excites me ever since
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I got my hands on OpenAI's GPT-3.
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Six months ago, I knew that it was
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important to research this for Emacs,
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you know, asides from being somebody
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who never wants to leave Emacs myself,
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and I hope that….
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Being one of the few Emacs users,
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possibly the only one that had
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access to GPT-3 for this long,
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I hope that I can contribute.
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So, Emacs, sorry.
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Imaginary programming is…,
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it's based on prompt engineering currently,
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but it's an abstraction over
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prompt engineering.
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You can read about prompt engineering
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and language models,
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that's quite easy to google for.
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And imaginary programming is a subfield
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of imaginary computing,
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which is just the larger domain
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of employing of computing
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that's based on imagination,
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artificial imagination,
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so, basically, dreaming up user interfaces
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instead of…, or at least partially
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dreaming them up.
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I suppose that it's a fringe paradigm,
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but it's extremely useful.
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Imaginary computing,
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if you're willing to call it that,
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would be what's used to
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imagine simulations
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for self-driving cars,
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as they're trained for example.
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But this technology finds
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its way to the public,
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and it should be in the public domain.
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So, Demis Hassabis
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he's the founder of DeepMind,
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and he did his Ph.D. in human imagination,
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now he's working on artificial imagination.
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So, just a couple of days ago
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I took AlephAlpha's world model API
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and I plugged it into Emacs's eww browser,
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and now I have a way of generating
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text for the images instead of actually…,
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so I can stay in my text only Emacs,
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which is the way it should be.
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Intelligent NFTs, I'll leave this
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for you guys to look at.
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Information bubbles.
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So, there's some potential bad outcomes
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from the runaway empowering of these
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large language models and other models
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in commercial hands.
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It's causing information bubbles and
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ways of controlling people.
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So, for example,
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micro tasks and stuff that…,
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furthermore just automating away,
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or abstracting away the role
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of a programmer,
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and the automating more and more
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increasingly abstract tasks,
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and I think the solution is to
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decentralize and break up these tasks.
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I have a potential way of doing that,
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but firstly I'll talk about
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the imaginary web briefly
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because the thing about these
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language models is,
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they can replace basically
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everything on the internet.
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So, like, replace your Wikipedia,
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or Stack Overflow,
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replace conversation if you want it with,
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from real people to chatbots instead,
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replace basically anything there's
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a website for.
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And that means that rich media has gone
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from becoming images and video
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and even from paywalls
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now into intelligent and truthful,
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because generating fictional websites
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is going to become a very easy thing to do,
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and actually the best way to do it,
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and the most useful way to do it,
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so then you need a source of truth.
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The imaginary web is a thing,
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imaginary interpreters are a thing,
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so you imagine your interpreter,
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or you overlay prompting on top of
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a real interpreter to see
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what you might want to do
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in an interpreter,
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and what you might want to say to somebody
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if you're talking to them.
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If you're inside, say,
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ERC in Emacs, an IRC client,
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and you prompt after somebody
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says something,
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then the prompt will probably suggest,
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what you might say in return,
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and then you can prompt like a multiverse,
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and you can pick from them.
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There's a bunch of crazy utilities
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for these language models.
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Paracosm vs Metaverse.
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So, Mark Zuck wants you to live in
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his virtual reality as defined by him,
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and he's going to do it
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by using these models to make you
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a fictional world that you can live in.
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You can do that,
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or you can use them yourself,
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and you build your own Paracosm.
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And I think that's an important
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ability to be able to have,
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otherwise we will be like the borg,
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and we'll be connected to Mark Zuckerberg.
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Truth is a hot topic.
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So, the way that I think we should do this
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to decentralize the language models is,
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to use Structuralism.
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Universal grammar,
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template metaprogramming, and GPT-3
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what do they have in common?
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Well, you have some kind of basis,
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like, you train your GPT-3,
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and then you do all your prompting
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on top of it.
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Like a person is born with this grammar,
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and then they quickly learn language,
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and like with C++ templates,
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you pre-process and then
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the run time runs on that.
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So, anyway, that was a slide.
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Structuralism.
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I think you can decompile…,
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think you can break,
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so you can decompose
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the language models into units,
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but those units won't look like neurons,
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they would look like these,
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and you put them onto a blockchain.
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But you can look at that later
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if you want anyway.
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I'm going to skip straight to ilambda,
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running out of time.
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I'll just quickly show you
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the ilambda primitive in ilambda.
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So, it evaluates instead of run,
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for example, here's the reduced function,
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and you've defined your
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imaginary lambda here.
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And it doesn't have a body,
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it's just got the comment
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and the parameters,
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and that's enough for….
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Once you have that ilambda
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that runs now as a function,
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you can stick it into
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a reduced function, for example,
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and it'll reduce this list.
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You could even remove…, yeah,
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so you kind of need the comment
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otherwise it's too hard to imagine
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what would happen next,
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but for a function you can literally
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have an idefun even without
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the argument list.
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It was just like generate-fib-sequence,
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and most likely when you run that defun,
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it would work the way you want it.
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The more information you give the idefun,
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the imaginary defun,
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the better it would capture the task
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which you're trying to do,
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in this case you want to generate
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a Fibonacci sequence.
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And yeah, you can define functions
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without having a body,
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and they run an inference instead.
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Here's a way of overriding
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the language model that's used,
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for example, using dynamic scope.
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So, under the hood,
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idefun just uses an ilambda.
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This function here just doubles things.
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So, here's a function that gets you
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a hexadecimal color just from the name.
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And you can create
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arbitrary functions like this,
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so, what we need is like a library
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of imaginary functions, I think,
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that match a language model.
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Macros on the other hand,
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as different from functions,
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they actually macro expand
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and generate code.
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So, when you macro expand this,
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you'll get this,
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and that's because this has an arity of 3,
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and then when you macro expand
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that underlying macro,
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it generates the actual source code.
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You can actually run these macros,
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and it will cache the output…,
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it will catch the source code,
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so the macro runs the same
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every single time,
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or generates the same code,
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but you can just use it
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to generate code really easily
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while you're programming.
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I hope that this has been informative,
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it wasn't too much time,
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but there's plenty of material
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for you to dig into it more
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if you're interested.
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Thank you very much
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for letting me talk today.
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Peace out!
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[captions by bhavin192 (Bhavin Gandhi)]
