Observer Theory

The Concept of the Observer

We call it perception. We call it measurement. We call it analysis. But in the end it’s about how we take the world as it is, and derive from it the impression of it that we have in our minds.

We might have thought that we could do science “purely objectively” without any reference to observers or their nature. But what we’ve discovered particularly dramatically in our Physics Project is that the nature of us as observers is critical even in determining the most fundamental laws we attribute to the universe.

But what ultimately does an observer—say like us—do? And how can we make a theoretical framework for it? Much as we have a general model for the process of computation—instantiated by something like a Turing machine—we’d like to have a general model for the process of observation: a general “observer theory”. Continue reading

Aggregation and Tiling as Multicomputational Processes

Aggregation and Tiling as Multicomputational Processes

The Importance of Multiway Systems

It’s all about systems where there can in effect be many possible paths of history. In a typical standard computational system like a cellular automaton, there’s always just one path, defined by evolution from one state to the next. But in a multiway system, there can be many possible next states—and thus many possible paths of history. Multiway systems have a central role in our Physics Project, particularly in connection with quantum mechanics. But what’s now emerging is that multiway systems in fact serve as a quite general foundation for a whole new “multicomputational” paradigm for modeling.

My objective here is twofold. First, I want to use multiway systems as minimal models for growth processes based on aggregation and tiling. And second, I want to use this concrete application as a way to develop further intuition about multiway systems in general. Elsewhere I have explored multiway systems for strings, multiway systems based on numbers, multiway Turing machines, multiway combinators, multiway expression evaluation and multiway systems based on games and puzzles. But in studying multiway systems for aggregation and tiling, we’ll be dealing with something that is immediately more physical and tangible. Continue reading

How to Think Computationally about AI, the Universe and Everything

Transcript of a talk at TED AI on October 17, 2023, in San Francisco

Human language. Mathematics. Logic. These are all ways to formalize the world. And in our century there’s a new and yet more powerful one: computation.

And for nearly 50 years I’ve had the great privilege of building an ever taller tower of science and technology based on that idea of computation. And today I want to tell you some of what that’s led to.

There’s a lot to talk about—so I’m going to go quickly… sometimes with just a sentence summarizing what I’ve written a whole book about. Continue reading

Expression Evaluation and Fundamental Physics

Expression Evaluation and Fundamental Physics

An Unexpected Correspondence

Enter any expression and it’ll get evaluated:

And internally—say in the Wolfram Language—what’s going on is that the expression is progressively being transformed using all available rules until no more rules apply. Here the process can be represented like this:

We can think of the yellow boxes in this picture as corresponding to “evaluation events” that transform one “state of the expression” (represented by a blue box) to another, eventually reaching the “fixed point” 12.

And so far this may all seem very simple. But actually there are many surprisingly complicated and deep issues and questions. For example, to what extent can the evaluation events be applied in different orders, or in parallel? Does one always get the same answer? What about non-terminating sequences of events? And so on. Continue reading

Remembering Doug Lenat (1950–2023) and His Quest to Capture the World with Logic

Logic, Math and AI

In many ways the great quest of Doug Lenat’s life was an attempt to follow on directly from the work of Aristotle and Leibniz. For what Doug was fundamentally trying to do over the forty years he spent developing his CYC system was to use the framework of logic—in more or less the same form that Aristotle and Leibniz had it—to capture what happens in the world. It was a noble effort and an impressive example of long-term intellectual tenacity. And while I never managed to actually use CYC myself, I consider it a magnificent experiment—that if nothing else ultimately served to demonstrate the importance of building frameworks beyond logic alone in usefully representing and reasoning about the world. Continue reading

Remembering the Improbable Life of Ed Fredkin (1934–2023) and His World of Ideas and Stories

Programmer of the Universe

Click to enlarge

“OK, so let me tell you…” And so it would begin. A long and colorful story. An elaborate description of a wild idea. In the forty years I knew Ed Fredkin I heard countless wild ideas and colorful stories from him. He always radiated a certain adventurous joy—together with supreme, almost-childlike confidence. Ed was someone who wanted to independently figure things out for himself, and delighted in presenting his often somewhat-outlandish conclusions—whether about technology, science, business or the world—with dramatic showman-like panache.

In all the years I knew Ed, I’m not sure he ever really listened to anything I said (though he did use tools I built). He used to like to tell people I’d learned a lot from him. And indeed we had intellectual interests that should have overlapped. But in actuality our ways of thinking about them mostly didn’t connect much at all. But at a personal and social level it was still always a lot of fun being around Ed and being exposed to his unique intense opportunistic energy—with its repeating themes but ever-changing directions. Continue reading

Generative AI Space and the Mental Imagery of Alien Minds

Click on any image in this post to copy the code that produced it and generate the output on your own computer in a Wolfram notebook.

Generative AI Space and the Mental Imagery of Alien Minds

AIs and Alien Minds

How do alien minds perceive the world? It’s an old and oft-debated question in philosophy. And it now turns out to also be a question that rises to prominence in connection with the concept of the ruliad that’s emerged from our Wolfram Physics Project.

I’ve wondered about alien minds for a long time—and tried all sorts of ways to imagine what it might be like to see things from their point of view. But in the past I’ve never really had a way to build my intuition about it. That is, until now. So, what’s changed? It’s AI. Because in AI we finally have an accessible form of alien mind. Continue reading

LLM Tech and a Lot More: Version 13.3 of Wolfram Language and Mathematica

LLM Tech and a Lot More: Version 13.3 of Wolfram Language and Mathematica

The Leading Edge of 2023 Technology … and Beyond

Today we’re launching Version 13.3 of Wolfram Language and Mathematica—both available immediately on desktop and cloud. It’s only been 196 days since we released Version 13.2, but there’s a lot that’s new, not least a whole subsystem around LLMs.

Last Friday (June 23) we celebrated 35 years since Version 1.0 of Mathematica (and what’s now Wolfram Language). And to me it’s incredible how far we’ve come in these 35 years—yet how consistent we’ve been in our mission and goals, and how well we’ve been able to just keep building on the foundations we created all those years ago. Continue reading

Introducing Chat Notebooks: Integrating LLMs into the Notebook Paradigm

This is part of an ongoing series about our LLM-related technology:ChatGPT Gets Its “Wolfram Superpowers”!Instant Plugins for ChatGPT: Introducing the Wolfram ChatGPT Plugin KitThe New World of LLM Functions: Integrating LLM Technology into the Wolfram LanguagePrompts for Work & Play: Launching the Wolfram Prompt RepositoryIntroducing Chat Notebooks: Integrating LLMs into the Notebook Paradigm

Introducing Chat Notebooks: Integrating LLMs into the Notebook Paradigm

A New Kind of Notebook

We originally invented the concept of “Notebooks” back in 1987, for Version 1.0 of Mathematica. And over the past 36 years, Notebooks have proved to be an incredibly convenient medium in which to do—and publish—work (and indeed, I, for example, have created hundreds of thousands of them). And, yes, eventually the basic concepts of Notebooks were widely copied—though still not even with everything we had back in 1987!

Well, now there’s a new challenge and opportunity for Notebooks: integrating LLM functionality into them. It’s an interesting design problem, and I’m pretty pleased with what we’ve come up with. And today we’re introducing Chat Notebooks as a new kind of Notebook that supports LLM-based chat functionality. Continue reading

Prompts for Work & Play: Launching the Wolfram Prompt Repository

This is part of an ongoing series about our LLM-related technology:ChatGPT Gets Its “Wolfram Superpowers”!Instant Plugins for ChatGPT: Introducing the Wolfram ChatGPT Plugin KitThe New World of LLM Functions: Integrating LLM Technology into the Wolfram LanguagePrompts for Work & Play: Launching the Wolfram Prompt RepositoryIntroducing Chat Notebooks: Integrating LLMs into the Notebook Paradigm

Prompts for Work & Play: Launching the Wolfram Prompt Repository

Building Blocks of “LLM Programming”

Prompts are how one channels an LLM to do something. LLMs in a sense always have lots of “latent capability” (e.g. from their training on billions of webpages). But prompts—in a way that’s still scientifically mysterious—are what let one “engineer” what part of that capability to bring out. Continue reading