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Culture War Roundup for the week of April 17, 2023

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You might be interested in this post on LessWrong which discusses Scaffolded LLM's as natural language computers.. I'd be curious on @DaseindustriesLtd's take on this as well.

Key points:

What we have essentially done here is reinvented the von-Neumann architecture and, what is more, we have reinvented the general purpose computer. This convergent evolution is not surprising -- the von-Neumann architecture is a very natural abstraction for designing computers. However, if what we have built is a computer, it is a very special sort of computer. Like a digital computer, it is fully general, but what it operates on is not bits, but text. We have a natural language computer which operates on units of natural language text to produce other, more processed, natural language texts. Like a digital computer, our natural language (NL) computer is theoretically fully general -- the operations of a Turing machine can be written as natural language -- and extremely useful: many systems in the real world, including humans, prefer to operate in natural language. Many tasks cannot be specified easily and precisely in computer code but can be described in a sentence or two of natural language.

The LLM itself is clearly equivalent to the CPU. It is where the fundamental 'computation' in the system occurs. However, unlike the CPU, the units upon which it operates are tokens in the context window, not bits in registers. If the natural type signature of a CPU is bits -> bits, the natural type of the natural language processing unit (NLPU) is strings -> strings.

The RAM is just the context length. GPT4 currently has an 8K context or an 8kbit RAM (theoretically expanding to 32kbit soon). This gets us to the Commodore 64 in digital computer terms, and places us in the early 80s.


The obvious thing to think about when programming a digital computer is the programming language. Can there be programming languages for NL computers? What would they look like? Clearly there can be. We are already beginning to build up the first primitives. Chain of thought. Selection-inference. Self-correction loops. Reflection. These sit at a higher level of abstraction than a single NLOP. We have reached the assembly languages. CoT, SI, reflection, are the mov, leq, and goto, which we know and love from assembly. Perhaps with libraries like langchains and complex prompt templates, we are beginning to build our first compilers, although they are currently extremely primitive.

I find this framing extremely persuasive, and awesome in the true sense. If transformers can actually act as a new type of general purpose computer using natural language, the world will become strange indeed very quickly.