2025 - Year of the Symbolics Genera on Desktop

Did you knew that symbolics.com was the first Internet domain ever registered?

On March 15, 1985, Symbolics, Inc. registered symbolics.com, making it the first domain ever recorded in the DNS database. Symbolics, Inc. was a Massachusetts-based company that specialized in building Lisp machines—specialized computers designed to efficiently run the Lisp programming language.

neural networks implemented in SEXP (S-expression)-based Lisp systems, like those that could be developed on Symbolics Genera, would struggle to compete with the GPU-accelerated deep learning frameworks we have today (like TensorFlow or PyTorch). This performance gap is due to the fundamental difference in hardware architectures and software optimizations available in the modern era. Let’s break this down.
Why SEXP-Based Neural Networks Were Slower

Lack of Hardware Acceleration:
Lisp machines like those running Genera were built for symbolic computation and AI tasks requiring logical inference and symbolic reasoning.
These machines lacked modern vectorized instructions or massively parallel computation hardware like GPUs or TPUs, which are optimized for matrix multiplications—the core operation in neural networks.

Single-Threaded or Low Parallelism:
Lisp systems were designed for interpretive, high-level symbolic processing, not for exploiting parallelism at the scale required for modern deep learning.

No SIMD/Vectorization:
Symbolics machines didn’t have hardware support for SIMD (Single Instruction, Multiple Data) operations or other optimized numerical computations, which are essential for training large-scale neural networks efficiently.

Dynamic Typing Overhead:
Genera and Lisp machines emphasized flexibility, with dynamic typing and garbage collection. While this made development faster, it added significant runtime overhead, especially for numerical tasks compared to statically typed, highly optimized languages like C++.

Small Data Sizes:
Symbolics systems were built in an era where datasets were tiny by today’s standards. Modern deep learning systems process terabytes of data, requiring highly scalable memory and I/O architectures.

Genera is proprietary crap. Use the real MIT or LMI Lisp machine systems.

Are domains good investments, guys? I've been lately thinking about starting to buy domains that seem to be valuable for someone else to sell it to them at a higher price.

>>5
literally nobody types or remembers domains grandpa