Transformers as Mathematical Optimization
March 26, 2023
Chatbot fashion can change while the Transformer remains a foundational mathematical machine. Its attention layers, learned representations, and massive optimization make it a durable method for fitting and transforming high-dimensional structure.
Brian Greenforest connects that machinery to autoencoding, variational principles, optimal control, consumer models, and hardware designed specifically for Transformer arithmetic.
Treat the Transformer as a Function Machine
Training selects parameters that minimize an objective across immense data. The resulting network composes dynamic weighting, nonlinear transforms, normalization, and residual structure into a reusable approximation engine.
That perspective links Transformers with Euler-Lagrange equations, Pontryagin-style control, and other optimization frameworks without reducing the architecture to conversational output.
Build the Hardware Around the Mathematics
Matrix multiplication, fused multiply-add, attention, normalization, memory movement, and sampling define the real workload. Specialized chips can organize those operations with far greater efficiency than a generic instruction stream.
Mathematicians, chip designers, and product builders can use the Transformer as a common platform: improve the objective, reveal the mechanism, and run it on hardware that fits its structure.
Run Transformers as Mathematical Optimization in a Four-Layer Transformer
The complete training run connects this mathematical argument to executable code, data flow, and a working small model.
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Chatbots can hype and fade, AGI hype will dissipate. The Autoencoder built on Transformers forever will remain more efficient method of mathematical optimization to solve Euler-Lagrange equations, to calculate multiversal intereference effects of consumer thought models, to apply Pontryagin's maximum principle (DRL doesn't scale, as you know, and CNN aren't required anymore). The hardware to run Transformers more efficiently does exist, and will become more prevalent. Our ability to predict and control user behavior is going to improve trillionfold. ChatGPT is not about emerging AIs, it's about more stable hierarchical word government, the very thing Elon Musk is worried about. Emergence of the new evolved lifeform. The Digital Neural System, envisioned by Bill Gates.
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Comments added by Brian Greenforest on LinkedIn
This comment was also preserved verbatim from Brian Greenforest’s LinkedIn data export or the public post page.
Comment 1 · (2023-03-26 17:30:08 UTC)
View the LinkedIn post