Watch the first-ever public demonstration of the Universal State Machine (USM) — a revolutionary approach to Artificial Intelligence that redefines how machines learn from experience.
Join @rukmal_w, our Co-Founder and CEO, as he unpacks the foundations of the revolutionary Universal State Machine (USM).
Learn about Infinite Time Turing Machines, Deep Learning, and more.
Watch the first-ever public demonstration of the Universal State Machine (USM) — a revolutionary approach to Artificial Intelligence that redefines how machines learn from experience.
Join @rukmal_w, our Co-Founder and CEO, as he unpacks the foundations of the revolutionary Universal State Machine (USM).
Learn about Infinite Time Turing Machines, Deep Learning, and more.
This talk was recorded at the Software Internals Meetup in Miami, organized by @alexjcomerford and @GrantKurz on October 16, 2024.
https://t.co/yW6RHBwS5S
@benshapiro Why are they "enemies?" No one that works at DeepSeek is an enemy of mine. The fact that they love open-source makes me think I would gel with them quite well.
Following @renxyzinc's announcement yesterday, I will be doing a series of threads diving into the the Infinite Time Turing Machines whitepaper.
To start, what is an Infinite Time Turing Machine (ITTM), and how does understanding them help us build better AI systems?
https://t.co/WQzKx6Ou7U
1/9
Learn more about Ren, Infinite Time Turing Machines, and the USM in our whitepaper!
Whitepaper: https://t.co/gi10PuxfOc
Announcement Blog: https://t.co/nYEN2DAfsg
Ren Homepage: https://t.co/rV7s7s3q1T
#AI#LLMs#MachineLearning#DeepLearning#UniversalStateMachine#USM
4/4
Ren is emerging from stealth with the Universal State Machine (USM) — a new AI framework built on the theoretical foundation of Infinite Time Turing Machines (ITTMs).
The USM offers a scalable, interpretable, and computationally efficient alternative to Deep Learning.
1/4
The USM addresses these challenges with:
✔ A deterministic, fully explainable structure
✔ Real-time learning without retraining
✔ A modular, computationally queryable knowledge graph
The future of AI is not just bigger models — it’s better foundations with the USM.
3/4
LLMs run on a surprisingly old tech stack:
gradient descent
‣ method for finding the minimum of a function
‣ Cauchy, 1847 (177 years ago)
next-token prediction
‣ core learning task for language models
‣ Shannon, 1948 (76 years ago)
autodiff + backpropagation
‣ techniques for efficiently computing gradients
‣ Linnainmaa, 1970 (54 years ago)
adam
‣ optimization algorithm
‣ Kingma et al, 2014 (10 years ago)
transformer
‣ neural network architecture
‣ Vaswani et al, 2017 (7 years ago)