4 quotes filed under model / architecture, newest first.
taken together, it appears that for most domains LLMs will continue to look like a cracked intern: quick and effective in the hands of an adult but not given run of the place. most firms will not be able to adopt fully autonomous AI, not for problems of skill issue or lagging technology diffusion but rather for structural reasons seemingly endemic to current architectures.
why i'm still bearish on LLMs after navier-stokes · jay kruer
Think of Jev as a frontier-intelligence function call: unstructured state in, typed probabilistic decisions out.
Introducing System One Models & Jev · hn · Diogo Almeida · 15 September 2026
The comparison between LLM speed and Jev speed is misleading, because they're using autoregression to generate all of the type names, all of the schema, etc. A closer comparison would be if the LLM was purely outputting the raw numbers. Even then, comparisons to LLMs are pointless because you could train a transformer on the same sort of task that Jev is doing and get even better performance yet again, and a smaller model. I suspect this is some form of stripped down diffusion language model.
Despite appearances, perhaps the internal representations of neural networks implicitly realize symbolic structure. In support of this hypothesis, we show that the vector representations of a variety of neural networks can be closely approximated with symbolic structures: we can replace the network's entire representation-generating process with a closed-form equation instantiating a symbolic structure, and the network's behavior remains largely unchanged.
The Emergent Symbolic Structure of Artificial Neural Networks · hn · Yale University · Johns Hopkins University · New York University · Microsoft Research · 30 August 2026
Global workspace theory,4 or GWT, describes the human brain as a collection of specialized modules sharing data through a central, limited capacity bottleneck. Most machine learning architectures already satisfy the first three indicators5 of this theory. However, they consistently fail to implement GWT-4, the requirement for temporal persistence. To address this, we use the framework of computational self-availability, or CSA. This describes a system where internal processing is available as an input to the system itself.
Architecting Awareness: The Hybrid Diffusion-Transformer · Michelle Tilley · 3 April 2026