We are entering the era where LLMs are being trained on data generated by other LLMs. I’m starting to see "semantic collapse" in some of the smaller models. In our internal testing, reasoning capabilities for edge-case logic are stagnating be…

Everyone is chasing larger context windows (1M+), but the retrieval accuracy (Needle In A Haystack) is still sub-optimal for professional use. I’m theorizing that we’re hitting a physical limit of the Transformer architecture. The future isn't a &q…

As we scale to GPT-5.2 and beyond, the energy footprint of centralized data centers in the US is becoming a physical limit. I'm theorizing that the next step isn't "bigger models," but smarter routing to specialized, regionally-hosted…