The mathematical foundations of modern AI β attention mechanisms, embedding-based retrieval, and sequential prediction β were derived analytically and patented by Science Counter Inc in 2009. The industry arrived at the same methods independently. Independently is not the same as first.
The AIT framework derives transformer attention as one specific instance of COP β where the context window defines the order of the participation matrix, and the learned query/key projections are the trained equivalent of what AIT derives in closed form analytically.
Multi-head attention is multiple instances of COP running in parallel. Word and token embeddings are specific instances of the COP matrix derived from participation structure β filed four years before word2vec was published. Sequential prediction via SPM(Ο) covers causal language modeling and next-token prediction as derived forms of the participation framework.
Priority date: November 10, 2009.
Single-head, multi-head, and stacked attention β all as instances of COP with different participation matrix configurations.
Distributed vector representations derived from co-occurrence structure β word2vec, GloVe, and their successors as specific instances of the participation framework.
Causal language modeling, next-token prediction, and sequential generation via SPM(Ο) β the causal form of COP.
Nov 10, 2009
Science Counter Inc files foundational AIT patent. COP, ASM, PM_kl derived analytically. No training. No neural networks. First principles.
2013
word2vec published by Mikolov et al. at Google. Distributed word representations from co-occurrence β a specific instance of the COP framework, independently derived 4 years later.
2014
GloVe published by Pennington et al. at Stanford. Another specific instance of the participation framework.
2017
Attention Is All You Need published at Google. Transformer attention β a specific instance of COP with learned weighting β becomes the industry standard. 8 years after AIT was filed.
2018βpresent
GPT, BERT, LLaMA, Gemini, Claude, and the entire transformer-based AI industry. All using methods within the scope of the 2009 portfolio.
The same technology that powers your AI systems was derived analytically and patented in 2009. We are not asking you to stop what you are doing. We are inviting you to do it on a licensed basis.