Our Chief Scientist Correy Kowall’s journey began over 30 years ago with early collaborations with AI pioneers such as Jürgen Schmidhuber at IDSIA. Schmidhuber’s work on neural networks and long short-term memory (LSTM) networks laid the groundwork for modern AI models, emphasizing the importance of memory and context in AI systems.
Fundamental problems with recent developments in AI drove us to explore new architectural adjustments. After decades of research we identified unexplored areas in attention mechanisms related to hallucinations in transformer-based Large Language Models.
Our proprietary research framework is designed to advance artificial intelligence through epistemic cognition, structured data integration, and sentiment-aware embeddings. This research enhances LLM efficiency, contextual adaptation, and decision-making accuracy.
ATOMIZER applies the ATOMIC framework to accelerate fine-tuning and training while significantly reducing GPU costs. ATOMIZER empowers researchers to:
Improve learning efficiency by reducing training time and token use
Measure accuracy, reasoning quality, and energy consumption of fine-tuned models
Scale training across LLMs, custom architectures, and domain-specific AI
Prepare for the future of Agentic & Edge AI
NOLA AI’s research is backed by a growing portfolio of granted and pending patents, covering innovations in scalable AI cognition, neural optimization, and epistemic reasoning. Our intellectual property advances AI efficiency, reliability, and adaptability, ensuring cutting-edge solutions for the future of humanity.
