Synthetic Models
Synthetic Models: Modular Deep Reasoning and Large Concept Models
Learn how we've replicated advanced deep reasoning models and built Synthetic Large Concept Models (SLCMs).
Recent advances in artificial intelligence have pushed the boundaries of what large language models can achieve. Despite these impressive capabilities, even the most powerful models are constrained by a single-pass prompt-to-response paradigm.
Replicating Deep Reasoning Models
Our initial breakthrough was to replicate the behavior of advanced deep reasoning models, including DeepSeek-R1, GPT-O1, and GPT-O3. We synthesized these recursive behaviors by fine-tuning existing models and overlaying them with externally imposed recursive loops.
Synthetic Large Concept Models (SLCMs)
Three specialized AI agents work in tandem: one generates questions, another identifies relationships, and a third brainstorms ideas. The outputs are aggregated and enhanced via vector storage retrieval augmented generation (RAG).
Modular Integration
- Model-Agnostic Integration
- Modularity
- Cost-Efficiency
- Flexibility in Deployment
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