
Recursively Self-Improving AI & AI Neofactories
๐ Join Sanscritic for an evening of insights into the future of AI! ๐
Explore the next generation of software, physical AI, biotech, and deeptech companies. This event will feature presentations and discussions on:
- Recursively Self-Improving AI
- Metareasoning
- AI Neofactories
๐ Key Highlights:
- Most AI systems today complete a task once. The future lies in systems that evaluate their own work, learn from feedback, and recursively produce better models, datasets, algorithms, simulations, and products.
- Discover how metareasoning can serve as a control layer for these systems, guiding when to simulate, critique, backtrack, experiment, or involve human experts.
- Dive into the rise of AI neofactoriesโAI-native systems that continuously create and enhance intellectual assets such as:
- Simulations
- Datasets
- Models and algorithms
- Product designs
- Scientific hypotheses
- Engineering configurations
- Decision systems
๐ก Discussion Topics:
- What does it mean for an AI system to genuinely improve itself?
- How can simulation lower the cost of building complex AI systems?
- How should self-improving systems be evaluated and controlled?
- Where should human experts remain in the loop?
- What new companies become possible when AI can continuously improve its own outputs and processes?
๐ฅ Who Should Attend:
Founders, AI researchers, engineers, domain experts, simulation builders, robotics and biotech teams, and investors interested in the next generation of AI-native companies.
๐ง About Sanscritic:
Sanscritic builds metareasoning and recursive self-improvement technology for expert work, helping organizations create complex reasoning systems and enabling specialized AI startups to develop self-improving AI products.
๐ Location:
JJ Lake Business Center, 340 E Middlefield Rd, Mountain View, CA 94043, USA
๐๏ธ Admission: Free
JJ Lake Business Center, 340 E Middlefield Rd, Mountain View, CA 94043, USA
Get directionsScan with your camera โ the event opens in the Somo app.









