As a deep-tech company, we've expanded our R&D capabilities by partnering with leading institutions to accelerate our innovation efforts and reinforce our position at the forefront of technological advancements.

R&D Areas of Focus
  • Developing interfaces and systems that enhance cooperation between humans and AI.

  • Augmenting AI systems with social science, decision theory, and managerial science to improve organizational decision-making.

  • Developing ontologies and schemas that facilitate knowledge representation and retrieval.

  • Developing algorithms for understanding and generating human language.

  • Applied techniques for enabling machines to interpret and process visual data from the world.

  • Developing multi-layered neural networks to learn complex data patterns with high accuracy.

  • Developing frameworks for interpreting, auditing, and validating AI models to ensure reliability and transparency.

  • Developing adaptive learning systems that evolve with changing data distributions and environments.

  • Developing techniques for multivariate time series analysis to understand the relationships between variables.

  • Developing systems that learn optimal behaviors through trial and error interactions with their environment.

  • Implementing graph-based learning algorithms for knowledge graph completion and link prediction tasks.

  • Creating complex systems where autonomous agent interact to simulate real-world scenarios.

  • Enhancing the robustness of generative AI models (e.g., GPT) for enterprise-level reliability and performance.

  • Applying probabilistic reasoning to analyze system variables and address uncertainty in decision-making.

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