Industrial Generative AI for
Government, Defense & Intelligence
AI and quantum computing will play a key role in maintaining American competitiveness in the technological sphere. Zapata AI is working closely with the US Department of Defense to benchmark when quantum-enhanced applications will make an impact across various domains.
Process sensor data on the edge in real time to drive smarter decisions.
Sensor data is critical to maintaining situational awareness in contested environments. However, challenges persist in leveraging that data to its full potential. In some cases, physical constraints limit where sensors can be placed. In other mission critical settings, the possibility of sensor failure demands redundancy and fault tolerance. Other challenges include managing the sheer volume and velocity of incoming data, data quality issues, integrating data from various sources, and edge processing. All these challenges must be overcome before applying AI and machine learning to this live streaming data to enhance situational awareness.
Real-time applications for Government, Defense & Intelligence’s most complex industrial-scale challenges
Anomaly Detection
LLM Retrieval
Optimization
Predictive Modeling
Sensor Fusion
Anomaly Detection
LLM Retrieval
Optimization
Predictive Modeling
Sensor Fusion
Key Challenges
Zapata AI Solutions
Predictive Maintenance
Prevent system failure by training an algorithm to proactively identify early warning signs of malfunctions.
Threat Detection
Detect potential threats with greater accuracy by training the detection algorithm with synthetic data simulating possible threat scenarios.
Defense Advanced Research Projects Agency (DARPA)
Quantum computers are poised to deliver an exponential advantage over classical computers but it’s unclear how or when this advantage will arrive. To answer these questions, the Defense Advanced Research Projects Agency (DARPA) of the US Government is funding Zapata AI to develop application-specific benchmark tests using the Orquestra® platform that compare performance across quantum hardware backends and estimate the hardware resources that will be required for different quantum applications.
How can these solutions work for your organization?