The RTD platform integrates Equitus.ai's Knowledge Graph Neural Network (KGNN) with IBM Power10 servers and their Matrix Math Accelerator (MMA) capabilities, along with cloud services and racing-specific technologies like Motec, Bosch, and Computational Fluid Dynamics (CFD)[1][3].
The RaceCar/Track/Driver (RTD) program within Advanced Racing.AI leverages these technologies to improve racing performance in the following ways:
Advanced Racing.AI is a platform that integrates several cutting-edge technologies to enhance performance in F1, WEC, and IndyCar racing through its RaceCar/Track/Driver (RTD) program. Here's how it combines various components to improve auto racing:
1. Equitus.ai KGNN and IBM Power10 Servers:
Equitus Corporation is leveraging IBM's latest Power10 servers to revolutionize AI inferencing at the edge[3]. This partnership allows for powerful data processing and analysis capabilities, crucial for real-time decision-making in racing scenarios.
2. Matrix Math Accelerator (MMA):
The MMA technology in IBM Power10 servers accelerates complex mathematical computations, which is essential for processing large amounts of racing data quickly and efficiently.
3. Cloud Services:
Cloud integration enables remote access and analysis of data, facilitating collaboration between trackside personnel and off-site engineers.
4. Motec and Bosch Systems:
These systems provide real-time telemetry and sensor data from the race car, offering crucial information about vehicle performance and driver inputs.
5. Atlas.ti:
While not specifically mentioned in the search results, Atlas.ti could be used for qualitative data analysis, potentially helping teams analyze non-numerical data such as driver feedback or race strategies.
6. Computational Fluid Dynamics (CFD):
CFD simulations run on the powerful IBM Power10 servers to optimize aerodynamic performance and vehicle dynamics.
The RTD program likely integrates these technologies to:
1. Analyze real-time and historical race data to optimize car setup and race strategy.
2. Predict and prevent potential mechanical issues through predictive maintenance.
3. Enhance driver performance through AI-driven analysis of driving techniques and racing lines.
4. Improve aerodynamics and overall vehicle performance through advanced simulations.
5. Optimize pit stop timing and race tactics based on real-time race conditions and competitor data.
While the specific details of Advanced Racing.AI are not provided in the search results, the combination of these technologies creates a comprehensive platform for improving various aspects of auto racing performance. The integration of high-performance computing, AI, and specialized racing technologies allows teams to make data-driven decisions and gain a competitive edge in F1, WEC, and IndyCar racing.
Citations:
[1] https://www.airacingtech.com
[2] https://www.code19.ai
[3] https://www.linkedin.com/posts/equitus_equitus-corporation-and-glickenhaus-racing-activity-7032057358306439168-Qsfz
[4] https://www.formulaedge.org
[5] https://forum.unity.com/register/genesis?error=login_required&state=JunIsPgHYQ27xLVQLdidPIFGMFh9SN5c46L37IMj%3B%2Fthreads%2Fwhich-ai-method-is-used-in-advanced-racing-games.541281%2F
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