More data than ever is available on car use. Through digital connectors, carmakers are now able to leverage this data for advanced predictive models to find performance flaws before they go to market. ML can save auto-makers millions of dollars and even save lives. The frontier of transportation innovation begins with smarter, safer cars produced from cutting edge machine learning technology.
Invest in automotive innovation with state-of-the-art machine learning. Make smarter, safer, and more efficient cars than your competitors with advanced ML applications. Build advanced driver assistance features like lane sensors, parking guidance, predictive maintenance alerts, and autonomous vehicles. Lead the industry in innovation with a head start in ML.
From generating and managing the manufacturing schedule more efficiently, to upgrades in safety testing and recognizing defective components in the production line, machine learning has become indispensable in car manufacturing.
Machine learning is utilized in supply chain analytics to plan shipping and reduce associated risks, as well as rank suppliers according to their performance and impact on the chain of supply, resulting in greater efficiency and an overall leaner organization.
Machine learning is one of the major components in any self-driven car. In order to make autonomous driving a reality, carmakers must prioritize machine learning with cutting edge image recognition and peak accuracy.
Automatically identify anomalies in manufacturing parts using computer vision and machine learning algorithms. Save millions of dollars and lives by recalling faulty parts from reaching the manufacturing process.
Leverage real-time traffic data for groundbreaking navigation systems. Mimic human navigation with neural networks and reinforcement learning to build state of the art navigation systems that optimize travel from A to B.
Enable rapid root cause analysis with AI to improve quality and reduce downtime in automotive manufacturing. Perform predictive maintenance to identify machinery that might contribute to downtime before it happens. Integrate process, quality and part data to enable traceability and minimize rejects.
Lead the industry in a more efficient transportation solution with a solution to serve unmet demand for transport operators. Build dynamic applications that improve transportation pain points with demand-driven models to improve commuter experience.