Hi, my name is Russ. I'm the business development leader for manufacturing here at NetApp. My role is to apply technologies and services in solutions that will be impactful to your business. I work with technology and industry partners to position NetApp capabilities in joint go to market solutions. Smart manufacturing, industry 4.0, everyone seeking to improve business outcomes. No matter what your starting level is, how is AI going to help you? Deep learning machine learning has reached um a level of maturity where many use cases now far exceed the accuracy and throughput performance of manual inspections. So where is AI being applied in manufacturing environments? AI is in use cases like predictive and prescriptive maintenance, leveraging more sensors at higher sample rates, running more sophisticated trend analytics, not only identifying anomalies earlier, but also advising on established best practices and courses of actions to identify problems. The goal minimizing unplanned downtime conducting maintenance only when it's necessary where it's necessary and product quality control using high resolution imagery uh video to inspect each product that's produced or assembled at a higher degree of detail and throughput performance. Now every product produced can be inspected without bias or oversight. Identifying and addressing problems early in the production cycle minimizes quality issues reaching your customers and also in supply management. Tightly integrating raw materials inventory to production line output to vendor management, financial and other business systems.The result is real-time inventory, full transparency and responsiveness with your vendors, partners and your customers.And of course, worker environment, health and safety monitoring systems are being deployed to advise on all aspects of worker physical environment, their efficiency, their need for training and support. AI is making workers job on a production line safer and more efficient.All these benefits and more are well documented in success stories across multiple manufacturing industries. But there have been cases whereby the benefits aren't realized. Why is that? Implementing new AI processes requires you to look holistically at end to-end architectures to support the solution all the while keeping focused on your business outcomes. The data used for a for training your AI models must be managed. Is it currently in silos? Is it accessible to all the stakeholders? Is it trusted? NetApp is first and foremost a data management company. We have a complete data fabric story to securely efficiently break down those data silos. move and manage your data where it needs to be across, you know, on premise or in the cloud. AI workflows and all this data requires attention to storage and compute infrastructure. NetApp offers a wide range of solutions from high performance computing for model training to inferencing that happens on the production lines. NetApp offers a scalable range of data management and infrastructure options to suit your requirements.Thanks very much for your time. Uh if you are interested in learning more about NetApp's position and approach to AI, please check out our AI manufacturing website.