 Hi, I'm Mike Murphy and welcome to this short, the news roundup from IBM Research. First up, we're checking out the prettiest location for a quantum computer. Now lots of chapels have chandeliers, but there aren't many like this one. This past week, Rensselaer Polytechnic Institute broke ground on installing a quantum system one on their campus. It's the first IBM system on a college campus and it happens to be housed in a former chapel which has been converted into a computing center. Last year, it'll be measuring the state of qubits while being vast in sunlight through a stained glass window. How serene. Next, let's learn a bit more about AI inferencing. So you've got a well-trained AI model that's perfectly fit for the task you want to tackle. But then what happens? The answer is inferencing. It's the moment of truth for an AI model. It's, you know, the test of how well it can apply what it learned during the training sessions to solve your task. Can it flag an email, spam, transcribe a conversation? Can it identify a hot dog? An AI model spends 90% of its life in inferencing mode. So IBM is looking at ways to make inferencing faster through innovative new hardware concepts like the AIU and working with platforms like PyTorch to make building systems as seamless as possible. And in case you missed it, AI is looking to fix Wall Street's spaghetti code. Transition critical systems around the world rely on secure legacy code languages like Cobalt. But for companies looking to modernize their operations with more flexible cloud-based systems, the transition from Cobalt to newer code languages like Java is a massive challenge. Now through a new generative AI system called WatsonX Code Assistant, IBM can turn legacy software into modern code in the fraction of the time it used to take. For more on the latest innovations from IBM, make sure you subscribe to our newsletter, Future Forward. Till next time.