My main use case for D-Wave Leap is to compare it to machine learning, so I was looking for use cases in the genetic genomics area mainly and I wanted to test the potential of the tool in terms of knowing which leverages or features influence more the output of different medical cases. A quick, specific example of how I use D-Wave Leap for that comparison in a genomic scenario is that I have more than 100 machine learning models in production right now, with all the features, validations, evaluations, and everything. I simply check and use D-Wave Leap as a contrafactual, as another tool to see if I get the same results, and the most important thing for me is explainability. I want to know if the output is the same, which in most cases it is, but it changed the view of the features that have more weight in those outputs, and in many genomic diseases I have compared more than 10 machine learning models versus D-Wave Leap.
I was using the hybrid quantum computer from D-Wave Leap for solving big and complex QUBO tasks. I did not utilize D-Wave Leap's Hybrid Solver Service as I was working in code mostly. I integrated the Ocean SDK in my workflow, though I do not remember the exact details of what we were using it for. I would describe the benefits of using D-Wave Leap for optimizing supply chain operations by saying we had no such tasks. I did not use the machine learning enhancements in D-Wave Leap.
My main use case for D-Wave Leap is research, specifically anything about how to use D-Wave Leap for optimization. Currently, I use it for classifying whether post-COVID patients have problems or not, and I will soon expand its use to aquaculture systems and medical terms.I chose to use D-Wave Leap for classifying post-COVID problems because of university support. I normally want to apply it in machine learning as generative AI, but currently, I'm still not sure which application I can use because I only have twenty minutes per month and need to make sure the dataset is small enough for D-Wave Leap.
D-Wave Leap provides cloud-based access to quantum computing resources, enabling businesses to solve complex problems faster. This service leverages quantum technology for practical applications, addressing computational challenges that traditional methods struggle to solve efficiently.D-Wave Leap is tailored for companies seeking quantum computing advantages in diverse sectors. Users gain access to a quantum cloud platform designed to optimize processes like optimization, machine learning,...
My main use case for D-Wave Leap is to compare it to machine learning, so I was looking for use cases in the genetic genomics area mainly and I wanted to test the potential of the tool in terms of knowing which leverages or features influence more the output of different medical cases. A quick, specific example of how I use D-Wave Leap for that comparison in a genomic scenario is that I have more than 100 machine learning models in production right now, with all the features, validations, evaluations, and everything. I simply check and use D-Wave Leap as a contrafactual, as another tool to see if I get the same results, and the most important thing for me is explainability. I want to know if the output is the same, which in most cases it is, but it changed the view of the features that have more weight in those outputs, and in many genomic diseases I have compared more than 10 machine learning models versus D-Wave Leap.
I was using the hybrid quantum computer from D-Wave Leap for solving big and complex QUBO tasks. I did not utilize D-Wave Leap's Hybrid Solver Service as I was working in code mostly. I integrated the Ocean SDK in my workflow, though I do not remember the exact details of what we were using it for. I would describe the benefits of using D-Wave Leap for optimizing supply chain operations by saying we had no such tasks. I did not use the machine learning enhancements in D-Wave Leap.
My main use case for D-Wave Leap is research, specifically anything about how to use D-Wave Leap for optimization. Currently, I use it for classifying whether post-COVID patients have problems or not, and I will soon expand its use to aquaculture systems and medical terms.I chose to use D-Wave Leap for classifying post-COVID problems because of university support. I normally want to apply it in machine learning as generative AI, but currently, I'm still not sure which application I can use because I only have twenty minutes per month and need to make sure the dataset is small enough for D-Wave Leap.