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Quantum Machine Learning (QML) in the Cloud: Algorithm Optimization & Use Case Exploration

Former Sr. Technologist
Intel Corporation
Quantum Computing
USA
North America

$ 645

June 18, 2025

Topics covered in this transcript

  • How do quantum neural networks differ from classical counterparts in cloud setups?
  • What hybrid quantum-classical architectures show near-term commercial promise?
  • How are cloud providers (e.g., AWS Braket) democratizing QML access?
  • What drug discovery use cases benefit most from quantum ML speedups?
  • How do quantum feature maps enhance classical ML model accuracy?
  • What benchmarks validate QML advantages in fraud detection?
  • How are error-correction techniques impacting QML algorithm design?
  • What role do cloud HPC clusters play in simulating quantum circuits?
  • How are startups navigating IP challenges in QML patent filings?
  • What skills merge quantum physics with ML engineering?
  • How do geopolitical export controls impact QML cloud service availability?
  • What investor trends are shaping QML startup valuations?

Keywords

  • Hybrid Quantum-Classical Models
  • Qml Drug Discovery
  • Quantum Feature Embedding
  • Error Mitigation Frameworks
  • Cloud Quantum Simulators
  • AI-Driven Circuit Optimization
  • Financial Portfolio QML
  • Quantum Kernel Methods
  • Patent Landscape Analysis
  • Quantum Advantage Benchmarks

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Bangalore

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Get in touch with us to learn more about our services, ask for assistance with a technical difficulty, or if you would like a product demo.
info@nextyn.com
Singapore
68 Circular Road, #02-01
049422, Singapore
Jakarta

Revenue Tower, Scbd, Jakarta 12190, Indonesia
Mumbai
4th Floor, Pinnacle Business Park, Andheri East, Mumbai, 400093
Bangalore

Cinnabar Hills, Embassy Golf Links Business Park, Bengaluru, Karnataka 560071
Instagram Favicon

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