We are excited to welcome Lucas Leclerc, a Research and Development Quantum Engineer at PASQAL, to share his work on a quantum-enhanced machine learning solution for the prediction of credit rating downgrades. Leclerc and his team of fellow researchers implement this solution on a neutral atom Quantum Processing Unit with up to 60 qubits on a real-life dataset. They report competitive performances against the state-of-the-art Random Forest Benchmark with their model achieving better interpretability and comparable training times. Join us on Friday, April 7th at 2pm to hear from Leclerc as he walks through this machine learning solution for fallen-angels forecasting.

Thought leaders, policymakers, business leaders, experts, government officials, researchers, scholars and other key stakeholders convene for a two-day event focused on the latest issues impacting the fintech ecosystem. Thursday, March 2nd, Day 1 is policymaker and practitioner oriented with conversations on how to move forward with digital assets from a use case to regulation, with topics that are top of mind for our legislators. Friday, March 3rd, Day 2 is the second annual meeting of the Decentralized Finance Research Conference with six academic papers on the program.

Traditional contact tracing, where workers query patients about their interactions to see who else might have been infected — and perhaps to find out where they got the infection — is being widely used. But for the first time, many public health authorities are considering, or have implemented, smart phone apps to partially automate and scale contact tracing.

Although artificial intelligence (AI) has become a crucial component of digital transformation efforts tied to organizational strategy, many firms struggle to articulate the strategic value of emerging AI systems. In this article we argue that the power of AI as a strategic resource lies in its self-learning capabilities. Such learning capabilities are only realized in partnership with humans through mutual learning. By building on a learning-centered framework, we elaborate on how AI can contribute to organizational learning to create a competitive advantage. We formulate the concept of artificial capital and the ways artificial and human capital can together drive routinization and strategic learning processes that connect internal and external environments of the organization. Finally, we use this conception to formulate practical recommendations for managing and developing AI to meet strategic business goals.