A technology entrepreneur who previously sold his artificial intelligence company to a major semiconductor firm has launched a new venture focused on quantum computing infrastructure. Peter Sarlin, founder of the AI startup Silo AI which was acquired by AMD, is now leading QuTwo, a startup developing the foundational systems it believes businesses will require for the future of quantum computation.
Foundational Work for a Future Technology
The launch of QuTwo represents a significant bet on the long-term commercial viability of quantum computing, a field still largely in the research and development phase. The company is not building quantum computers themselves. Instead, its mission is to create the software and architectural layers that will allow standard enterprise IT systems to integrate with and eventually leverage quantum processors.
This approach acknowledges a widely held view in the technology sector: while fully fault-tolerant, commercially useful quantum computers may be years or even decades away, the supporting ecosystem must be built in advance. Enterprises in finance, logistics, pharmaceuticals, and materials science are already exploring potential quantum applications.
Bridging Classical and Quantum Systems
Quantum computers operate on fundamentally different principles than classical computers, using quantum bits or “qubits” that can exist in multiple states simultaneously. This promises unprecedented power for solving specific complex problems but creates a major compatibility challenge with existing data centers and software.
QuTwo’s work involves creating what is often termed “quantum-ready” or “post-quantum” infrastructure. This includes developing tools for hybrid computing, where certain tasks are offloaded to a quantum processor while the main application runs on classical servers. The startup also focuses on software that helps enterprises structure their data and algorithms in ways that could eventually be optimized for quantum advantage.
An Experienced Founder’s Perspective
Peter Sarlin’s background lends credibility to this ambitious undertaking. His previous company, Silo AI, was one of Europe’s largest private AI labs before its acquisition by Advanced Micro Devices (AMD) for a reported $665 million. This experience in building and scaling a deep technology startup, coupled with his expertise in machine learning, informs QuTwo’s strategy.
Sarlin has stated that the lessons learned from the AI industry’s evolution are directly applicable. He draws parallels to the early days of AI and cloud computing, where foundational infrastructure had to be established before widespread adoption could occur. The goal for QuTwo is to prevent a future scenario where quantum hardware is available, but enterprises lack the necessary software and integration frameworks to use it effectively.
The Broader Quantum Computing Landscape
QuTwo enters a competitive and rapidly evolving field. Major technology companies like IBM, Google, Microsoft, and Amazon have substantial quantum computing divisions, often providing cloud-based access to their experimental quantum processors. Several well-funded startups are also developing quantum hardware and software.
However, most industry analysts agree that a significant “readiness gap” exists. A recent report from a leading consulting firm indicated that while over 80% of large corporations are monitoring quantum computing, fewer than 20% have begun any concrete preparation for its integration. This gap is the specific market challenge QuTwo aims to address.
Looking Ahead
The next phase for QuTwo involves expanding its engineering team and beginning pilot projects with early-adopter enterprise clients in sectors with clear potential for quantum benefit. The company has not publicly disclosed its funding details or a specific timeline for product releases. The broader industry continues to work on overcoming the immense technical hurdles of quantum computing, particularly improving qubit stability and error correction. The success of infrastructure-focused companies like QuTwo will depend on the pace of progress in these core hardware challenges, as their solutions are designed to activate once that foundational threshold is crossed.
Source: GeekWire
