Panel Abstract:
Deep Tech is commonly defined as an area of business or research that involves using advanced science and technology to provide solutions to complicated problems. The panel focuses on the challenges of fostering a complete innovation chain in Deep Tech and the identification of the Canadian strengths such as semi-conductors, computing hardware, photonics and telecommunications.

Summary of Conversations

The panel explored the concept of deep tech as a collaborative, challenge-focused approach to innovation, emphasizing the convergence of multiple emerging technologies to solve complex problems. Discussions revolved around Canada’s strengths in research but weaknesses in translating knowledge into commercial applications. The lack of a dense ecosystem, cultural differences between academia and business, and the need for a more collaborative mindset were highlighted. Examples like AbCellera and Nortel were mentioned, showcasing the impact of nurturing ecosystems and the role of anchor companies. The need for organic collaboration, revising academic incentives, and promoting a culture of risk-taking were recurring themes.

Take Away Messages/ Current Status of Challenges

The panel addressed the following key challenges and insights:

• Ecosystem Fragmentation: Canada’s geography and siloed approach hinder the development of a dense, interconnected deep tech ecosystem.
• Cultural Divide: Significant cultural differences between academia and business impede knowledge translation and collaboration.
• Incentive Misalignment: Current academic incentives prioritize publications over practical application and collaboration.
• Risk Aversion: Canada’s risk-averse culture, particularly in the public sector, stifles innovation and commercialization.
• Funding Gaps: Lack of funding for scaling up operations and protecting intellectual property limits the growth of deep tech companies.
• Talent Training: Academic training often lacks the interdisciplinary skills and entrepreneurial mindset needed for deep tech ventures.
• Overrated metrics: Papers and patents can be overrated; know-how needs to be more valued.
• Limited User Engagement: Insufficient engagement with end-users and industry stakeholders early in the research process.

Recommendations/Next Steps

The discussion yielded several actionable recommendations for advancing deep tech in Canada:

• Build Collaborative Platforms: Develop physical and digital platforms to foster interaction and knowledge sharing among researchers, industry, and investors.
• Redefine Excellence: Revise academic metrics and incentives to prioritize collaboration, impact, and practical application of research.
• Support Independent Research Labs: Strengthen the role of independent research labs to bridge the gap between academia and industry.
• Incentivize Anchor Companies: Encourage large companies to anchor in Canada, creating ecosystems and driving innovation.
• Promote Leadership Training: Train a new generation of scientists to act as true leaders, who can focus on problems and build strong teams.
• Encourage Prototyping: Push academia to test the usefulness and relevance of knowledge, for example, build a prototype.
• Foster a Risk-Taking Culture: Encourage and support risk-taking in both the public and private sectors to drive innovation.
• Improve Wayfinding: Enhance resources to improve orientation and facilitate the knowledge of resources that researchers need in their labs.