Branding Partner

  • On April 20th, Minds2Capital welcomed industry leaders, family office investors, and entrepreneurs in the tech space to an intimate lakeside chat on Tech Trends in 2016 at Whitspaceblackbox, Neuchatel! Our speakers hit the issues hard leading to engaging discussions on Marketplaces and AI/Machine Learning. 

    Michael van Swaaij, founder of eBay Europe, and Kerstin Cooley, CEO Moor, gave us unique insights into what it takes to build leading Internet marketplace businesses.  Alex Housley, CEO Seldon, and Marc Sloan, CEO of Context Scout, two powerhouse CEOs building companies that use machine learning technology educated us on the many ways in which artificial intelligence can make businesses more efficient.

    Key Investor Takeaways:

    Marketplaces

    How to spot trends and conditions for success in marketplaces?

    1. Understand the problem. 2. Does the technology exist to solve it?

    •      The most exciting opportunities come in areas where no-one is looking. We are never at end point where we can’t improve on the status quo. 

    • When supply and demand in a sector are not optimal – focus on the inefficiency – marketplaces can help solve it.

    • The best companies focus on value creation and have the assets to execute once they have identified the link with the core problem.

    Artificial Intelligence: Machine Learning

    • Watch our speaker, Alex Housley, CEO of Seldon, give a powerhouse pitch on how Seldon is using machine learning to change the way we do businesses. 

  • Existential risk of AI: Jaan Tallinn (co-founder Skype)

    Jaan Tallinn, co-founder Skype, shared his views on the existential risks of AI through his work at the Future of Life Institute. We discussed the value alignment problem, causal control methods, built-in controls, human-friendly AI, the 
global coordination of values, raising awareness in the younger generation, and funding AI Research Initiatives to offset the existential dangers of AI.

    AIaaS

    Our panel of CEOs also discussed specific use cases on how AI is revolutionizing the software industry with significant strides in machine learning and the rise of open source creating new winners and losers in the industry. Software has disrupted technology over the last several decades; modernizing traditional businesses through cloud-based platforms and enabling growth in B2C technologies, from mobile to banking, to real estate, to consumer products. The development of AI-as-a-service has the potential to open new markets and disrupt the playing field. The ability to leverage AI will become a defining attribute of competitive advantage or disadvantage to companies and our broader society in coming years.

  • Our panel of CEOs and industry specialists discussed the fact that AI is not just “tech for tech”. From deep learning to natural language processing, in the financial sector, costs are being lowered and returns increased by opening up new data sets to faster analysis. AI is still in the very early stages but as the technology is democratized a wave of innovation will follow. AI has also made significant strides in its impact on Switzerland’s Silicon Valley of Robotics. We can now create robots and intelligent systems with the intelligence to autonomously navigate challenging environments, e.g. robot concepts that are best adapted for acting on the ground, in the air, and in the water.

  • The idea: Artificial Intelligence in Healthcare Diagnostics is moving beyond a back-end tool for the healthcare enterprise to the forefront of the consumer and clinician experience. These technologies are taking on more sophisticated roles, with the potential to make every interface both simple and smart. As AI becomes more sophisticated, it will increasingly become a partner to clinicians, helping automate encounters and support early diagnoses of life-threatening diseases. Data protection and digital identities in the world of new technologies. We also discussed the myth of data privacy and supporting digital transformation without creating digital harm. What are the consequences for data privacy / digital identities and the impact of responsible data sharing?