Welcome to the Tech for Non-Techies podcast

103. How I got into deep tech investing (with Colin Beirne, Two Sigma Ventures)

“There are things that are much more important about investing in technology companies than technology,” says Colin Beirne, Founder of Two Sigma Ventures. TSV has invested in around 100 start-ups over the last 10 years, and funded 10 unicorns. They’re part of Two Sigma, a hedge fund with more than $60 billion under management.

Colin is surrounded by data scientists and programmers, but doesn’t have a background in programming. Listen to this episode to hear how Colin went from a liberal arts college to becoming one of the world’s leading deep tech investors.

Learning notes from this episode:

  • The winning company is not always the one with the best technology. Tech can be a differentiator, but usually it’s only temporary. The job of a venture capitalist is not to figure out which company has the best tech. It’s to figure out which company has the best business that can ultimately be the biggest impact,” says Colin.
  • Data science...
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81. Technology is just another business tool. Don’t put it on a pedestal.

It’s easy to put the tech sector on a pedestal, as we’re constantly bombarded with its power and profits. But “technology is just a tool to affect business outcomes,” says prop tech entrepreneur Sebastian Rivas.

Sebastian runs Andes STR, a which uses machine learning algorithms to find property investments for short term rentals. If you want to invest in a property and rent it out on Airbnb, Andes STR will find the investment and manage the rental.

Sebastian started his career in finance, and created a smart plan to break into tech. Listen to this episode to learn how he did it.

Learning notes from this episode:

  • Technology is a tool used in business to improve efficiency, user experience and productivity, but it is not an end in itself.
  • Being tech savvy and understanding how technology influences business outcomes is a must have in today’s working environment, almost no matter where you work. Even your coffee shop has an app!
  • “The biggest...
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73. How I transitioned into a career in tech

Lots of smart people want to transition into careers in tech, but don’t know how to get started. If that sounds like you, then listen to how Alexandra Soroko went from finance to tech leadership.

Today, Alexandra is Head of Merchant Sales at Visa in France, and connects fintech companies, banks and Visa’s technologies to help some of the world’s largest companies process payments. In her role, she combines tech knowledge, marketing and finance skills. She started her career at JP Morgan, but didn’t let her lack of tech skills stop her.

Learning notes from this episode:

  • You don’t need to be an engineer, but you need a willingness to understand what lies beneath the surface if you want to succeed in a tech business,” says Alexandra
  • "If we don't have a vision, life just happens to us," says Alexandra. Before embarking on a transition into tech, think about your values and what you want from your next role. Alexandra’s six desires...
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46. How technology moves money around the world

When you make a payment, your money doesn’t reach the destination bank account straight away. Instead, it goes through an underground railroad of payment providers and intermediaries to reach its destination.

In traditional banking, this process is expensive and slow, but new fintech players are changing the system.

In this episode, you’ll hear from Justin Xiao how fintech company Railsbank is solving this problem, and how tiny snippets of code called APIs tie technology companies together.

Learning notes from this episode:

  • APIs are tiny snippets of code that allow one tech product to be integrated into another tech product. For example, each time you see Login with Facebook in a website or an app, that company is using the Facebook API to allow you to login.
  • Railsbank allows companies to move money around just like a bank would, by giving access to its services via its API
  • To learn more about APIs, listen to episode 37: APIs: Why Uber uses Google Maps

 

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41. From tech entrepreneurship to venture capital

Venture capital is usually not somebody's first job. It is a career people transition into, and one of the best ways to prepare is by working in a start-up.

In this episode, you'll hear from VC James Sore, Principal at SuperSeed ventures, about how he transitioned into tech entrepreneurship and then investing. You will also learn about equity crowdfunding and syndicate investing.

If you want to raise money for a start-up or invest in one, this episode is for you.

 

Learning notes from this episode:

  • Venture capitalists have three main jobs: sourcing deals and investing, raising capital for their own funds, and helping the start-ups in their portfolio.
  • Early stage investing, like early stage start-ups, is risky. In the early stages, companies are still finding structure and product market fit. This makes them the right environment for some people, but completely wrong for others. Knowing yourself and where you thrive is important to get this right. 
  • Venture...
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34. How I Built A Fintech AI Business As A Non-Technical Founder

Sophia Matveeva spoke to Jung Seok Kung (JS) founder of Aizen, a fintech company which uses AI to support decision making and manage risk for banks. JS is a non-technical founder, who now leads a company that processes 10,000+ algorithms in real time.

If you want to learn what AI is in practice and how it's changing business this episode is for you.

We cover how JS went from spotting a market opportunity to creating an algorithm using a spreadsheet, and the ups and downs of entrepreneurship.

Learning notes from this episode:

  • An algorithm is just a set of instructions that you put into a computer.
  • JS created a prototype of his algorithm using a spreadsheet. The aim of his algorithm was to give out loans to customers. He bought lending data from the Lending Club and tested it against a control group. This means one set of loan applications was assessed by the algorithm and the other was done manually. By doing this, JS proved that his algorithm was making correct decisions....
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