From Research to AI Startup: A Journey Worth Taking

Radical ventures organized a master class for AI founders. The aim? To equip AI researchers with insights on transitioning into the startup space and creating successful AI-driven products and services. More about this can be found [HERE] .

Pieter Abbeel, a professor at UC Berkeley and co-founder of Gradescope and Covariant, shared some valuable insights. Covariant focuses on applying Deep Reinforcement Learning and Imitation Learning to design robots that solve real-world planning problems.

Finding Your Drive

Be genuinely interested in solving a problem. This intrinsic motivation will attract like-minded individuals to join your team. Uniqueness and value are crucial. Stand out!

Envisioning the Future

Think ahead. Will the problem you’re solving still exist in 10–20 years? Will your technology improve lives in the long run? Companies like Google and Airbnb have thrived by anticipating future needs. This foresight is critical.

Will we still have the same problem 10–20+ years from now?

Building a Team

If you’re in research, tap into your network of researchers and graduate students. These individuals are often the most qualified team members. The founding members of Covariant were graduate students.

Reach Out!

Go through your email contacts and send out invites. You might find a few people who are interested in your startup’s mission. Pieter did this when founding Covariant, and two people joined as co-founders.

Taking the Leap

If you’ve been contemplating an AI-driven startup, now is the time. AI research has a plethora of active researchers and like-minded individuals who are easily reachable. AI technologies can be incredibly disruptive and solve problems in unprecedented ways. Think of “Uber in the taxi business” or the next Airbnb or Lyft. Dive in, and the rules will follow!

Defining Roles

Clearly define the roles of every team member. The CEO should make quick decisions, while the CTO should focus on decisions that ensure the product’s functionality. Knowing your team, including yourself, is vital in settling these roles. However, avoid overthinking it.

The CEO should be able to make decisions which work fast.

Patience is Key

Be prepared for the long haul. Creating a reliable AI product takes time. You’ll need to collect data, validate it, run simulations, implement in the real world, gather feedback, and iterate. Patience is essential; it might take at least seven years to perfect a successful product.

Striving for Perfection

90% accuracy isn’t enough. For instance, if a robot has 90% accuracy in picking and placing objects, one in every 100 objects will be misplaced. With multiple robots and high volume, this error rate becomes significant. The same applies to other AI models. Rolling out Covariant’s first commercially viable product took four years!

Exercising Control

Have some control over new ideas. While new team members or co-founders might bring radical ideas, exercise your power indirectly to avoid too much friction. Team members are the ones making product-level decisions daily — they are the builders.

Learning from Others

Successful entrepreneurs are often willing to help others. Write them an email — they might respond. If not, follow up; people can be busy but still willing to help.

Every successful entrepreneur is always willing to help an upcoming one.

Understanding Customers

Observe how customers use your product and be receptive to complaints. AI product design follows Software Engineering principles. Ensure your product has error-handling capabilities and can restart after failures. These small features can make a big difference in user satisfaction.

Connecting with Investors

If you can’t reach investors directly, contact people who can. Established entrepreneurs often help newcomers. However, honesty is crucial — investors conduct their research, and you don’t want to start on the wrong foot.

If you cannot reach investors then reach out to people who reach them.

Good luck to all aspiring AI startup founders!

-Stephen.

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