Iris.ai CEO Takes the Road Less Traveled
Last week at Mindspace coworking in Berlin, GTEC kicked off their 2018 Open Lecture Series by inviting Anita Schjøll Brede, CEO of Iris.ai, to discuss her startup and entrepreneurial path. It proved revelatory.
Not only does Anita’s startup truly disrupt science publishing for the benefit of knowledge-sharing – using open source and tokenization – Anita also shared her personal story which offered perfect lessons for Berlin’s active startup scene.
I want to crystalize some of Anita’s witty comments here because a) I enjoyed them immensely and b) if you missed it, I now don’t have to feel badly for you.
This woman catapults herself into situations where she grasps knowledge, masters skills, and successfully braves odds. Now she’s sharing her tips. She broke down lessons learned along the way to creating one of the coolest new ‘actors’ in modernizing and decentralizing scientific publishing.
Disruption, Tokenization, Transparency
First, a brief introduction. Iris.ai uses artificial intelligence to read scientific research papers and with the help of trained algorithms, can understand text and match it to other text. Iris delivers back concepts in a visual way, and allows you to search millions of scientific research papers, sharing knowledge in a refreshing way. This open access challenges traditional approaches to science publishing.
This feat alone is noteworthy, as the science publishing market has a 44% profit margin to potentially disrupt. Meaning it is expensive to access journals and publications and glean the latest knowledge. But there are 2 more gems here: Tokenization and Transparency: People who help train Iris.ai’s system, that is who annotate a paper digitally in the ecosystem, can earn a token in a new economy. They run on the Ethereum blockchain. Iris.ai uses open source, codes, and algorithms – allowing people to challenge each other.
To recap the evening, I’ll expand on three general themes of her talk:
- Make the absolute best use of your education and network.
- Go after wide-ranging opportunities, even if long shots.
- Use the strength of a community to get things done.
1. Stay in School
Anita is passionately curious, resourceful, and committed – all traits of a successful entrepreneur. With Scandivanian roots and a CV spanning 9 countries and 7 languages, she is a force to contend with. In the next 4 weeks she will be on 4 continents. But she didn’t always have a ticket to her next destination in hand.
She reflected on indecision regarding her educational future: theater or medical school? She chose theater, circuitously leading to refined presentation skills for different audiences. That partly explains her confident stage presence at GTEC. The other explanation is simply her broad experience.
After theater opportunities fizzled, Anita partook in a Norwegian entrepreneurship program that led her to an internship in a high-tech startup in Silicon Valley. She overcame a steep learning curve and developed a customer focus, while experiencing the volatile waves of startup life. She went on to a Master’s in entrepreneurship at Chalmer’s University of Technology in Sweden, on which she reflected: “Studying entrepreneurship is a tricky business.” In other words, you need to get outside the classroom and into the weeds. She build an award-winning race car and completed a solar project in Kenya.
2. Take Long Shots
Next up, she knew she wanted to start a company with a specific person. She got up the nerve to contact that individual, and together they created a company matching students with internship opportunities. After a few years, and some mentorship influence, she decided it was time to change gears. She whipped together a last-minute but successful application for a competitive spot at Singularity University, which ultimately opened her future more widely. She spent 10 weeks in a ‘brilliant bubble’ engaging with classmates and techies who built things to affect positive change in the world. They stayed up all night philosophizing about topics like ethics in robotics.
3. Build Strong Community
Iris.ai needs a community, not a platform. They are creating a decentralized community of academics, coders, and self-proclaimed science geeks. Remarkably Anita says: “ We are starting it, but we don’t want to own it in the long run.” The startup itself is not attempting to be the determiner of knowledge, but rather aims to create a knowledge-validation system and build a community that can leverage itself to advance insights into science.
Speaking of knowing how to deal with a community, Anita put that directly into practice. During the evening with GTEC, Anita ticked through audience questions which were posted on the screen behind her. This meant she on-the-fly tailored the lecture about her experience to match expectations or interests from this sold-out crowd. Anita is clearly a gifted storyteller.
Takeaways: enjoy some pearls of her wisdom.
“Time management is the curse of the entrepreneur.”
Iris.ai, which is 2.5 years old, in a 2 million dollar seed round, and has a staff of 12 going on 20, offers some kernels of wisdom to fellow entrepreneurs and innovation enthusiasts. She says her company is in a awkward position of “we can’t afford assistants but we are big enough to have a lot of admin.” The Founders hop on a morning strategy meeting each day about different business areas. This type of recurrent, high-level thinking is key to avoiding the natural tendency to put out fires. You must ask yourself: “Are you focusing on the right thing?” As a growing, funded business, you have to be strategic with your time and energy.
Deep Learning Tech
“If you don’t need Machine Learning or AI, don’t do it. Use the tech that is best applicable to the problem you are trying to solve.”
Anita stressed that for them, text understanding is the focus. They use machine learning techniques like natural language understanding and neural topic modeling to build a model based on reviewing text extracts of 18 million research papers. They will soon be publishing a white paper on blockchain, so stay tuned for that.
“We need to be mindful when selecting datasets.”
Anita was referencing a NYT article about how algorithms can perpetuate stereotypes and discriminating policies based on limited data sets or skewed input. “Long story short, the algorithm was racist,” she continued. She says we need to build diverse teams to broaden our perceptions and data sets.
“Say yes to random things.”
Despite disliking small talk, Anita says CEOs need to build networks– saying yes to chances to get on stage and be visible. Meeting people inevitably results in new possibilities. This can directly impact investment opportunities. Once you get the first investor, it becomes easier to get the ball rolling with others.
“Don’t give yourself equity on Day 1.”
Anita presented an interesting framework called the ‘Slicing the Pie’ model, where you get yourself on a vesting schedule. When starting a company, you assign a different value to different contributions and then use a mathematical approach that everyone can agree on.
Why it Matters
Why is what Iris.ai is doing so important? There are universities in some countries which simply cannot afford to pay the necessary fees for reading and accessing scientific research papers. This means they have limited access to the latest knowledge in their fields and therefor hinders scientific progress.
The hope, as I understand it, is that through a decentralized system and tokenization economy, people will be inspired to contribute efforts towards this knowledge-sharing community, which is our future. Just at Spotify disrupted the music industry, scientific research and the costly peer review process is ready to be shaken up.
The evening was basically a holy trinity of science, technology, and inclusion. I hope you found this summary of highlights useful, and if so please spread the word. Big thanks to Anita, GTEC, Mindspace and the Berlin community for sparking such worthy dialogue.
Written by Elisheva Marcus.
Stay tuned next month for a talk from Ida Tin, CEO of Berlin-based Clue.