Indico: Machine Learning without the PhD
Congrats Slater and Alec!
Slater Victoroff and Alec Radford of Olin College of Engineering are looking to make machine learning as simple as any other programming function. That’s why they developed Indico, a platform for machine learning and data science. They believe in Douglas Adam’s idea that “We are stuck with technology when what we really want is just stuff that works.” No one calls a refrigerator a piece of “technology” anymore because it just works. They are looking to do the same with machine learning, moving it to a core competency, something that people rely on.
The Kaggle Connection:
Slater, who has previously applied his natural language processing expertise working at edX and Fetchnotes, and Alec, who has worked on machine learning research in both academic and startup settings, got the idea for Indico from Kaggle, a large-scale data competition that the two began competing in during their sophomore year. On Kaggle, top PhD and post-docs from around the world compete on this platform for “fortune, fame, and fun.” At first, Victoroff and Radford started competing as a hobby, but when they found themselves ranked as 66 out of 150,000, they thought it might be time to start something in this space. They began contracting projects, raising over $2,000 in just two weeks. While they did not have time to fully devote to such an endeavor, they re-examined what they were excited about and good at: the user-centric design side of machine learning.
The Idea Goes Live:
They began by putting a few machine learning apps online, constructing demos, and talking to individuals about these ideas. They saw a whole range of needs that individuals in this space have, from new developers to big companies that were frustrated about the amount of time they were devoting to machine learning, where they weren’t positive about its use. Slater noted, “People don’t really understand what can be done with machine learning. But if you can imagine it, you can do it. Conveying that you can do anything instead of sticking to the academic approach to machine learning makes it applicable to parts of everyday life.”
What’s Next for Indico?
The team is launching the Indico Platform as a developer tool, for small to medium sized companies with high technology consumer-facing aspects. They have launched a beta where they currently contain 200 users, with eight API’s up and running. They’re looking to grow with a few corporate partners as they continue to figure out the pain points in this niche. While they are currently focused on producing a highly locked down Indico platform, a few ideas have surfaced for future developments. Could they build their machine learning platform into hardware? Or, could they produce a machine learning marketplace, with an “app store” type model containing requirements for entry, and revenue sharing for usage?
Whatever course they decide to take, we’re proud to have them as a part of the Rough Draft Portfolio, as we help them grow, refine, or pivot their idea. And on a personal note, I am so happy to have another awesome team from Olin College join the RDV portfolio!
Congrats on your success so far, Slater and Alec!
