HOW DID WE GET HERE?
OUR FOUNDER'S STORY
From academia to business
Brad was doing his PhD at MIT in machine learning and AI when he started TrueMotion, now the market leader in the US telematics auto insurance space.
Starting state: lots of data to label, no viable solution on the market
We were in an 18-month RFP process to win a contract with Progressive in which 11 competitors were participating. To win we had to label a ton of noisy, complex, and poorly structured data sensitive to errors. We tried to use existing labeling solutions and libraries, but they didn’t work.
We looked at labeling companies on the market at the time and found none were able to help:
- The interfaces were static and too complex
- AI automation didn’t work
- Training the crowd took a lot of effort
- Performance between different people was highly variable and we needed to track it ourselves
- Could only use one type of crowd
- Errors were hard to catch and fix
- No trainable parameters to improve the system
Ending state: we built an in-house labeling solution
We developed our in-house labeling solution adjusted to our needs, use cases, and edge cases. What we realized after building this is that there were a lot of other data science teams that had the same needs, and that there was a strong market need for our solution.
What we built provided a great feature set:
- Train the crowd with less effort
- Automatically qualify new crowd on the task
- Distribute tasks to best performing crowd and measure individual performance over time
- Improve crowd performance by building expertise on a subset of tasks that can be used in multiple use cases
- Automate much of the labeling process
Super.AI technology offering
Super.AI provides the same technology that we built and used to deploy machine learning algorithms to the below insurance companies at TrueMotion (many customers not public yet).
Built BY RESEARCHERS from
Meet the rest of our team
We experienced AI in different ways in our careers, we came together to allow companies outside of the Google's of the world to use AI.
old & new
A new programming paradigm for AI
Making AI available to everyone
50 years ago
Only the smartest people in the world could use computers, which were expensive and could only be programmed in binary. Over time people built abstractions: assembly, compiled languages, interpreted languages, GUI. Now almost anyone can use a computer. This changed the world.
Only the smartest and most well funded companies can effectively use AI. Just like 50 years ago, when computers only understood binary, today's AI only understands labeled data. At super.AI, we built abstractions on top of labeled data: AI assembly language, AI Compiler and data programming.
But we aren't even close to being done. We made big steps with the AI Compiler and data programming, but our mission is to ultimately make AI available for everyone.