For almost all of 2020, everyone at Monolith has been working remotely. Many of us have sorely missed the social aspect of working in an office together.
So, every day at 3 pm, everyone who works at Monolith can join a remote 'tea time' call, our way of adding the social aspect of office space. Those who join talk about everything other than our jobs. It's 20 minutes of random conversations and epic tangents.
Just like everybody else who has religiously watched The Great British Bake-off and Masterchef, many of us love cooking or baking. Food comes up often in tea time calls, and recently, cookies became a talking point.
What's the best cookie? Some like it gooey, and some like an extra crunch. So, an idea started forming - why not use machine learning to optimize chocolate chip cookies? It's not that different from what our platform is used for by engineers in manufacturing.
Our CEO, Richard, decided that the process will be a mixed-initiative system where both human chefs, human cookie-raters, and a machine optimizer will participate in 120 experiments.
Process allocation was conducted in Monolith AI
Each participant was randomly allocated different tunable parameters to use in their cookie bake.
Everyone will bake six cookies.
Finally, the baked cookies will be given a rating on three criteria:
120 items in a dataset are enough for our platform to train a machine learning model but as everyone at Monolith shared the idea with our loved ones and others, we realised more people wanted to participate. Either for science or just to have an excuse to think that Paul Hollywood would shake their hand. So, we are opening up the experiment to everyone. You can fill in the form below and you will get your baking recipe, instructions, and a form to add your rating for each bake! Of course, we will notify you when the final model is ready!