Idea Learning Combines the Power of Human Knowledge with Machine Learning.
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Idea
Learning
Gamalon gets smarter faster by bringing together machine learning with domain-specific human understanding.
Gamalon was built to be explainable and easily editable.
6 Key
Principles
We have developed our approach to machine learning, which we call Idea Learning, with 6 key principles in mind. Inspired by the work of Pedro Domingos in the Master Algorithm, we combined different aspects of each approach to machine learning.
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People
Editable & Auditable AI; Human-machine interaction using ideas, not just labeling data -
Deep Learning
Neural / Connectionist; Deep learning finds patterns that people cannot find themselves. -
Programs
The ability to learn rules/programs that humans can read and understand -
Probabilistic
System is self aware internally about where it is uncertain -
Populations
Inspiration from evolutionary algorithms -
Compositional
Train and then recombine modules
Related
Articles
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When Machines Have Ideas
A lab-to-market examination of AI solutions putting corporate data to work.
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Academic Literature Relating To Gamalon
Reviewing the emergence of several core architectural principles or axioms that seem necessary for machine learning systems to progress.
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MIT Media Lab Presentation
Ben Vigoda, Gamalon CEO, speaks at MIT Media Lab about Gamalon and how Gamalon helps you understand your customers.
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TEDx Boston: When Machines Have Ideas
Why building “stories” (i.e. Bayesian generative models) into machine intelligence systems can be very powerful.
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Talking Machines Interview
Listen to Katherine Gorman interview our CEO, Ben Vigoda, on Talking Machines.