Brainome Launches Solution To Course Correct Machine Learning With A Fundamentally Different, Measure-First Approach
By introducing measurement as a discipline to the field, Brainome changes the way companies such as SK telecom approach machine learning
Brainome, the company behind the first-ever measure before build tool for machine learning, launched its product, Daimensions, for the enterprise market. By introducing measurement as a structured discipline to the field, Brainome changes the way organizations approach machine learning: faster, more effective data preparation, rapid training and execution of models, compact model size, quick identification of most predictive data attributes, and explainability of results. Brainome ultimately delivers a new and complete structured method for analyzing data and creating models.
Operating in the default “more is better” framework, today’s data science and machine learning teams are encouraged to spend millions of dollars on data preparation and compute power. As a result, experts are getting bogged down by model complexity, size, and opacity, resulting in limited business output and often disappointing return-on-investment. Brainome corrects this massive industry problem by taking a fundamentally different approach: measuring information content in data against target types of models before building anything. Brainome’s approach steers teams towards better outcomes, making it possible to predict project speed, costs, and ultimately success.
“Every field of engineering and science starts with measurement. Before building a car, plane, bridge, or computer chip, you must measure before you design and build. Today’s data scientists and machine learning experts are forced to rely on what is essentially guesswork instead of having access to any advanced type of measurement,” said Bertrand Irissou, Co-Founder and CEO at Brainome. “Brainome takes a completely new angle by providing much-needed tools based on a novel, systematic measurement-based approach.”
“Brainome has been a breath of fresh air in helping us model a problem in the healthcare domain. Our previous approach was time consuming, full of guess-work, and took over a week to iterate from feature extraction to experimentation to results,” said Eric Davis, Vice President of AI Language Tech Labs at SK telecom. “Brainome took a lot of the guesswork out of data quantity needs and feature importance, allowing us to reduce our experimentation cycle from a week to mere hours. Equally as important, the easy-to-deploy Python model allowed us to spend more time on experimentation versus serving and deploying our model.”
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Although it can be used in any field on any data, the power of Daimensions’ core benefits have been demonstrated for industries such as Genomics research, FinTech, HealthTech, and AdTech. By measuring first, customers can:
- Know whether there’s enough data to learn rules and avoid overfitting;
- Find and design the data features that matter;
- Iterate quickly through data prep and model design options without training; and
- Train and execute rapidly using compact, efficient models
Brainome was co-founded by former business partners Gerald Friedland and Bertrand Irissou in Berkeley, California. Bertrand Irissou, CEO at Brainome, is a serial tech entrepreneur who founded two successful companies: Asic Advantage Inc. and Audeme. Gerald Friedland, CTO, is a data scientist and professor at UC Berkeley in the electrical engineering and computer sciences department.