Brainome Launches Solution To Course Correct Machine Learning

Brainome, the organization behind the first-since forever measure-before-assemble apparatus for machine learning, today dispatched its item, Daimensions™, for the undertaking market. By presenting estimation as an organized order to the field, Brainome changes the manner in which associations approach machine learning: quicker, more successful information arrangement, fast preparing and execution of models, minimal model size, speedy recognizable proof of most prescient information credits, and logic of results. Brainome eventually conveys another and complete organized strategy for examining information and making models.

Working in the default "more is better" system, the present information science and machine learning groups are urged to burn through large number of dollars on information arrangement and register power. Therefore, specialists are getting impeded by model multifaceted nature, size, and darkness, bringing about restricted business yield and frequently disillusioning rate of profitability. Brainome revises this enormous industry issue by adopting an on a very basic level distinctive strategy: estimating data content in information against target sorts of models prior to building anything. Brainome's methodology steers groups towards better results, making it conceivable to foresee venture speed, costs, and eventually achievement.

“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.”

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 helped to establish by previous colleagues Gerald Friedland and Bertrand Irissou in Berkeley, California. Bertrand Irissou, CEO at Brainome, is a sequential tech business visionary who established two fruitful organizations: Asic Advantage Inc. also, Audeme. Gerald Friedland, CTO, is an information researcher and teacher at UC Berkeley in the electrical designing and PC sciences office.

About Brainome

Brainome is fundamentally changing machine learning as the first company to offer a measure-before-build tool. The company was founded by two UC Berkeley alums who saw a need to course correct against the ever-escalating upward cycle of consumption of more data and more computing happening with machine learning. Brainome finally offers enterprises a clear path to return-on-investment by using its measurements-based approach to solve major business problems.