Brainome in the news

Brainome's measure-before-build tool for machine learning highlighted in our press coverage.

  • Datanami

    A startup called Brainome today launched a new product designed to help data scientists determine how much data they need to sufficiently train their machine learning models. In addition to cutting costs, the software can also help data scientists avoid overfitting their models.

  • AIthority

    By introducing measurement as a discipline to the field, Brainome changes the way companies such as SK telecom approach machine learning.

  • Medium

    AI startup Brainome aims to change how companies approach machine learning

  • ZDNET

    Brainome's new product, Daimensions, seeks to eliminate brute-force aspects of machine learning model development, integrate with existing CI/CD infrastructure and generate small ML models that can run efficiently on commodity hardware.

  • siliconANGLE

    An artificial intelligence startup called Brainome Inc. is launching today, hoping to change the way organizations approach machine learning with a new concept it calls “measure-before-build.”

  • RT Insights

    Brainome takes 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.

Brainome featured in webinars

Follow along Brainome's guest appearances in machine learning webinars

  • Dahshu

    ​In this webinar, we will discuss an entirely new and different approach to supervised machine learning - one that is rooted in measurements. We will explain how this new approach (which is actually as old as science itself) can be used to solve difficult bioinformatics problems, many of which have previously been out of reach. We will explain the fundamentals of how measurements-based machine learning works, and also explore how the approach can be applied to solve real-world problems in bioinformatics & biostatistics.

Read our blog

The trend in Machine learning for the last 20 years has been that the more data you have and the more you spend on computation the more likely you are to succeed. Is “more data” and “more compute” a thing of the past?

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