Aible Scored Highest (4.5/5) for the AutoML Use Case in the 2021 Gartner Critical Capabilities Report for Cloud AI Developer Services

Aible in Gartner 2021

Aible, the pioneer in impact-optimized enterprise AI, has scored highest in the Automated Machine Learning (AutoML) services Use Case in Gartner’s 2021 “Critical Capabilities for Cloud AI Developer Services” report. In Gartner’s evaluation of 13 AutoML providers, Aible scored the highest in the AutoML Use Case.

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Google AI Introduces ‘Model Search’: An Open Source Platform For Finding Optimal Machine learning (ML) Models

Model search

Google AI has announced the release of Model Search, a platform that will help researchers develop machine learning (ML) models automatically and efficiently. Model Search isn’t domain-specific, flexible, and well equipped to find the appropriate architecture that best fits a given dataset and problem. At the same time, it minimizes the coding time, effort, and resources. […]

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Introducing Model Search: An Open Source Platform for Finding Optimal ML Models

Google Model Search

he success of a neural network (NN) often depends on how well it can generalize to various tasks. However, designing NNs that can generalize well is challenging because the research community’s understanding of how a neural network generalizes is currently somewhat limited: What does the appropriate neural network look like for a given problem? How deep should it be? Which types of layers should be used? Would LSTMs be enough or would Transformer layers be better? Or maybe a combination of the two? Would ensembling or distillation boost performance? These tricky questions are made even more challenging when considering machine learning (ML) domains where there may exist better intuition and deeper understanding than others.

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AutoML vs HPO vs CASH: what is the difference?

Robot and doctor with telescope

Automated Machine Learning, or AutoML for short, is on the rise. More and more commercial products appear on the market, academic tools, and public, open-source AutoML libraries. As with every new technology that is new, unclear, and nebulously defined, AutoML is misunderstood. On one end, there are grandiose claims that it will send data analysts home, and on the other end, extreme statements that it automates only the trivial part of the analysis. This is because different people give different definitions to AutoML. Let us examine them.

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Abacus.AI raises $22 million to automate AI model creation, deployment, and maintenance

Abacus.AI (previously RealityEngines) is developing a service that automates machine learning model creation, deployment, and maintenance. Today the company raised $22 million in a series B round at an over $100 valuation.

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