Model Selection & Hyper-Parameter Tuning

August 26, 2020 | Patrick Bangert

Brightics AI Accelerator automated, distributed machine learning (AutoML) speeds network training time up and over the critical point when automated model selection, feature generation, and hyper-parameter tuning become possible. Brightics AI Accelerator does all of this for you - yielding a much better model.

The Role of Domain Knowledge in Data Science

August 26, 2020 | Patrick Bangert

Data science aims to take data from some domain and produce a high-level description or model of it that can be applied practically to solve some particular challenge in that domain. How much knowledge about the domain does the data scientist have to have to do a good job? We explore this question in this article.

AI in the Service of Humanity - Guidelines for Ethical AI

August 25, 2020 | Patrick Bangert

As artificial intelligence impacts people's lives more and more, it is indispensable that we watch out for ethical issues. The new field of AI Ethics deals with bias in datasets and models as well as misdirected use cases. This article discusses some topics at a high level. I'm interested in your opinions and any other cases where you've seen ethical challenges in datascience, machinelearning, and AI.

Automated Driving with Brightics AI Accelerator

August 25, 2020 | Yogesh Luthra

This article discusses various stages of autonomous driving and explores Computer Vision aspects of it in detail. Semantic segmentation is the partition of an image into coherent parts. Instance segmentation is Semantic Segmentation with the addition of identification of each unique entity in the image.

The Status and Future of AI

August 25, 2020 | Patrick Bangert

Artificial Intelligence is a collection of disparate models that perform extremely well in a very narrow domain. What is the future of AI and ML? It is not just collecting more data or tweaking an algorithm. We must reimagine a wholistic use case on the one hand, and upgrade the model architecture with reasoning. Please read my latest article and let me know what you think.

The Case for Collaboration - Data Science Is Done Best When an Operator Works With a Data Scientist

August 18, 2020 | Patrick Bangert

Studies conducted through collaboration between an operator that knows the physical reality and a data-science company that knows the best machine-learning methods yield good practical results. This article analyzes the various categories of Oil & Gas projects and papers and provides a recommendation for collaboration of data science and domain expertise for best results.

Introduction to Brightics AI Accelerator

August 01, 2020 | Dan Waters

Distributed machine learning is a fascinating thing, reducing the training time by the number of computers that work on the job. Using 512 computers, for example, will reduce training time from 3 weeks to 1 hour. This model training speed up enables automated model selection, feature generation, and hyperparameter tuning. Imagine training an AI model in the time it takes to go to lunch!

Semi-Automatic Labeling and Segmentation

July 25, 2020 | Patrick Bangert

Semi-automatic labeling reduces the human effort by 80% in generating a training data set for classification and segmentation tasks. Click to learn more!

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