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OUR LATEST ARTICLES

Ask the CEO: What if customers don't have a lot of data?

Interviewer: So as anyone who plays in the data space knows, data is really important. Data quality is really important. What about customers who don't have enough or the right kind of data?

Mr. Kari: That's a really good question. I think it's very important to realize there are so many ways to actually acquire data.

You don't need to have data yourself. They are massive repositories of datasets that could fit your use case. We jump for just that initial learning before we actually start with full on automation as we start to get into the augmentation space. We could use other sources' data. There are public data sets. There are datasets that you could buy but there's also one more important thing that is so amazing with the open source movement...

20.11.2019

The Complete Guide to Bringing AI to Your Organization

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Our Most Recent Articles

How to extract knowledge from documents with Google PaLM 2 LLM

DevFest West Coast 2020

Video: Machine Learning Engineering with Tensorflow Extended

Video: How to Build a Reproducible ML Pipeline

50 AI Secrets: How Every Fortune 50 Company is Using AI Right Now

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OUR LATEST RESOURCES

OUR LATEST ARTICLES

How to extract knowledge from documents with Google PaLM 2 LLM

PaLM 2 is Google's next generation large language model that builds on Google’s legacy of breakthrough research in machine learning and responsible AI. It excels at advanced reasoning tasks, including code and math, classification and question answering, translation and multilingual proficiency, and natural language generation better than previous state-of-the-art LLMs. It can accomplish these tasks because of the way it was built – bringing together compute-optimal scaling, an improved dataset mixture, and model architecture improvements. This article offers a quick and straightforward method for leveraging the PaLM 2 API to extract knowledge and ask questions from text.

DevFest West Coast 2020

Watch videos of some of the world's top AI experts discuss everything from Tensorflow Extended to Kubernetes to AutoML to Coral.

Video: Machine Learning Engineering with Tensorflow Extended

In this talk, Hannes is providing insights into Machine Learning Engineering with TensorFlow Extended (TFX). He introduces how TFX for machine learning pipeline tasks and how to orchestrate entire ML pipelines with TFX. The audience learns how to run ML production pipelines with Kubeflow Pipelines, and therefore, free the data scientist's time from maintaining production machine learning models.

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Headquartered in the heart of Portland, Oregon, our satellite offices span North America, Europe, the Middle East, and Africa.

(503) 922-1164

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