AWS DeepRacer League weekly challenges – compete in the AWS DeepRacer League virtual circuit to win cash prizes and a trip to re:Invent 2019!

Favorite The AWS DeepRacer League is the world’s first global autonomous racing league, open to anyone. Developers of all skill levels can get hands-on with machine learning in a fun and exciting way, racing for prizes and glory at 21 events globally and online using the AWS DeepRacer console. The

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Shared by AWS Machine Learning August 15, 2019

Problem-focused innovation process at De Beers

Favorite Innovation should be focused on problems first, ideas second, and should follow a structured process. Here’s an example from the mining sector Image of the De Beers AUV from Sonardyne.com A few years ago, my then colleague Ian Corbett published a really interesting case study entitled “Learning for the long view – A

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Shared by Nick Milton August 15, 2019

Lesson learning at NASA – video

Favorite From the AFAC lesson management forum last week, this video below from David Oberhettinger, NASA’s Jet Propulsion Lab, talking about lesson learning in their human and robotic space exploration program David makes some interesting points, such as the need to dedicate individuals for lessons capture (although NASA allows engineers

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Shared by Nick Milton August 14, 2019

How to estimate the size of the KM prize

Favorite I blogged last week about the importance of knowing the value KM will deliver. But how do you do this? Big Prize, by Alberto G on Flickr As I said in last week’s post; if you understand the value that Knowledge Management can bring, then you understand how much

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Shared by Nick Milton August 12, 2019

How collaboration can simplify

Favorite Collaboration adds simplicity in a complicated world.  Simplifying through collaboration is the topic of a Ted talk by Yves Morieux, embedded below, in which he gives us 6 rules to simplify work. Watch the talk to get the context, but here are his 6 rules (with more explanation here)

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Shared by Nick Milton August 9, 2019

Adding a data labeling workflow for named entity recognition with Amazon SageMaker Ground Truth

Favorite Launched at AWS re:Invent 2018, Amazon SageMaker Ground Truth enables you to efficiently and accurately label the datasets required to train machine learning (ML) systems. Ground Truth provides built-in labeling workflows that take human labelers step-by-step through tasks and provide tools to help them produce good results. Built-in workflows

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Shared by AWS Machine Learning August 8, 2019