A Technology Broker and Management Company Specializing in KM Systems
Favorite Rated the number 2 Knowledge Management authority by Agilence, the social authority ranker. Second only to the legendary Stan Garfield (congratulations Stan) View Original Source (nickmilton.com) Here.
Favorite The Experts can sometimes be resistant to KM, seeing it as a threat or a burden, with little personal reward. How can we address this? Image from wikimedia commons Many clients we speak to are having real problems recruiting the expert knowledge holders to the concept of Knowledge Management. Even
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Shared by Nick Milton September 13, 2019
Favorite People often make a big thing about learning from failure, but learning from success is just as important, and can often be overlooked. Crossroads by Chris Potter on Flickr and stockmonkeys.com The impetus to revisit this topic came from a one-liner post on LinkedIn by Oleg Vishnepolsky reading “Sometimes I
Read More Shared by Nick Milton September 11, 2019
Favorite Is KM a Science? Is KM a Philosophy? No – it’s a Management Discipline. And here is why that is a useful viewpoint. I have met many people over the years who treat Knowledge Management as something entirely unique – a philosophy, almost, or a “world-view”. For these people,
Read More Shared by Nick Milton September 10, 2019
Favorite Confirmation Bias is one of the most pernicious cognitive biases, and is a major challenge to Knowledge Management. See it in action below. Confirmation bias is a powerful cognitive bias, which means that people Tend to select evidence that supports what they already believe, and Set up tests that
Read More Shared by Nick Milton September 9, 2019
Favorite This post offers a dive deep into how to use Amazon Elastic Inference with Amazon Elastic Kubernetes Service. When you combine Elastic Inference with EKS, you can run low-cost, scalable inference workloads with your preferred container orchestration system. Elastic Inference is an increasingly popular way to run low-cost inference
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Shared by AWS Machine Learning September 7, 2019
Favorite After you’ve trained and exported a TensorFlow model, you can use Amazon SageMaker to perform inferences using your model. You can either: Deploy your model to an endpoint to obtain real-time inferences from your model. Use batch transform to obtain inferences on an entire dataset stored in Amazon S3.
Read More Shared by AWS Machine Learning September 7, 2019
Favorite Launched at AWS re:Invent 2018, Amazon SageMaker Ground Truth helps you quickly build highly accurate training datasets for your machine learning models. Amazon SageMaker Ground Truth offers easy access to public and private human labelers, and provides them with built-in workflows and interfaces for common labeling tasks. Additionally, Amazon
Read More Shared by AWS Machine Learning September 6, 2019
Favorite The default approach to managing knowledge which many companies use, is to keep knowledge in people’s heads, and to move the knowledge where it is needed by moving the people, not by transferring the knowledge. Homer Simpson’s head by SOCIALisBETTER on Flickr In this old model, knowledge is owned
Read More Shared by Nick Milton September 6, 2019
Favorite We’re excited to announce an end-to-end solution that leverages natural language processing to analyze and visualize unstructured text in your Amazon Elasticsearch Service domain with Amazon Comprehend in the AWS Cloud. You can deploy this solution in minutes with an AWS CloudFormation template and visualize your data in a
Read More Shared by AWS Machine Learning September 5, 2019
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