A Technology Broker and Management Company Specializing in KM Systems
Favorite Today, Amazon Web Services (AWS) announced Amazon Rekognition Custom Labels, a new feature of Amazon Rekognition that enables customers to build their own specialized machine learning (ML) based image analysis capabilities to detect unique objects and scenes integral to their specific use case. For example, customers using Amazon Rekognition
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Shared by AWS Machine Learning November 25, 2019
Favorite All voices are unique, yet speakers tend to adjust their delivery, or speaking style, according to their context and audience. Before Amazon Polly used Neural Text-to-Speech technology (NTTS) to build voices, TTS (Standard Text-to-Speech) voices couldn’t change their speech patterns to match any particular speaking style. When Amazon Polly
Read More Shared by AWS Machine Learning November 25, 2019
Favorite We recently announced that Amazon Transcribe now supports transcription for audio and video for 7 additional languages including Gulf Arabic, Swiss German, Hebrew, Japanese, Malay, Telugu, and Turkish languages. Using Amazon Transcribe, customers can now take advantage of 31 supported languages for transcription use cases such as improving customer service, captioning and subtitling,
Read More Shared by AWS Machine Learning November 25, 2019
Favorite This is a reprise and rewrite of a post from 5 years ago about KM change models vs KM maturity models. AKA “why KM change is more like spread of a forest fire than the growth of a tree”. Photo from the US National Parks Service The use of
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Shared by Nick Milton November 25, 2019
Favorite Does KM need a single technology platform? More likely it needs several technologies. This blog post was prompted by a thread in Stan Garfield’s SIKM community asking what technology platform people use for KM. My immediate thought was that a single platform probably is not sufficient. However let’s look
Read More Shared by Nick Milton November 22, 2019
Favorite This is a guest post from Matt Fielder and Jordan Rosenblum at iHeartRadio. In their own words, “iHeartRadio is a streaming audio service that reaches tens of millions of users every month and registers many tens of thousands more every day.” Personalization is an important part of the user
Read More Shared by AWS Machine Learning November 21, 2019
Favorite To have an effective conversation, it is important to understand the sentiment and respond appropriately. In a customer service call, a simple acknowledgment when talking to an unhappy customer might be helpful, such as, “Sorry to hear you are having trouble.” Understanding sentiment is also useful in determining when
Read More Shared by AWS Machine Learning November 21, 2019
Favorite If you are a leader who wants to help develop a Knowledge Management and Organisational Learning culture in their organisation, you can do this simply, by asking two questions. I have a question by The US Army on Flickr The two questions are Who have you learned from?Who have
Read More Shared by Nick Milton November 21, 2019
Favorite Amazon SageMaker Ground Truth helps you build highly accurate training datasets for machine learning. It can reduce your labeling costs by up to 70% using automatic labeling. This blog post explains the Amazon SageMaker Ground Truth chaining feature with a few examples and its potential in labeling your datasets.
Read More Shared by AWS Machine Learning November 20, 2019
Favorite I have blogged quite a bit recently on Connect and Collect approaches to KM, aka the transfer of tacit and explicit knowledge. Here is a reprise and extension of a useful table which describes the two. Three of my recent blog posts have touched on Charts and pilots, Why
Read More Shared by Nick Milton November 20, 2019