Favorite Computer vision uses machine learning (ML) to build applications that process images or videos. With Amazon Rekognition, you can use pre-trained computer vision models to identify objects, people, text, activities, or inappropriate content. Our customers have use cases that span every industry, including media, finance, manufacturing, sports, and technology.
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Shared by AWS Machine Learning October 16, 2020
Favorite Historically, humans have observed animal behaviors and applied them for different purposes. For example, behavioral observation is important in animal ecology, such as how often the behaviors are, when the behaviors occur, or whether there is individual difference or not. However, identifying and monitoring these behaviors and movements can
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Shared by AWS Machine Learning October 16, 2020
Favorite In 2018, we introduced Duplex, our AI technology that uses natural conversation to get things done. Since then, we’ve been exploring how conversational technology can be both easy to interact with and help people save more time. Today, during our Search On event, we shared an update on how
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Shared by Google AI Technology October 15, 2020
Favorite Muratcan Cicek, a PhD candidate at UC Santa Cruz, worked as a summer intern on Google’s Project Euphonia, which aims to improve computers’ abilities to understand impaired speech. This work was especially relevant and important for Muratcan, who was born with cerebral palsy and has a severe speech impairment.
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Shared by Google AI Technology October 15, 2020
Favorite For years, people have talked about tacit and explicit knowledge, but what about the other types? Confused, by Guudmorning on Fickr Tacit and explicit knowledge have been assumed to be the two main types of knowledge for most of Knowledge Management’s short history. Polanyi described tacit knowledge as the
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Shared by Nick Milton October 15, 2020
Favorite Object detection is a common task in computer vision (CV), and the YOLOv3 model is state-of-the-art in terms of accuracy and speed. In transfer learning, you obtain a model trained on a large but generic dataset and retrain the model on your custom dataset. One of the most time-consuming
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Shared by AWS Machine Learning October 15, 2020
Favorite Improving radiologist efficiency and preventing burnout is a primary goal for healthcare providers. A nationwide study published in Mayo Clinic Proceedings in 2015 showed radiologist burnout percentage at a concerning 61% [1]. In additon, the report concludes that “burnout and satisfaction with work-life balance in US physicians worsened from
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Shared by AWS Machine Learning October 15, 2020
Favorite Customer obsession, one of the key Amazon Leadership principles that guides everything we do at Amazon, has helped Amazon Translate be recognized as an industry leading neural machine translation provider. This year, Intento ranked Amazon Translate #1 on the list of top-performing machine translation providers in its The State of
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Shared by AWS Machine Learning October 15, 2020
Favorite We’re excited to announce new efficiency improvements for Amazon Personalize. These improvements decrease the time required to train solutions (the machine learning models trained with your data) by up to 40% and reduce the latency for generating real-time recommendations by up to 30%. Amazon Personalize enables you to build
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Shared by AWS Machine Learning October 14, 2020
Favorite This is a guest post by Ray Goh, a tech executive at DBS Bank. AWS DeepRacer is an autonomous 1/18th scale race car powered by reinforcement learning, and the AWS DeepRacer League is the world’s first global autonomous racing league. It’s a fun and easy way to get started
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Shared by AWS Machine Learning October 14, 2020
Shared by AWS Machine Learning October 16, 2020
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