Smashing Magazine has a handy tutorial on how front-end developers can start learning machine learning. The post describes how to use a pre-trained model, transfer learning and a custom model using Tensorflow.js.
The Microsoft Academic Knowledge Graph is a RDF dataset of over 8 billion triples of information about academic publications across 200,000+ fields of study.
Trivago deployed machine learning to present images of hotel spas when a user searched hotels with spas to improve user experience. This blog post describes how they tweaked pre-trained convolutional neural networks (CNNs) to label 100+ million hotel images in order to display spa realted images during contextual searches.
Researchers used machine learning to analyse 3.3 million material science abstracts from 1922 to 2018. They found that the ML system captured fundamental knowledge within the field and also historically identified new materials and research to study before the new materials were discovered in real life. The research shows how machine learning can be used to identify latent knoweldge more quickly.
Lyft have released a huge self driving level 5 dataset comprising 55,000 human labelled 3D annotated frames, a driveable surface map and an underlying spacial semantic map to contextualise the data. The release of the dataset is part of a competition with a prize of $25,000, aimed at researchers to help Lyft train AI algorithms to help them reach their goal of a Level 5 (fully automated) self driving car.
Julia White from Microsoft Azure Marketing demonstrated the use of Hololens 2 to project a motion captured holograph of herself speaking in Japanese using her own speech patterns. The demonstration was created using Azure mixed reality to record the hologram, Azure text to speech and translate to create the spoken content and Azure neural text to speech technology to imprint her speech patterns in Japanese.
The Spanish soccer league LaLiga has been fined €250,000 for breah of data privacy laws after they used their scores app to covertly listen for soccer matches being illegally streamed in bars using the phone's microphone and GPS location. The app was downloaded more than 10 millions times and did include a clause in the terms and conditions that user would consent to allowing their phone to be used to detect fradulent behaviour like pirated soccer games.
Researchers at UC Berkeley and a team at Adobe have trained a convolutional neural network to detect photoshopped faces at 99% accuracy compared to 53% human accuracy.
Google's The Launchpad have published a machine learning case study by The Frontier Car Group. The case study describes how the company, with the help of Lunchpad mentors, implemented a machine learning pipeline to predict the selling price of used cars month over month.
