TALK OF THE TOWN: Memrise, a U.K.-based startup that uses machine learning for language lessons, has raised $15.5 million, TechCrunch reports. Octopus Ventures and Korelya Capital led the Series B round. Avalon Ventures and Balderton Capital, two existing investors, also took part. The company's CEO tells TechCrunch he wants to expand the AI platform, adding more features. He also wants to get a bigger office space.
Apple's first iPhone launched in 2007, decades after the concept of machine learning -- a subset of artificial intelligence (AI) that employs mathematical techniques that "teach" software to make sense of complicated datasets -- rose to prominence. But it was only recently that the two collided. Apple launched Core ML, a framework designed to speed up machine learning tasks, alongside iOS 11 in May 2017. The Cupertino company shipped its first chip purpose-built for AI, the A11 Bionic, in last year's iPhone X. And at the 2018 Worldwide Developers Conference (WWDC), it took the wraps off Core ML 2, a new and improved version of Core ML; and Create ML, a GPU-accelerated tool for native AI model training on Macs.
Just as many readers are swapping paperbacks for tablets, many language learners are trading in their textbooks for apps so they can study on the go. One of the most popular language applications on the market is Duolingo, a program that "gamifies" learning by rewarding players with points and new levels after they memorize vocabulary words and grammar points. The app, which has over 170 million users around the world, currently offers over 20 language courses, including Spanish, Vietnamese and Turkish. But Japanese had been notably missing until this week, when it was released on Friday by the Apple store for iOS. Duolingo's landing page for its Japanese course showed that more than 60,000 people signed up to be notified the moment that lessons were finally added.
Just to let you know, if you buy something featured here, Mashable might earn an affiliate commission. Need to familiarize yourself with a local language? Say goodbye to feeling like Google Translate is the only person who understands you, and be the bilingual who makes heads turn. And no, it will not bring back those awful high-school Spanish memories. Whether your only free time is waiting in a coffee line or you have a few minutes on your phone during the day, there is an app that can do the job quickly.
At WWDC Apple released Core ML 2: a new version of their machine learning SDK for iOS devices. The new release of Core ML, whose first version was released in June 2017, should create an inference time speedup of 30% for apps developed using Core ML 2. They achieve this using two techniques call "batch prediction" and "quantization". Batch prediction refers to the practice of predicting for multiple inputs at the same time (e.g. Quantization is the practice of representing weights and activation in fewer bits during inference than during training. During training, you can use floating-point numbers used for weights and activations, but they slow down computation a lot during inference on non-GPU devices.