Natural language processing is a messy and complicated affair but modern advanced techniques are offering increasingly impressive results. Word embeddings are a modern machine learning technique that has taken the natural language processing world by storm.
An interview with Petrica Martinescu, Lead Architect Web Platforms, Tremend. Microservices are emerging as the preferred way to create enterprise applications, bringing a wide range of advantages such as isolated risk and faster innovation, flexibility and agility.
Over the past few years we’ve seen amazing improvements in machine learning applied to natural languages. New applications have emerged, and some of them are likely to change how humans communicate with each other and with their computers.
Google is making a big impression right now with the launch of the Pixel Buds, the earphones that can translate conversations between 40 languages. This is just the latest display of remarkable machine learning power, applied to human language.
WhatsApp, Facebook Messenger, WeChat and Viber had 2.125 billion monthly users, mostly on mobile. The same as as the top four social media platforms combined – Facebook, Twitter, LinkedIn and Instagram.
From our experience, microservices are mainly employed when clients want to develop or rewrite an application for which they forecast uneven growth. That can happen when a certain business segment is expected to grow, or change radically.
Which do you think works better for your company – one big machine that does all the jobs, or several sleek tools that deal with various parts of your business? No surprise here, the consultant’s answer would be “It depends.”
Mircea Marghidanu, lead developer at Unity3D was our guest at Tech Talks@Tremend for a presentation on game development, code testing and human perception limits.