Tag: Machine Learning

Over the years, the physical act of producing music has become increasingly technical. On the forefront of this innovation is Splice, a music creation platform that uses advanced machine learning to take things to the next level.

Founded in 2019, ActZero is an ML-based cybersecurity company that equips small to medium-sized businesses to detect and manage breaches. The Seattle-based startup is now aggressively scaling after completing a full migration to AWS.

Founded in 2015, Amenity Analytics offers advanced natural language processing technology that helps financial companies extract actionable insights from text at scale.

FloodMapp is a world-first flood modelling solution, purpose-built for flood forecasting and early warning. Aimed at improving safety and preventing damage, FloodMapp provides highly accurate, real-time, property-specific, and dynamic flood inundation and depth insights for businesses exposed to flooding. It is 10,000 faster and 200 higher resolution than traditional models in an emergency response setting. Here’s how it works.

No one wants to hear from a debt collection agency. Most people associate it with letters in red, capital characters, high charges with imaginative reasons and intrusive phone calls. Berlin-based fintech PAIR Finance’s mission is to change that with the help of Machine Learning, introducing you and your customers to a completely new debt collection experience.

Creating a movie trailer takes time and most broadcasters and streaming platforms don’t have enough resources to do it. PromoMii, a UK startup, solves this problem with a unique blend of domain expertise and machine learning. Here’s how they do it.

Founded in 2013 by mathematicians from the University of Cambridge, Darktrace has developed an AI-based system for cyber security designed for the modern age. In this article, Mike Beck, Global Head of Threat Analysis at Darktrace, explains how their approach is similar to the human immune system.

Since dely is able to create its own recipe content, the startup can control both human wave-attack based and rule-based annotation, as well as how to apply feedback from user activities. In particular, Amazon SageMaker allows dely to train and deploy models quickly without the cost of additional resources. Here’s how.

Allie K. Miller the Head of ML Growth, Startups and Venture Capital and Emily Webber, Machine Learning Specialist Solutions Architect, both of AWS, walk through how to create an Amazon SageMaker notebook instance.

Reverie Labs uses computation to drive the development of therapeutics for cancer. To do this, they’ve built substantial cloud-based infrastructure to train machine learning models, deploy models to production, and build and ship internal-facing applications for our chemistry teams.