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Automotive
NeoGalaxy teamed up with Waymo, the leading autonomous driving technology development company, to develop an efficient solution to train and optimize self-driving algorithms. The technique, called population-based training (PBT), previously developed by DeepMind for honing video-game algorithms, which takes inspiration from biological evolution, speeds up the selection of machine-learning algorithms and parameters for a particular task by having candidate code draw from the “fittest” specimens (the ones that perform a given task most efficiently) in an algorithmic population.
Satellite Imagery
Teams at NeoGalaxy and NASA worked together to build customizable autonomous artificial agents that may learn complex tasks in large, partially observed, and visually diverse worlds. The simple and flexible APIs enables creative task-designs and novel AI-designs to be explored and quickly iterated upon.
Consumer Goods
NeoGalaxy and P&G, the multinational consumer goods corporation, worked together to build cloud-based solutions using DeepMind's language modelling architectures to reduce sentiment bias in language models via counterfactual evaluation during sentiment analysis of consumer data while also ensuring the data privacy of consumers.
Health Care
NeoGalaxy partnered with National Health Service of England to build AI-powered assistant for medical professionals. By combining and analyzing historical and real-time data (both texts and images) of patients using classical statistical methodology and cutting-edge machine learning algorithms, the algorithm behind the assistant created a system that improves medical diagnosis.
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Financial Services
NeoGalaxy and Visa collaborated on building and deploying AI models that can analyze large volume of data on Visa network and track any large-scale changes in transactions. DeepMind's generative adversarial networks (GAN) framework was used to identify gaps in fraud-detection models.
Manufacturing
NeoGalaxy and ABB teamed up to integrate reinforcement learning capabilities into ABB's IIoT device called "Smart Sensor" for analyzing electro-magnetic field strength, friction coefficients, speed, temperature, vibration, and other parameters to help monitor motors' condition. The real-time analysis of data increases the product life cycle, minimizes energy costs and reduces machine downtime.
