DeepMindJust like DeepMind’s neural network, there are numerous contributions of  DeepMind in the field of AI, here are the top 10 of them

DeepMind Technologies is a British artificial intelligence subsidiary of Alphabet Inc. and research laboratory founded in September 2010. DeepMind was acquired by Google in 2014. DeepMind has created a neural network that learns how to play video games in a fashion similar to that of humans, as well as a Neural Turing machine, or a neural network that may be able to access an external memory like a conventional Turing machine, resulting in a computer that mimics the short-term memory of the human brain. Let's explore some more of DeepMind’s contribution. Here is the list of the top 10 contributions of DeepMind in the field of AI. 

Identifying eye disease faster

DeepMind partnered with Moorfields Eye Hospital to develop faster ways of identifying, and better ways of understanding, common eye diseases from routine scans. The results, which were published in Nature Medicine, showed that DeepMind’s AI system could recommend patient referrals as accurately as world-leading expert doctors for over 50 sight-threatening eye diseases. More recently, it showed that its system can predict whether a patient will develop a more severe form of age-related macular degeneration months before it happens–paving the way for future research in sight-loss prevention.

Saving Energy at Google scale

Google's data centers contain thousands of servers that power services including Google Search, Gmail, and YouTube.It’s essential to keep these servers cool, but this takes a lot of electricity. Even minor improvements would significantly reduce energy usage and CO2 emissions. By building an AI system that manages data center cooling more efficiently, DeepMind helped save around 30% of the energy needed. It is also designed with safety and reliability in mind, so the AI system works within strict constraints.

Improving Google products

Working with Google, deep mind has applied its cutting-edge research to products and infrastructure used by billions of people. Its voice synthesis technology WaveNet is in the hands of people who use Google Assistant and Google Cloud Platform around the world. And its systems have helped improve mobile phone battery use and screen brightness for millions of people using the Android Pie operating system.

Breast Cancer Screening Datasets

Breast cancer screening programs vary from country to country. In the US, women are typically screened every one to two years, and their mammograms are interpreted by a single radiologist. In the UK, women are screened every three years, but each mammogram is interpreted by two radiologists, with an arbitration process in case of disagreement. DeepMind utilized large datasets collected in both countries to develop and evaluate its AI system.

Giving Doctors a 48-hour Head Start on Life-Threatening Illness

Working alongside experts from the US Department of Veterans Affairs (VA), DeepMind has developed technology that, in the future, could give doctors a 48-hour head start in treating acute kidney injury (AKI), a condition that is associated with over 100,000 people in the UK every year. These findings come alongside a peer-reviewed service evaluation of Streams, its mobile assistant for clinicians, which shows that patient care can be improved, and health care costs reduced, through the use of digital tools. 

Treating Head and Neck Cancers

DeepMind's has worked with the NHS in the U.K. and aims to improve the treatment of head and neck cancers. Before radiotherapy can begin, clinicians currently spend around four hours preparing a detailed map of each patient's body to avoid targeting the delicate surrounding tissue that can be damaged in treatment. The information is then fed into a radiotherapy machine to target cancer without harming the healthy tissue.

Creating More natural-sounding Speech 

DeepMind created a more natural-sounding speech for products used by millions of people around the world. WaveNet is a generative model that is trained on speech samples. It creates the waveforms of speech patterns by predicting which sounds likely follow each other. And because the model learns from human speech, WaveNet automatically incorporates natural-sounding elements left out of earlier text-to-speech systems, such as lip-smacking and breathing patterns.

A Design for Safety and Reliability

Google's data centers contain thousands of servers that power popular services including Google Search, Gmail, and YouTube. Ensuring that they run reliably and efficiently is mission-critical. DeepMind has designed its AI agents and the underlying control infrastructure from the ground up with safety and reliability in mind and uses eight different mechanisms to ensure the system will behave as intended at all times.

Personalizing Battery Management and Screen brightness on Android Devices

DeepMind for Google has created two new features for Android: Adaptive Battery, which predicts which apps you'll need next and thereby boosts battery performance, and Adaptive Brightness, which learns your brightness preferences in different surroundings to personalize your screen settings.

Optimizing App Recommendations in Google Play

DeepMind has also helped personalize app recommendations in Google Play by using machine learning to find the apps that users are more likely to use and enjoy based on their previous downloads and the context in which they were used.