AI to Cool Down Google's Servers

DeepMind's algorithm allowed to save energy - for 9 months the efficiency index increased from 12% to 30%
20 August 2018   360

Google used DeepMind's AI technology to fully automate the cooling system in its data centers. The corporation began to use the algorithm in 2016, but then it just gave the engineers advice on reducing costs. In August 2018 the system began to work completely autonomously.

Researchers trained the algorithm using the "Training with reinforcement" method. Every five minutes, the AI ​​collects data from thousands of sensors inside the data center. The algorithm determines which configurations of the cooling system reduce the energy consumption in the  best way and independently includes them. Although its work is fully automated, the company's engineers can intervene at any time.

We wanted to achieve energy savings with less operator overhead. Automating the system enabled us to implement more granular actions at greater frequency, while making fewer mistakes.
 

Dan Fuenffinger
Data Centre Operator, Google

In total, the system monitors more than 120 different parameters of the data center operation, including air conditioning control, closing and opening of windows, fan speed and others.

After full automation, the DeepMind's algorithm allowed to save more energy - for 9 months the efficiency index increased from 12% to 30%.


Energy Consumption

According to Google data center vice president Joe Cava, the project will help the company save millions of dollars and reduce carbon dioxide emissions into the environment. In the long term, the system will help solve the problem of climate change, according to representatives of Google.

Microsoft to Use AI to Create Human Voice

Synthetic voice is nearly indistinguishable from recordings of people
27 September 2018   457

Researchers from Microsoft recorded computer voice, imitating human speech. To overcome the difficulties of the traditional model, they used neural networks for speech synthesis. Microsoft promises to provide support for 49 languages ​​and the ability to create unique voices for the needs of companies in the near future.

Synthesis of speech with the help of neural networks involves comparing the stress and length (so-called prosody) of the speaker's speech units, as well as their synthesis into a computer voice. In systems of traditional speech synthesis, prosody is divided into acoustic and linguistic analysis, controlled by various models. As a result, the speech is noisy and indistinct. Representatives of Microsoft argue that in the model of neural synthesis two stages are combined into one, so the voice sounds like a real one.

The developers are convinced that the synthesis of speech with the help of neural networks will make it more natural to communicate with virtual interlocutors and assistants. Moreover, it will enable you to convert e-books into audiobooks and will allow you to change the scoring of built-in navigators.

Microsoft Neural TTS
Microsoft Neural TTS

Azure computing power is available for real-time use, and Azure Kubernetes is responsible for this. Simultaneous application of neural synthesis of speech together with traditional speaks about expansion and increase of availability of service. At the moment, there are a female voice named Jessa and a man named Guy.

Microsoft is competing in speech recognition and synthesis technologies with Google, which updated its services in late August 2018. Google Cloud announced the release of a stable API for the synthesis of speech Cloud Text-to-Speech with the experimental function of audio profiles and support for several new languages.