Nvidia to Launch Enterprise AI Data Platform Ontap AI

The basis of the platform is the supercomputers DGX-1 and cloud flash storages AFF A800
03 August 2018   437

NVIDIA and NetApp launched the corporate platform Ontap AI to store models of artificial intelligence. Unlike cloud services, it is equipped with tools for accelerated collection, processing and transmission of data. This is reported by Venture App.

The basis of the platform is the supercomputers DGX-1 and cloud flash storages AFF A800. To distribute data over the clouds and provide quick access, regardless of format and location, the Data Fabric architecture is used.

The NVIDIA DGX-1 computers support second-generation in-depth training and are equipped with Tesla V100 graphics cards. One DGX-1 rack provides 1 Pflops of power and is able to train the FairSeq Neural Network presented in May 2017 for one and a half days. The AFF A800 drives in a cluster with 24 nodes read data at 300 GB / s and have a delay of 200 μs.

The Ontap AI platform was already used in the consulting firm Cambridge Consultants. It was involved in the development of systems for studying the effects of drugs on patients. Also Ontap AI was used to create Vincent - a painting training program at the level of human capabilities.

In April 2018, NVIDIA CEO Jensen Huang announced that their video cards no longer comply with Moore's law. With the help of the DGX-2 supercomputer, the company managed to train the AlexNet neural network to store 15 million images in 18 minutes.

Microsoft to Use AI to Create Human Voice

Synthetic voice is nearly indistinguishable from recordings of people
27 September 2018   465

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.