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Creating a more accessible world with Azure AI

At Microsoft, we are inspired by how artificial intelligence is transforming organizations of all sizes, empowering them to reimagine what’s possible. AI has immense potential to unlock solutions to some of society’s most pressing challenges.

One challenge is that according to the World Health Association, globally, only 1 in 10 people with a disability have access to assistive technologies and products. We believe that AI solutions can have a profound impact on this community. To meet this need, we aim to democratize AI to make it easier for every developer to build accessibility into their apps and services, across language, speech, and vision.

In view of the upcoming Bett Show in London, we’re shining a light on how Immersive Reader enhances reading comprehension for people regardless of their age or ability, and we’re excited to share how Azure AI is broadly enabling developers to build accessible applications that empower everyone.

Empowering readers of all abilities

Immersive Reader is an Azure Cognitive Service that helps users of any age and reading ability with features like reading aloud, translating languages, and focusing attention through highlighting and other design elements. Millions of educators and students already use Immersive Reader to overcome reading and language barriers.

The Young Women’s Leadership School of Astoria, New York, brings together an incredible diversity of students with different backgrounds and learning styles. The teachers at The Young Women’s Leadership School support many types of learners, including students who struggle with text comprehension due to learning differences, or language learners who may not understand the primary language of the classroom. The school wanted to empower all students, regardless of their background or learning styles, to grow their confidence and love for reading and writing.

Watch the story here. 

Teachers at The Young Women’s Leadership School turned to Immersive Reader and an Azure AI partner, Buncee, as they looked for ways to create a more inclusive and engaging classroom. Buncee enables students and teachers to create and share interactive multimedia projects. With the integration of Immersive Reader, students who are dyslexic can benefit from features that help focus attention in their Buncee presentations, while those who are just learning the English language can have content translated to them in their native language.

Like Buncee, companies including Canvas, Wakelet, ThingLink, and Nearpod are also making content more accessible with Immersive Reader integration. To see the entire list of partners, visit our Immersive Reader Partners page. Discover how you can start embedding Immersive Reader into your apps today. To learn more about how Immersive Reader and other accessibility tools are fostering inclusive classrooms, visit our EDU blog.

Breaking communication barriers

Azure AI is also making conversations, lectures, and meetings more accessible to people who are deaf or hard of hearing. By enabling conversations to be transcribed and translated in real-time, individuals can follow and fully engage with presentations.

The Balavidyalaya School in Chennai, Tamil Nadu, India teaches speech and language skills to young children who are deaf or hard of hearing. The school recently held an international conference with hundreds of alumni, students, faculty, and parents. With live captioning and translation powered by Azure AI, attendees were able to follow conversations in their native languages, while the presentations were given in English.

Learn how you can easily integrate multi-language support into your own apps with Speech Translation, and see the technology in action with Translator, with support for more than 60 languages, today.

Engaging learners in new ways

We recently announced the Custom Neural Voice capability of Text to Speech, which enables customers to build a unique voice, starting from just a few minutes of training audio.

The Beijing Hongdandan Visually Impaired Service Center leads the way in applying this technology to empower users in incredible ways. Hongdandan produces educational audiobooks featuring the voice of Lina, China’s first blind broadcaster, using Custom Neural Voice. While creating audiobooks can be a time-consuming process, Custom Neural Voice allows Lina to produce high-quality audiobooks at scale, enabling Hongdandan to support over 105 schools for the blind in China like never before.

“We were amazed by how quickly Azure AI could reproduce Lina's voice in such a natural-sounding way with her speech data, enabling us to create educational audiobooks much more quickly. We were also highly impressed by Microsoft's commitment to protecting Lina's voice and identity."—Xin Zeng, Executive Director at Hongdandan

Learn how you can give your apps a new voice with Text to Speech.

Making the world visible for everyone

According to the International Agency for the Prevention of Blindness, more than 250 million people are blind or have low vision across the globe. Last month, in celebration of the United Nations International Day of Persons with Disabilities, Seeing AI, a free iOS app that describes nearby people, text, and objects, expanded support to five new languages. The additional language support for Spanish, Japanese, German, French, and Dutch makes it possible for millions of blind or low vision individuals to read documents, engage with people around them, hear descriptions of their surroundings in their native language, and much more. All of this is made possible with Azure AI.

Try Seeing AI today or extend vision capabilities to your own apps using Computer Vision and Custom Vision.

Get involved

We are humbled and inspired by what individuals and organizations are accomplishing today with Azure AI technologies. We can’t wait to see how you will continue to build on these technologies to unlock new possibilities and design more accessible experiences. Get started today with a free trial.

Check out our AI for Accessibility program to learn more about how companies are harnessing the power of AI to amplify capabilities for the millions of people around the world with a disability.
Quelle: Azure

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OpenShift Container Storage 4: Introduction to Ceph

This Blog will go through Ceph fundamental knowledge for a better understanding of the underlying storage solution used by Red Hat OpenShift Container Storage 4.

> Note: This content is relevant to learning about the critical components of Ceph and how Ceph works. OpenShift Container Storage 4 uses Ceph in a prescribed manner for providing storage to OpenShift applications. Using Operators and CustomResourceDefinitions (CRDs) for deploying and managing OpenShift Container Storage 4 may restrict some of Ceph’s advanced features when compared to general use outside of Red Hat OpenShift Container Platform 4.

Timeline
The Ceph project has a long history as you can see in the timeline below.

Figure 29. Ceph Project History
It is a battle-tested software defined storage (SDS) solution that has been available as a storage backend for OpenStack and Kubernetes for quite some time.
Architecture
The Ceph cluster provides a scalable storage solution while providing multiple access methods to enable the different types of clients present within the IT infrastructure to get access to the data.

Figure 30. Ceph Architecture
The entire Ceph architecture is resilient and does not present any single point of failure (SPOF).
RADOS
The heart of Ceph is an object store known as RADOS (Reliable Autonomic Distributed Object Store) bottom layer on the diagram. This layer provides the Ceph software defined storage with the ability to store data (serve IO requests, protect the data, check the consistency and the integrity of the data through built-in mechanisms). The RADOS layer is composed of the following daemons:

MONs or Monitors
OSDs or Object Storage Devices
MGRs or Managers
MDSs or Meta Data Servers

Monitors
The Monitors maintain the cluster map and state and provide distributed decision-making while configured in an odd number, 3 or 5 depending on the size and the topology of the cluster, to prevent split-brain situations. The Monitors are not in the data-path and do not serve IO requests to and from the clients.
OSDs
One OSD is typically deployed for each local block device present on the node and the native scalable nature of Ceph allows for thousands of OSDs to be part of the cluster. The OSDs are serving IO requests from the clients while guaranteeing the protection of the data (replication or erasure coding), the rebalancing of the data in case of an OSD or a node failure, the coherence of the data (scrubbing and deep-scrubbing of the existing data).
MGRs
The Managers are tightly integrated with the Monitors and collect the statistics within the cluster. Additionally they provide an extensible framework for the cluster through a pluggable Python interface aimed at expanding the Ceph existing capabilities. The current list of modules developed around the Manager framework are:

Balancer module
Placement Group auto-scaler module
Dashboard module
RESTful module
Prometheus module
Zabbix module
Rook module
Dashboard module

MDSs
The Meta Data Servers manage the metadata for the POSIX compliant shared filesystem such as the directory hierarchy and the file metadata (ownership, timestamps, mode, …​). All the metadata is stored within RADOS and they do not serve any data to the clients. MDSs are only deployed when a shared filesystem is configured in the Ceph cluster.
If we look at the Ceph cluster foundation layer, the full picture with the different types of daemons or containers looks like this.

Figure 31. RADOS as it stands
The circle represents a MON, the ‘M’ represents a MGR and the square with the bar represents an OSD. In the diagram above, the cluster operates with 3 Monitors, 2 Managers and 23 OSDs.
Access Methods
Ceph was designed to provide the IT environment with all the necessary access methods so that any application can use what is the best solution for its use-case.

Figure 32. Different Storage Types Supported
Ceph supports block storage through the RADOS Block Device (aka RBD) access method, file storage through the Ceph Filesystem (aka CephFS) access method and object storage through its native librados API or through the RADOS Gateway (aka RADOSGW or RGW) for compatibility with the S3 and Swift protocols.
Librados
librados allows developers to code natively against the native Ceph cluster API for maximum efficiency combined with a small footprint.

Figure 33. Application Native Object API
The Ceph native API offers different wrappers such as C, C++, Python, Java, Ruby, Erlang, Go and Rust.
RADOS Block Device (RBD)
This access method is used in Red Hat Enterprise Linux, Red Hat OpenStack Platform or OpenShift Container Platform version 3 or 4. RBDs can be accessed either through a kernel module (RHEL, OCS4) or through the librbd API (RHOSP). In the OCP world, RBDs are designed to address the need for RWO PVCs.
Kernel Module (kRBD)
The kernel RBD (aka krbd) driver offers superior performance compared to the userspace librbd method. However, krbd is currently limited and does not provide the same level of functionality. e.g., no RBD Mirroring support.

Figure 34. krbd Diagram
Userspace RBD (`librbd`)
This access method is used in Red Hat OpenStack Environment or OpenShift through the RBD-NBD driver when available starting in the RHEL 8.1 kernel. This mode allows us to leverage all existing RBD features such as RBD Mirroring.

Figure 35. librbd Diagram
Shared Filesystem (CephFS)
This method allows clients to jointly access a shared POSIX compliant filesystem. The client initially contacts the Meta Data Server to obtain the location of the object(s) for a given inode and then communicates directly with an OSD to perform the final IO request.

Figure 36. File Access (Ceph Filesystem or CephFS)
CephFS is typically used for RWX claims but can also be used to support RWO claims.
Object Storage, S3 and Swift (Ceph RADOS Gateway)
This access method offers support for the Amazon S3 and OpenStack Swift support on top of a Ceph cluster. The Openshift Container Storage Multi Cloud Gateway can leverage the RADOS Gateway to support Object Bucket Claims. From the Multi Cloud Gateway perspective the RADOS Gateway will be tagged as a compatible S3 endpoint.

Figure 37. Amazon S3 or OpenStack Swift (Ceph RADOS Gateway)
CRUSH
The Ceph cluster being a distributed architecture some solution had to be designed to provide an efficient way to distribute the data across the multiple OSDs in the cluster. The technique used is called CRUSH or Controlled Replication Under Scalable Hashing. With CRUSH, every object is assigned to one and only one hash bucket known as a Placement Group (PG).

CRUSH is the central point of configuration for the topology of the cluster. It offers a pseudo-random placement algorithm to distribute the objects across the PGs and uses rules to determine the mapping of the PGs to the OSDs. In essence, the PGs are an abstraction layer between the objects (application layer) and the OSDs (physical layer). In case of failure, the PGs will be remapped to different physical devices (OSDs) and eventually see their content resynchronized to match the protection rules selected by the storage administrator.
Cluster Partitioning
The Ceph OSDs will be in charge of the protection of the data as well as the constant checking of the integrity of the data stored in the entire cluster. The cluster will be separated into logical partitions, known as pools. Each pool has the following properties that can be adjusted:

An ID (immutable)
A name
A number of PGs to distribute the objects across the OSDs
A CRUSH rule to determine the mapping of the PGs for this pool
A type of protection (Replication or Erasure Coding)
Parameters associated with the type of protection

Number of copies for replicated pools
K and M chunks for Erasure Coding

Various flags to influence the behavior of the cluster

Pools and PGs

Figure 38. Pools and PGs
The diagram above shows the relationship end to end between the object at the access method level down to the OSDs at the physical layer.

> Note: A Ceph pool has no capacity (size) and is able to consume the space available on any OSD where its PGs are created. A Placement Group or PG belongs to only one pool and an object belongs to one and only one Placement Group.

Data Protection
Ceph supports two types of data protection presented in the diagram below.

Figure 39. Ceph Data Protection
Replicated pools provide better performance in almost all cases at the cost of a lower usable to raw storage ratio (1 usable byte is stored using 3 bytes of raw storage by default) while Erasure Coding provides a cost efficient way to store data with less performance. Red Hat supports the following Erasure Coding profiles with their corresponding usable to raw ratio:

4+2 (1:1.666 ratio)
8+3 (1:1.375 ratio)
8+4 (1:1.666 ratio)

Another advantage of Erasure Coding (EC) is its ability to offer extreme resilience and durability as adminstrators can configure the number of coding chunks (parities) being used. EC can be used for the RADOS Gateway access method and for the RBD access method (performance impact).
Data Distribution
To leverage the Ceph architecture at its best, all access methods but librados, will access the data in the cluster through a collection of objects. Hence a 1GB block device will be a collection of objects, each supporting a set of device sectors and a 1GB file is stored in a CephFS directory will be split into multiple objects. Similarly, a 5GB S3 object stored through the RADOS Gateway via the Multi Cloud Gateway will be divided into multiple objects. The example below illustrates this principle for the RADOS Block Device access method.

Figure 40. Data Distribution

> Note: By default, each access method uses an object size of 4MB. The above diagram details how a 32MB RBD (Block Device) supporting a RWO PVC will be scattered throughout the cluster.

Resources and Feedback
To find out more about OpenShift Container Storage or to take a test drive, visit https://www.openshift.com/products/container-storage/.
If you would like to learn more about what the OpenShift Container Storage team is up to or provide feedback on any of the new 4.2 features, take this brief 3-minute survey.
The post OpenShift Container Storage 4: Introduction to Ceph appeared first on Red Hat OpenShift Blog.
Quelle: OpenShift