Dell EMC Ready Solutions for machine learning with Hadoop (L) and deep learning with NVIDIA (R).
Many in the M&E sector are starting to look at the deployment of Artificial Intelligence (AI) and Machine Learning (ML) to aid parts of their businesses. AI is finding applications in areas where large amounts of unstructured data needs to be analysed. The OTT distributors are already using AI as core to their content recommendation engines. AI is also finding applications in speech-to-text conversion and language translation, both essential to the localization of programs for international distribution. At the sharp end, for acquisition, AI is finding uses in genres like live sports. One use case is brand analysis, a sponsor may want to know the duration that their logo appears on screen. Image analysis is one of the key capabilities of AI systems. Similar analysis can be used with scripted shows that are using product placement
The big cloud providers, AWS, Google and Microsoft are all offering ML algorithms as part of their cloud processing services. However, for a broadcaster looking to try out the technologies, cloud processing may not be the optimum solution. Most broadcasters have extensive on-premise content archives, and to use cloud processing means upload and download costs. The alternative is to use on-premise processing adjacent to the media file storage array.
It is this latter market that Dell EMC can address with a new range of AI processing appliances. The company has launched Ready Solutions for AI, with specialized designs for machine learning with Hadoop and deep learning with NVIDIA. The aim is to simplify AI environments, deliver faster, and leverage Dell EMC’s proven expertise to help organizations realize the full potential of AI.
Deep Learning with NVIDIA
The company has engineered the deep learning design in collaboration with NVIDIA to be built around Dell EMC PowerEdge servers with NVIDIA Tesla V100 Tensor Core GPUs.
Key features include:
- PowerEdge R740xd and C4140 servers with four NVIDIA Tesla V100 SXM2 Tensor Core GPUs. With 640 tensor cores, the Tesla V100 was the first to break the 100 teraFLOPS barrier for deep learning performance5
- EMC Isilon F800 All-Flash Scale-out NAS storage for a deep learning enables analyzing large datasets concurrently for faster results
- Bright Cluster Manager for Data Science in combination with the Dell EMC Data Science Provisioning Portal to set up, provision, monitor and manage the cluster
Machine Learning with Hadoop
Dell EMC Ready Solutions for AI, Machine learning with Hadoop builds on the power of tested and proven Dell EMC Ready Solutions for Hadoop (open-source software for reliable, scalable, distributed computing), and is created in partnership with Cloudera and Intel . This design includes an optimized solution stack, along with data science and framework optimization to get up and running quickly, and allows expansion of existing Hadoop environments for machine learning.
Key features include:
- PowerEdge R640 and R740xd servers
- Cloudera Data Science Workbench – for fast, easy and secure self-service data science for the enterprise.
- Apache Spark – the open source unified data analytics engine for Big Data and Machine Learning
- Dell EMC Data Science Provisioning Engine – provides pre-configured containers allowing data scientists access to the Intel BigDL distributed deep learning library on the Spark framework.
The new Ready Solutions for AI were built to simplify AI, deliver faster, deeper insights, and leverage the company’s proven AI expertise. Organizations no longer have to individually source and piece together their own solutions. Instead, they can rely on a Dell EMC-designed and validated set of best-of-breed technologies for software – including AI frameworks and libraries - with compute, networking and storage. With a portfolio of services from consulting to deployment, support and education, customers can drive the rapid adoption and optimization of their AI environments.
The Dell EMC Ready Solutions are available now in the United States. Availability rolls out in Brazil, Canada, Mexico, France, Germany, UK, Australia, China, India and Japan within 60 days.
You might also like...
Today’s broadcast engineers face a unique challenge, one that is likely unfamiliar to these professionals. The challenge is to design, build and operate IP-centric solutions for video and audio content.
Broadcasting used to be simple. It required one TV station sending one signal to multiple viewers. Everyone received the same imagery at the same time. That was easy.
Saving dollars is one of the reasons broadcasters are moving to IP. Network speeds have now reached a level where real-time video and audio distribution is a realistic option. Taking this technology to another level, Rohde and Schwarz demonstrate in…
Are you an IT engineer having trouble figuring out why the phones, computers and printer systems work but the networked video doesn’t? Or maybe you have 10-15 years of experience with video production equipment but really don’t understand why…
As the television business has become more global, and evolving consumer devices spawn the need for ever more formats, there has been an explosion of the number of versions that are needed for an item of content. The need to…