Eighty-five percent of the world's enterprises will be using artificial intelligence (AI) - including machine learning (ML), natural language processing (NLP) and pattern recognition - by 2026, according to IDC. That's just a few years from now, but there are still a few hurdles to clear before AI is fully mainstream, as IDC also reports that the lack of purpose-built infrastructure is often the cause of AI projects failing.
Let's face it, designing, deploying and maintaining separate AI systems can create a roadblock to success when rapidly evolving AI technologies aren't integrated into traditional application environments. That's why
Using the latest NVIDIA AI Enterprise software suite running on
The integrated solution lets IT teams run accelerated and containerized AI workloads alongside existing applications in their
NVIDIA just announced the latest version of NVIDIA AI Enterprise, available with Dell AI solutions. It includes AI frameworks and containers for performance-optimized data science, and training and inference frameworks and tools that simplify building, sharing and deploying AI software.
NVIDIA AI Enterprise 2.0 brings enterprise-grade AI to everyone, everywhere on every platform. Here are just a few of the new features:
* Red Hat® OpenShift® is now certified, extending support to both bare-metal and
* Deploy AI on CPU-only Dell PowerEdge servers. Teams can run AI on GPU-accelerated Dell PowerEdge NVIDIA-Certified Systems with or without GPUs.
* Upskill the workforce with NVIDIA training. Enterprise Edition subscribers receive access to an instructor-led workshop and two self-paced courses for every 10 licenses, so developers, data scientists and IT professionals can get the most out of the NVIDIA AI Enterprise upgrade.
Find more answers with AI
With AI adoption increasing, enterprises are actively looking to optimize investments and harness the innovation as AI technology and infrastructure components continue to mature. Year-over-year spending plans to continue, across 62% of enterprises, according to ESG, along with investments in key technology areas, including compute and graphics nodes.
From deep learning and AI model training to demanding real-time inferencing, an infrastructure strategy built to find answers must be able to harness innovation that scales performance on demand, while democratizing AI projects to standardized compute platforms, within an AI framework such as NVIDIA AI Enterprise.
The next step in performance was announced today. The new NVIDIA H100 Tensor Core GPU, powered by the NVIDIA Hopper architecture, delivers the next massive leap for PowerEdge servers, securely accelerating diverse workloads, from enterprise to exascale HPC and trillion-parameter AI.
With the planned support of NVIDIA H100 into the Dell PowerEdge portfolio and Validated Designs, customers will be able to transform their AI infrastructures and compute strategy to be future-ready for exascale while making it easier to kickoff AI initiatives that change businesses - and the world. Adopt AI with confidence
At
With the integration between
Enterprises can experience AI with
Now, every organization can increase the number of successful AI projects in production. Learn more about
.
(C) 2022 M2 COMMUNICATIONS, source