The integrations will enable organizations adopting NVIDIA AI Enterprise, the software layer of the NVIDIA AI platform, to take advantage of the Weights & Biases MLOps platform to accelerate deep learning workloads across computer vision, natural language processing, and generative AI. "Weights & Biases' goal is to streamline the workflow for all ML practitioners," said Seann Gardiner, VP Business Development & International at Weights & Biases. "The integrations we've built in collaboration with NVIDIA will accelerate organizations of all sizes to develop and adopt AI to transform their offerings and operations." "Enterprises across industries are adopting artificial intelligence to provide customers with the leading performance of today's AI-powered applications," said Anne Hecht, Senior Director of AI Software at NVIDIA. "NVIDIA AI Enterprise combined with Weights & Biases MLOps software gives enterprises an ideal platform for developing and deploying transformative AI."

Promising more timely deliveries for consumers around the globe, NVIDIA's cuOpt real-time route optimization software has set records on a key route optimization benchmark. NVIDIA cuOpt set three new records on the widely followed Li & Lim pickup and delivery benchmark. Last-mile delivery is the most expensive part of the logistics industry, representing over 40% of overall supply chain cost and carbon footprint, according to Gartner. Nearly 150 billion parcels are shipped every year, according to Pitney Bowes. AT&T is using cuOpt to optimize routes for 30,000 technicians.

There are many exciting advancements made in the field of artificial intelligence (AI), like machine learning at the edge, explainable AI, and adversarial machine learning. This rapid progression of AI is accelerating industry innovations, including medical imaging, speech recognition, robotics, logistics, and cybersecurity. While many enterprises are exploring new use cases and possibilities for AI, a considerable number of IT teams, business units, and stakeholders still need to familiarize themselves with AI and analytics technology. Businesses require a platform that gives them access to catalogs of AI tools and information to guide them along their AI journey and help them accelerate and implement AI technologies at scale. Ronald van Loon is a NVIDIA partner and had the opportunity to discuss the new release of NVIDIA AI Enterprise 3.0 to support and accelerate business AI workloads.

Expanding their longstanding alliance, Oracle and NVIDIA today announced a multi-year partnership to help customers solve business challenges with accelerated computing and AI. The collaboration aims to bring the full NVIDIA accelerated computing stack -- from GPUs to systems to software -- to Oracle Cloud Infrastructure (OCI). OCI is adding tens of thousands more NVIDIA GPUs, including the A100 and upcoming H100, to its capacity. Combined with OCI's AI cloud infrastructure of bare metal, cluster networking, and storage, this provides enterprises a broad, easily accessible portfolio of options for AI training and deep learning inference at scale. "To drive long-term success in today's business environment, organizations need answers and insight faster than ever," said Safra Catz, CEO, Oracle.

Oracle and Nvidia announced Tuesday a new partnership that promises to drive accelerated computing and Artificial Intelligence (AI) functionality for Oracle Cloud Infrastructure (OCI). Oracle is bringing more Nvidia hardware to OCI and Nvidia's AI Enterprise platform will be available on OCI instances, the companies said, adding that the development is part of a new multi-year partnership signed between the two businesses. "Combined with OCI's AI cloud infrastructure of bare metal, cluster networking, and storage, this provides enterprises a broad, easily accessible portfolio of options for AI training and deep learning inference at scale," Oracle and Nvidia said. Oracle CEO Safra Catz said in a statement that the expanded alliance with Nvidia will help Oracle deliver new solutions in industries ranging from healthcare to manufacturing, telecommunications to financial services. Jensen Huang, Nvidia CEO and founder, underscored his now-familiar mantra that AI and accelerated computing are the future of business.

Nvidia has rolled out the latest version of its AI Enterprise suite for GPU-accelerated workloads, adding integration for VMware's vSphere with Tanzu to enable organisations to run workloads in both containers and inside virtual machines. Available now, Nvidia AI Enterprise 1.1 is an updated release of the suite that GPUzilla delivered last year in collaboration with VMware. It is essentially a collection of enterprise-grade AI tools and frameworks certified and supported by Nvidia to help organisations develop and operate a range of AI applications. That's so long as those organisations are running VMware, of course, which a great many enterprises still use in order to manage virtual machines across their environment, but many also do not. However, as noted by Gary Chen, research director for Software Defined Compute at IDC, deploying AI workloads is a complex task requiring orchestration across many layers of infrastructure.

Enterprises can begin to run trials of their AI projects using VMware vSphere with Tanzu together with Nvidia AI Enterprise software suite, as part of moves by both companies to further simplify AI development and application management. By extending testing to vSphere with Tanzu, Nvidia boasts it will enable developers to run AI workloads on Kubernetes containers within their existing VMware environments. The software suite will run on mainstream Nvidia-certified systems, the company said, noting it would provide a complete software and hardware stack suitable for AI development. "Nvidia has gone and invested in building all of the next-generation cloud application-level components, where you can now take the NGC libraries, which are container-based, and run those in a Kubernetes orchestrated VMware environment, so you're getting the ability now to go and bridge the world of developers and infrastructure," VMware cloud infrastructure business group marketing VP Lee Caswell told media. The move comes off the back of VMware announcing Nvidia AI Enterprise in March.

Hundreds of thousands of companies worldwide will now have the ability to run AI on VMware vSphere and industry-standard servers thanks to NVIDIA software. A comprehensive software set of AI tools and frameworks is now available from NVIDIA, enabling VMware vSphere users to virtualize AI workloads on NVIDIA-Certified SystemsTM. During the epidemic, companies are adopting AI more and more as they realize the benefits of automation and big data analytics. AI is vital to their digital transformation initiatives. According to a separate McKinsey survey, 30 percent of firms are running AI pilots, and nearly half have integrated at least one AI capability into their typical business operations.

After months in early release, Nvidia today announced the general availability of Nvidia AI Enterprise, a new software offering that's designed to bring AI capabilities to the masses via VMware's vSphere. The announcement also includes precertification of AI Enterprise running on a handful of industry-standard X64 servers (equipped with GPUs, of course), as well as a partnership with Domino Data Labs for MLOps. "AI is real and it has real value," said Manuvir Das, Nvidia's head of enterprise computing. Das knows it's real because Nvidia has helped thousands of customers deploy AI into their operations. However, AI has also proven to be difficult to implement, he said. "And the reason is because, on the one hand, it's an end-to-end problem, from the acquisition of data to the training to produce models and then deploy the models to production," Das said.

NVIDIA today announced the availability of NVIDIA AI Enterprise, a comprehensive software suite of AI tools and frameworks that enables the hundreds of thousands of companies running VMware vSphere to virtualize AI workloads on NVIDIA-Certified Systems . Leading manufacturers Atos, Dell Technologies, GIGABYTE, Hewlett Packard Enterprise, Inspur, Lenovo and Supermicro are offering NVIDIA-Certified Systems optimized for AI workloads on VMware vSphere with NVIDIA AI Enterprise. Separately, Dell Technologies today announced Dell EMC VxRail as the first hyperconverged platform to be qualified as an NVIDIA-Certified System for NVIDIA AI Enterprise. To help teams of data scientists run their AI workloads most efficiently, Domino Data Lab today announced it is validating its Domino Enterprise MLOps Platform with NVIDIA AI Enterprise, which runs on mainstream NVIDIA-Certified Systems. "The first wave of AI has been powered by specialized infrastructure that focused adoption on industry pioneers," said Manuvir Das, head of Enterprise Computing at NVIDIA.