Crossing the chasm and reaching its iPhone moment, generative AI must scale to fulfill exponentially increasing demands. Reliability and uptime are critical for building generative AI at the enterprise level, especially when AI is core to conducting business operations. NVIDIA is investing its expertise into building a solution for those enterprises ready to take the leap.
Introducing NVIDIA AI Enterprise 4.0
The latest version of NVIDIA AI Enterprise accelerates development through multiple facets with production-ready support, manageability, security, and reliability for enterprises innovating with generative AI.
Quickly train, customize, and deploy LLMs at scale with NVIDIA NeMo
Generative AI models have billions of parameters and require an efficient data training pipeline. The complexity of training models, customization for domain-specific tasks, and deployment of models at scale require expertise and compute resources.
NVIDIA AI Enterprise 4.0 now includes NVIDIA NeMo, an end-to-end, cloud-native framework for data curation at scale, accelerated training and customization of large language models (LLMs), and optimized inference on user-preferred platforms. From cloud to desktop workstations, NVIDIA NeMo provides easy-to-use recipes and optimized performance with accelerated infrastructure, greatly reducing time to solution and increasing ROI.
Build generative AI applications faster with AI workflows
NVIDIA AI Enterprise 4.0 introduces two new AI workflows for building generative AI applications: AI chatbot with retrieval augmented generation and spear phishing detection.
The generative AI knowledge base chatbot workflow, leveraging Retrieval Augmented Generation, accelerates the development and deployment of generative AI chatbots tuned on your data. These chatbots accurately answer domain-specific questions, retrieving information from a company’s knowledge base and generating real-time responses in natural language. It uses pretrained LLMs, NeMo, NVIDIA Triton Inference Server, along with third-party tools including Langchain and vector database, for training and deploying the knowledge base question-answering system.
The spear phishing detection AI workflow uses NVIDIA Morpheus and generative AI with NVIDIA NeMo to train a model that can detect up to 90% of spear phishing e-mails before they hit your inbox.
Defending against spear-phishing e-mails is a challenge. Spear phishing e-mails are indistinguishable from benign e-mails, with the only difference between the scam and legitimate e-mail being the intent of the sender. This is why traditional mechanisms for detecting spear phishing fall short.
Develop AI anywhere
Enterprise adoption of AI can require additional skilled AI developers and data scientists. Organizations will need a flexible high-performance infrastructure consisting of optimized hardware and software to maximize productivity and accelerate AI development. Together with NVIDIA RTX 6000 Ada Generation GPUs for workstations, NVIDIA AI Enterprise 4.0 provides AI developers a single platform for developing AI applications and deploying them in production.
Beyond the desktop, NVIDIA offers a complete infrastructure portfolio for AI workloads including NVIDIA H100, L40S, L4 GPUs, and accelerated networking with NVIDIA BlueField data processing units. With HPE Machine Learning Data Management, HPE Machine Learning Development Environment, Ubuntu KVM and Nutanix AHV virtualization support, organizations can use on-prem infrastructure to power AI workloads.
Manage AI workloads and infrastructure
NVIDIA Triton Management Service, an exclusive addition to NVIDIA AI Enterprise 4.0, automates the deployment of multiple Triton Inference Servers in Kubernetes with GPU resource-efficient model orchestration. It simplifies deployment by loading models from multiple sources and allocating compute resources. Triton Management Service is available for lab experience on NVIDIA LaunchPad.
NVIDIA AI Enterprise 4.0 also includes cluster management software, NVIDIA Base Command Manager Essentials, for streamlining cluster provisioning, workload management, infrastructure monitoring, and usage reporting. It facilitates the deployment of AI workload management with dynamic scaling and policy-based resource allocation, providing cluster integrity.
New AI software, tools, and pretrained foundation models
NVIDIA AI Enterprise 4.0 brings more frameworks and tools to advance AI development. NVIDIA Modulus is a framework for building, training, and fine-tuning physics-machine learning models with a simple Python interface.
Using Modulus, users can bolster engineering simulations with AI and build models for enterprise-scale digital twin applications across multiple physics domains, from CFD and Structural to Electromagnetics. The Deep Graph Library container is designed to implement and train Graph Neural Networks that can help scientists research the graph structure of molecules or financial services to detect fraud.
Lastly, three exclusive pretrained foundation models, part of NVIDIA TAO, speed time to production for industry applications such as vision AI, defect detection, and retail loss prevention.
NVIDIA AI Enterprise 4.0 is the most comprehensive upgrade to the platform to date. With enterprise-grade security, stability, manageability, and support, enterprises can expect reliable AI uptime and uninterrupted AI excellence.
