Agentic AI
Autonomous intelligence that thinks, plans, and acts independently to solve complex problems and achieve your goals.
Explore the FutureAutonomous intelligence that thinks, plans, and acts independently to solve complex problems and achieve your goals.
Explore the FutureAgentic AI is the next evolution of artificial intelligence, which uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems. Unlike traditional generative AI models that follow a basic “request-and-respond” framework, agentic AI systems (also called AI agents) ingest data from multiple sources to analyze challenges, develop strategies, and complete tasks independently. They can orchestrate resources, collaborate with other agents, and utilize tools to solve complex business problems. AI agents go beyond content generation to execute complex tasks by perceiving, reasoning, planning and acting on data. Teams of specialized agents can work together in multi-agent systems to solve complex, domain-specific problems. AI agents utilize tools such as calculators, browsers, text editors and other such separate software to solve problems – allowing enterprises to take advantage of their existing infrastructure to build and deploy AI agents.
The opportunities for AI agents deployed in the Federal Government is massive and set to become a cornerstone of the new digital workforce. Soon, each worker will collaborate with thousands of highly specialized agents, equipped with deep domain and industry knowledge, to enhance productivity and efficiency.
AI agents are meant to achieve a goal that solves a problem – not just produce a response. They apply logic and evaluate multiple possibilities in order to formulate the best solution.
AI agents break down tasks into steps, analyze dynamic environments, learn from feedback, and adjust their strategies accordingly.
Custom AI agents are trained on proprietary business data, ensuring better decision-making and task execution specific to their needs.
Unlike traditional or generative AI which assists in decision-making, AI agents can execute multi-step processes, reducing manual effort and operational overhead to deliver better customer experiences.
Through reinforcement learning and feedback loops, or “data flywheels,” agents refine their decision-making over time, improving accuracy and efficiency.
AI agents integrate into existing systems and processes, becoming, in essence, a new digital workforce that help to improve employee productivity.
Emergency response agencies operate in dynamic, high-pressure environments where timely, informed decisions are critical. Agentic AI enables rapid information synthesis, real-time coordination. Read More…
The engineer is responsible for ensuring multiple tactical systems are operational before deployment. Each system pulls real-time telemetry from embedded sensors, various simulations, and satellite feeds. Read More…
Researchers often work with massive datasets, high-performance simulations, and time-consuming literature reviews. Discovering new materials with specific properties—such as ultra-light alloys for aerospace, or advanced conductors for defense applications—requires cross-disciplinary knowledge, complex modeling, and iterative experimentation. Read More…
With NVIDIA Workbench, you can easily scale your Generative AI projects from laptop to workstation, to data center or cloud with a few clicks.
NVIDIA AI Workbench is a free development environment manager for data scientists, researchers and developers to create, customize, and collaborate on AI applications on GPU systems that manages your containers, environment, and configurations.
AI Workbench is built for AI and ML development, rapid prototyping, and providing speed and agility to get up and running with different SDKs, environments, and toolkits on whatever system you need to use.
Utilizing the Dell PowerEdge XE Platform offering support for NVIDIA GPUs. This Example configuration serves to transform a trained model into one that is ready for production use. It provides an example of how we can create a general-purpose generative AI solution to meet specific Gen-AI application requirements.
In this Proof of Concept, we investigate the ability to perform scale-out inferencing for production and to utilize a similar inferencing software stack.
The PoC highlights the following:
Contact us for more details on this Proof of Concept highlighting the Dell PowerEdge XE Platform powered by NVIDIA HGX H200 GPUs.
The PowerEdge XE9680 adds support for NVIDIA H200 Tensor Core GPUs. The NVIDIA HGX H200 has an expanded 141 GB of memory per GPU, enabling the PowerEdge XE9680 to accommodate more AI model parameters for training and inferencing in the same air-cooled 6RU profile for a lower TCO. The NVIDIA BlueField-3 SuperNIC accelerates and offloads the cluster network traffic common in large AI models, enabling direct GPU-to-GPU communication and speeding up time to solutions.
Wildflower Intl. will help you harness the full power of AI with high-performance workstation deployments. Leverage advanced AI capabilities to accelerate design and engineering workflows, enhance decision-making, and drive innovation across your agency. Contact Wildflower today to connect with our team of Federal experts.
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