AI is Rapidly Transforming How Organizations Solve Complex Challenges
The early stages of enterprise AI adoption focused on using large language models to create chatbots. Now, enterprises are using agentic AI to create intelligent systems that reason, act, and execute complex tasks with a degree of autonomy.
Jacob Liberman on Agentic AI
Jacob Liberman, director of product management at NVIDIA, joined the NVIDIA AI Podcast to explain how agentic AI bridges the gap between powerful AI models and practical enterprise applications.
Freeing Human Workers from Time-Consuming Tasks
Enterprises are deploying AI agents to free human workers from time-consuming and error-prone tasks. This allows people to spend more time on high-value work that requires creativity and strategic thinking.
Collaboration between AI Agents and Human Workers
Liberman anticipates it won’t be long before teams of AI agents and human workers collaborate to tackle complex tasks requiring reasoning, intuition, and judgment. For example, enterprise software developers will work with AI agents to develop more efficient algorithms. And medical researchers will collaborate with AI agents to design and test new drugs.
NVIDIA AI Blueprints
NVIDIA AI Blueprints help enterprises build their own AI agents – including many of the use cases listed above. "Blueprints are reference architectures implemented in code that show you how to take NVIDIA software and apply it to some productive task in an enterprise to solve a real business problem," Liberman said.
Customizable AI Blueprints
The blueprints are entirely open source. A developer or service provider can deploy a blueprint directly, or customize it by integrating their own technology.
Popular NVIDIA Blueprints
Liberman highlighted the versatility of the AI Blueprint for customer service, for example, which features digital humans. "The digital human can be made into a bedside digital nurse, a sportscaster or a bank teller with just some verticalization," he said. Other popular NVIDIA Blueprints include a video search and summarization agent, an enterprise multimodal PDF chatbot, and a generative virtual screening pipeline for drug discovery.
Time Stamps
1:14 – What is an AI agent?
17:25 – How software developers are early adopters of agentic AI.
19:50 – Explanation of test-time compute and reasoning models.
23:05 – Using AI agents in cybersecurity and risk management applications.
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Conclusion
Agentic AI is rapidly transforming how organizations solve complex challenges. By deploying AI agents, enterprises can free human workers from time-consuming tasks and enable them to focus on high-value work. NVIDIA AI Blueprints provide a flexible and customizable solution for building agentic AI systems.
FAQs
Q: What is an AI agent?
A: An AI agent is an intelligent system that reasons, acts, and executes complex tasks with a degree of autonomy.
Q: How do software developers use agentic AI?
A: Software developers are early adopters of agentic AI, using it to develop more efficient algorithms and automate repetitive tasks.
Q: What is a test-time compute and reasoning model?
A: A test-time compute and reasoning model is a type of AI model that can reason and act at runtime, using data from the environment to inform its decisions.
Q: Can AI agents be used in cybersecurity and risk management applications?
A: Yes, AI agents can be used in cybersecurity and risk management applications to detect and respond to threats, and to identify potential risks.
