Training Example: Amazon Web Services (AWS) – Review the Data, Give Your Score & Compare to the Real AI Evaluation

[H1] Meet your unique security requirements
AWS is designed for security, protecting even the most sensitive workloads—including government, financial services, and healthcare

Start free with AWS

[IMG: Missing alt text value]

[H2] What's new
Catch up on the most talked-about launches, updates, and success stories across AWS.

Loading

Loading

Loading

Loading

Loading

[H2] From startups to enterprises—AWS is how leaders have powered innovation for 20 years
Join the largest global community of innovators who trust AWS to accelerate transformation and redefine industries.

View more stories

1 / 5

Aerospace & Satellite

[IMG: Missing alt text value]

[H2] Blue Origin advances space exploration with agentic AI on AWS

View the story

Advertising & Marketing

[IMG: Missing alt text value]

[H2] Pinterest drives visual discovery for 600 million monthly users building on Amazon EC2 and S3

View the story

Automotive

[IMG: Missing alt text value]

[H2] Mercedes-Benz drives innovation with AWS AI

View the story

Artificial Intelligence

[IMG: Missing alt text value]

[H2] WRITER is the end-to-end platform for enterprises to build, activate, and supervise AI agents

View the story

Media & Entertainment

[IMG: Missing alt text value]

[H2] Condé Nast modernizes century-old publishing with new data and AI strategy on AWS

View the story

[H1]
I want to see new customer stories in

manufacturing

[H2] Powering what’s next in every industry
Discover how AWS helps organizations in every sector build, scale, and transform.

Explore AWS for your industry

Loading

Loading

Loading

Loading

Loading

[H2] AWS Global Infrastructure

[H5] The AWS Cloud spans 123 Availability Zones within 39 Geographic Regions, with announced plans for 7 more Availability Zones and 2 more AWS Regions in the Kingdom of Saudi Arabia, and Chile.

North America

South America

Europe

Middle East

Africa

Asia Pacific

Australia and New Zealand

AWS Coverage Regions North America

[H3]

Geographic Regions 9

AWS GovCloud (US-East)

AWS GovCloud (US-West)

Canada (Central)

Canada West (Calgary)

Mexico (Central)

US West (Northern California)

US East (Northern Virginia)

US East (Ohio)

US West (Oregon)

Available

Coming soon

[H3]

Edge Locations 31

The AWS Cloud in North America has 31 Availability Zones within 9 Geographic Regions, with 31 Edge Network Locations and 3 Edge Cache Locations.

Ashburn, VA

Atlanta. GA

Boston, MA

Chicago, IL

Columbus, OH

Dallas/Fort Worth, TX

Denver, CO

Hayward, CA

Houston, TX

Jacksonville, FL

Kansas City, MO

Los Angeles, CA

Miami, FL

Minneapolis, MN

Montreal, QC

Nashville, TN

New York, NY

Newark, NJ

Palo Alto, CA

Phoenix, AZ

Philadelphia, PA

Portland, OR

Queretaro, MX

Salt Lake City, UT

San Jose, CA

Seattle, WA

South Bend, IN

St. Louis, MO

Tampa Bay, FL

Toronto, ON

Washington D.C.

[H1]
I want to

try AWS for free

[H2] Did you find what you were looking for today?
Let us know so we can improve the quality of the content on our pages

Yes

No

[H1] Contact AWS
General support for sales, compliance, and subscribers

[H2] Want to speak with an AWS sales specialist?

Get in touch

[H2] Chat online or talk by phone

Connect with support directly Monday through Friday

Request form

[H2] Request AWS sales support

Submit a sales support form

[H2] Compliance support

Request support related to AWS compliance
Connect with AWS compliance support

[H2] Subscriber support services

[H3] Technical support

Support for service related technical issues. Unavailable under the Basic Support Plan.

Sign in and submit request

[H3] Account or billing support

Assistance with account and billing related inquiries

Sign in to request

[H3] Wrongful charges support

Received a bill for AWS, but don't have an AWS account?

Learn more

[H3] Support plans

Learn about AWS support plan options

See Premium Support options

[H2] AWS sign-in resources
See additional resources for issues related to logging into the console

[H3]
Help signing in to the console

Need assistance to sign in to the AWS Management Console?
View documentation

[H3]
Trouble shoot your sign-in issue

Tried sign in, but the credentials didn’t work? Or don’t have the credentials to access AWS root user account?

View solutions

[H3]
Help with multi-factor authentication (MFA) issues

Lost or unusable Multi-Factor Authentication (MFA) device
View solution

[H3]
Still unable to sign in to your AWS account?

If you are still unable to log into your AWS account please fill out this form.
View form

[H2] Additional resources

[H3] Self-service

re:Post provides access to curated knowledge and a vibrant community that helps you become even more successful on AWS

View AWS re:Post

[H3] Service limit increases

Need to increase to service limit? Fill out a quick request form

Sign in to request

[H3] Report abuse

Report abusive activity from Amazon Web Services Resources

Report suspected abuse

[H3] Amazon.com support

Request Kindle or Amazon.com support

View on amazon.com

[H2] Did you find what you were looking for today?
Let us know so we can improve the quality of the content on our pages

Yes

No

[H1] Why AWS?
Amazon Web Services is the world’s most comprehensive and broadly adopted cloud, enabling customers to build almost anything they can imagine. We offer the greatest choice of innovative cloud and AI capabilities and expertise, on the most extensive global infrastructure, with industry-leading security, reliability, and performance.

Explore our Industry Solutions

Check out our latest news

[H2] What is AWS

Explore how millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

Watch the video

Play

[IMG: Missing alt text value]

[H2] Breakthrough innovations

AWS is committed to delivering industry-first cloud capabilities for our customers. The scale and scope at which we operate enable us to look around corners and think years ahead—to innovate on your behalf. We have delivered the first cloud-native services for compute, serverless, storage, and relational databases, and the first fully managed, end-to-end machine learning suite.

Learn about our culture of innovation

[IMG: Missing alt text value]

[H2] Security you can trust

Security is our highest priority. We've architected our infrastructure and services to provide you with the most secure cloud computing environment available today. AWS helps meet the unique security requirements of the most sensitive workloads, trusted by government agencies, financial institutions, and healthcare organizations worldwide.

Visit our Trust Center

[IMG: Missing alt text value]

[H2] Greatest choice

AWS gives you the greatest choice and flexibility by offering the broadest and deepest set of cloud and AI capabilities to build optimized solutions that balance performance and cost-effectiveness. With AWS, organizations modernize faster, scale more efficiently, and maintain competitive advantages through access to cutting-edge technologies and industry-specific solutions.

Discover our services

[IMG: Missing alt text value]

[H2] Largest and most extensive global infrastructure

We've built the world’s largest and most extensive global
infrastructure, providing you the capacity you need. Our infrastructure is uniquely architected to offer unparalleled scalability, performance, and reliability for your applications whether they are running in the cloud, on-premises, or at the edge.

Explore our Global Infrastructure

[H2] Trusted partners and solutions

AWS and our partners share an obsession over customer success and are committed to helping you find the right solutions. By combining our partners’ deep, specialized expertise with AWS services, infrastructure, and AWS Marketplace, we empower you to achieve exceptional business outcomes with greater speed and confidence.

Work with a partner

[IMG: Missing alt text value]

[H2] Longest-running Magic Quadrant Leader for SCPS

Gartner has recognized AWS as a Magic Quadrant Leader for Strategic Cloud Platform Services (SCPS) for the 15th straight year. AWS placed highest in the Ability to Execute axis of measurement among the eight vendors named in the report.

Read the Gartner report

[H2] Built for industry breakthroughs
AWS provides proven architectures, compliance guides, and customer success stories to help organizations transform their industry.

Explore AWS solutions for your industry

[IMG: Missing alt text value]

[H3] Financial Services: Accelerate innovation from secure operations to business growth

Transform financial services through breakthrough technology and innovation while maintaining security and compliance at global scale.

Learn more

[IMG: Missing alt text value]

[H3] Media & Entertainment: Deliver breakthrough experiences to global audiences

Create content faster, connect workflows and teams to increase efficiency, and enhance your entertainment experiences to captivate audiences.

Learn more

[IMG: Missing alt text value]

[H3] Manufacturing: Drive innovation and enhance efficiency in operations

Transform your operations and explore how AWS helps manufacturers speed time-to-market, improve operational efficiency, and increase revenue.

Learn more

[IMG: Missing alt text value]

[H3] Healthcare & Life Sciences: Power healthcare breakthroughs from insights to patient impact

Remove barriers between groundbreaking research and clinical implementation to accelerate the delivery of innovative healthcare solutions to patients worldwide.

Learn more

[H2] Featured customer stories

Loading

Loading

Loading

Loading

Loading

[H2] Latest news

[H2] Build, deploy, and operate highly capable agents at scale with Amazon Bedrock AgentCore

Learn how

[H2] Access OpenAI's open weight models in Amazon Bedrock

Learn how

[H2] Did you find what you were looking for today?
Let us know so we can improve the quality of the content on our pages

Yes

No

[H1] What is cloud computing?
Cloud computing is the on-demand delivery of IT resources over the Internet with pay-as-you-go pricing. Instead of buying, owning, and maintaining physical data centers and servers, you can access technology services, such as computing power, storage, and databases, on an as-needed basis from a cloud provider like Amazon Web Services (AWS).

Create an AWS Account

Connect with an expert

[H2] Who is using cloud computing?

Organizations of every type, size, and industry are using the cloud for a wide variety of use cases, such as data backup, disaster recovery, email, virtual desktops, software development and testing, big data analytics, and customer-facing web applications. For example, healthcare companies are using the cloud to develop more personalized treatments for patients. Financial services companies are using the cloud to power real-time fraud detection and prevention. And video game makers are using the cloud to deliver online games to millions of players around the world.

[H2] Benefits of cloud computing

[H3] Agility

The cloud gives you easy access to a broad range of technologies so that you can innovate faster and build nearly anything that you can imagine. You can quickly spin up resources as you need them–from infrastructure services, such as compute, storage, and databases, to Internet of Things, machine learning, data lakes and analytics, and much more.
You can deploy technology services in a matter of minutes, and get from idea to implementation several orders of magnitude faster than before. This gives you the freedom to experiment, test new ideas to differentiate customer experiences, and transform your business.

[H3] Elasticity

With cloud computing, you don’t have to over-provision resources up front to handle peak levels of business activity in the future. Instead, you provision the amount of resources that you actually need. You can scale these resources up or down to instantly grow and shrink capacity as your business needs change.

[H3] Cost savings

The cloud allows you to trade fixed expenses (such as data centers and physical servers) for variable expenses, and only pay for IT as you consume it. Plus, the variable expenses are much lower than what you would pay to do it yourself because of the economies of scale.

[H3] Deploy globally in minutes

With the cloud, you can expand to new geographic regions and deploy globally in minutes. For example, AWS has infrastructure all over the world, so you can deploy your application in multiple physical locations with just a few clicks. Putting applications in closer proximity to end users reduces latency and improves their experience.

[H2] Types of cloud computing
The three main types of cloud computing include Infrastructure as a Service, Platform as a Service, and Software as a Service. Each type of cloud computing provides different levels of control, flexibility, and management so that you can select the right set of services for your needs.

[H3]
Infrastructure as a Service (IaaS)

IaaS contains the basic building blocks for cloud IT. It typically provides access to networking features, computers (virtual or on dedicated hardware), and data storage space. IaaS gives you the highest level of flexibility and management control over your IT resources. It is most similar to the existing IT resources with which many IT departments and developers are familiar.

[H3]
Platform as a Service (PaaS)

PaaS removes the need for you to manage underlying infrastructure (usually hardware and operating systems), and allows you to focus on the deployment and management of your applications. This helps you be more efficient as you don’t need to worry about resource procurement, capacity planning, software maintenance, patching, or any of the other undifferentiated heavy lifting involved in running your application.

[H3]
Software as a Service (SaaS)

SaaS provides you with a complete product that is run and managed by the service provider. In most cases, people referring to SaaS are referring to end-user applications (such as web-based email). With a SaaS offering, you don’t have to think about how the service is maintained or how the underlying infrastructure is managed. You only need to think about how you will use that particular software.

[H2] Powering Customer Innovation

View all customer stories

Loading

Loading

Loading

Loading

Loading

[H2] FAQs

[H3] What are cloud services?

Cloud services are IT resources managed by AWS and delivered on demand over the internet. Traditionally, organizations had to purchase and configure everything from server hardware and storage systems to networking and security technologies before launching any digital system. Provisioning and managing IT infrastructure is expensive, complicated; and takes time away from innovation.

[H3] What are cloud managed services?

Cloud services are also called cloud managed services because the underlying infrastructure is fully managed by AWS. All required hardware, operating systems, and other infrastructure layers are stored and managed in highly secure AWS data centers distributed around the globe. We purchase and maintain all types of IT resources, making them available as services you can access in your application code.

[H2] Example uses of cloud services
Cloud services can be used for everything—from provisioning servers and storage to data analytics, artificial intelligence, and end-to-end security for every application. Below are a few examples.

[H3] Resizable compute capacity

Access and configure compute capacity as a fully managed cloud service for any type of workload. From Intel, AMD, and Arm processors to Amazon EC2 Mac Instances, and 400 Gbps Ethernet networking, AWS provides cutting-edge computer offerings for flexible use. Choose from hundreds of cloud instance types with the latest processors, operating systems, and purchase models to best match your workload needs. AWS cloud services allow you to quickly scale capacity up or down and pay only for what you use while maintaining complete control of your computing resources.

Learn more about compute on AWS

[H3] Databases and data storage

AWS cloud services include an array of secure, reliable, and highly scalable database options and data storage solutions. You can use cloud services for file, block, and object storage systems. AWS also has cloud services for both SQL and NoSQL databases. Use fully managed relational and non-relational databases to simplify database management, scaling, and backup for operational efficiency.
Learn more about cloud storage on AWS
Learn more about cloud databases on AWS

[H3] Artificial intelligence and machine learning (AI/ML)

Access the most comprehensive, secure, and price-performant AI infrastructure for all your training and inference needs. Improve customer experiences with interactive chatbots and virtual assistants, conversational and predictive analytics, and agent assistance. Boost employee productivity with conversational search, code generation, and automated report generation. Accelerate process optimization with natural language processing and image recognition, data augmentation, and supply chain optimization.

Learn more about AI on AWS

[H3] Networking and content delivery

Deliver applications and content anywhere in the world while maintaining the highest availability levels with AWS networking and content delivery services. Simplify your networking environment and distribute network traffic more efficiently by switching to the cloud. Deliver faster, more secure applications and connect hybrid infrastructure with the highest level of reliability and performance.

Learn more about networking on AWS

[H3] Security, identity and compliance

Cloud services can enhance your security posture and streamline your security operations at scale. Protect your accounts, workloads, and data from unauthorized access. Our cloud services help you manage resources, permissions, and identities, enforce fine-grained policies at network control points, and continuously monitor with automated compliance checks. Secure your workloads in the cloud with network, application, and data protection services from AWS.

Learn more about security on AWS

[H3] Migration and modernization

Application and data modernization require cloud migration so you can innovate continuously while reducing operational costs. AWS migration services provide automation and intelligent recommendations to expedite digital transformation. Use our cloud services to automatically convert your source servers to run natively on AWS, perform non-disruptive tests, and move your applications to the cloud. Discover, assess, convert, and migrate any database or analytics workload with minimal downtime.

Learn more about cloud migration on AWS

[H2] Learn more about cloud computing on AWS

[H3] Pricing

AWS offers a pay-as-you-go approach for pricing. Pricing for each service is unique.

Learn more

[H3] Products

AWS has over 200 fully featured services for a wide range of technologies, industries, and use cases.

Learn more

[H3] Global infrastructure

AWS has the most extensive, reliable, and secure global cloud infrastructure.

Learn more

[H3] Get started

Ready to get started with AWS?

Create an AWS Account

[H1] What Is Agentic AI?

Create an AWS account

What is Agentic AI? What are the characteristics of agentic AI systems? What are the use cases of agentic AI? What are the benefits of agentic AI? What are the types of agentic AI systems? How does agentic AI work? What are the challenges with agentic AI systems? How can AWS support your agentic AI requirements?

[H2] What is Agentic AI?

Agentic AI is an autonomous AI system that can act independently to achieve pre-determined goals. Traditional software follows pre-defined rules, and traditional artificial intelligence also requires prompting and step-by-step guidance. However, agentic AI is proactive and can perform complex tasks without constant human oversight. "Agentic" indicates agency — the ability of these systems to act independently, but in a goal-driven manner.
AI agents can communicate with each other and other software systems to automate existing business processes. But beyond static automation, they make independent contextual decisions. They learn from their environment and adapt to changing conditions, enabling them to perform sophisticated workflows with accuracy.
For example, an agentic AI system can optimize employee shift schedules. If an employee is off sick, the agent can communicate with other employees and readjust the schedule while still meeting project resource and time requirements.

[H2] What are the characteristics of agentic AI systems?

Here are the key features of an agentic AI system.
[H3] Proactive
Agentic AI acts proactively rather than waiting for direct input. Traditional systems are reactive, responding only when triggered and following predefined workflows. In contrast, agentic systems anticipate needs, identify emerging patterns, and take initiative to address potential issues before they escalate. Their proactive behavior is driven by environmental awareness and their ability to evaluate outcomes against long-term goals.
For instance, in a supply chain setting, a traditional logistics platform updates delivery statuses when a user checks in or through periodic notifications. An agentic AI system, however, can monitor inventory levels, track weather conditions, and anticipate shipping delays. It can proactively raise alerts and even reroute shipments to reduce downtime.
[H3] Adaptable
A key feature of agentic AI is its ability to adapt to changing environments and specific domains. Traditional SaaS solutions are built to scale across industries and handle repetitive tasks, but they often lack the depth to understand unique domain-specific situations. Agentic systems fill this gap by using context awareness and domain knowledge, enabling AI agents to respond intelligently. They adjust their actions based on real-time input and can handle complex scenarios that standard solutions cannot.
For example, while a generic customer service platform might respond with predefined answers, an agentic AI system supporting a healthcare provider understands medical terminology and complies with healthcare regulations. It can adapt to evolving patient concerns and delivers more accurate, context-sensitive support.
[H3] Collaborative
Agentic AI is designed to collaborate with humans and with other agentic AI systems. AI agents work as part of a broader team. They can understand shared goals, interpret human intent, and coordinate actions accordingly. They work well in settings that require human oversight or decision-making by considering inputs from multiple sources.
For example, a treatment planning agent can coordinate with several different medical teams to prepare an integrated treatment and follow-up plan for a cancer patient.
[H3] Specialized
Agentic AI typically builds upon multiple hyperspecialized agents, with each focused on a narrow area of expertise. These AI-powered agents coordinate with each other, sharing insights and handing off tasks as needed. This approach enables significantly deeper domain-specific performance.
For instance, in financial services, one agent might specialize in regulatory compliance, another in fraud detection, and another in portfolio optimization. Working together, they can monitor transactions in real time, flagging anomalies and recommending investment adjustments, all while maintaining regulatory compliance.

[H2] What are the use cases of agentic AI?

Agentic AI has unlimited applications and can be fully customized to any requirement. We give some examples of early adoption.
[H3] Supporting research and development
Research and development in any field requires a great deal of manual processes, such as testing hypotheses, gathering research information, collecting data, synthesizing insights across data sources, and more. Agentic AI can reduce the need for human intervention with these manual processes. It streamlines research and better coordinates teams that are working on research and development challenges.
Agentic AI also facilitates multi-agent orchestration, where supervisors use multiple specialist models to construct complex research and development pipelines. For example, agentic AI could draw from recent research published on credible platforms, synthesize the results, plan further tests, and present researchers with the final product they need to investigate. This approach saves a significant amount of time and cost involved in research.
[H3] Code transformation
Agentc AI can use specialized AI-powered agents to remove the complexity of modernization and migration tasks. For example, agentic AI models for .NET can modernize Windows-based .NET applications to Linux significantly faster using machine learning, graph neural networks, Large language models (LLMs), and automated reasoning.
Equally, agentic AI can decompose monolithic z/OS COBOL applications into individual components, reducing the timeframe of this process from months to minutes. Agentic AI offers unmatched speed, scale, and performance in automating application migration and modernization.
[H3] Incident response automation
Whenever an incident occurs, whether due to a vulnerability or a manual error, agentic AI can expedite the incident response process, saving your business time and improving time-to-recovery. Agentic AI can automate the entire incident response pathway, rolling back issues, creating incident reports, and notifying any team members who need to stay informed.
Agentic AI enhances incident response speed while also providing a more specific and in-depth post-incident analysis to prevent the same errors from recurring in the future.
[H3] Customer service automation
In many customer service scenarios, the information that a customer needs is already online in a tutorial or help article. Agentic AI processes customer service inquiries and rapidly searches through available company documents to find a suitable answer that helps them out. If this alone isn’t enough to solve a query, agentic AI can then communicate with the user to gather more information about their case and direct them toward a solution. They are designed with modular components, such as reasoning engines, memory, cognitive skills, and tools, that enable them to remedy the vast majority of problems.
AI-powered agents can operate independently, learn from their environment, adapt to changing conditions, and develop more effective strategies to assist customers. If, after several attempts, it cannot solve a customer’s issue, it then contacts a human support agent and assigns them to the case. Utilizing this form of AI in customer service scenarios alleviates the burden on human teams and enables the vast majority of customer-oriented services to operate 24/7.

[H2] What are the benefits of agentic AI?

There are several business benefits to using agentic AI.
[H3] Increased efficiency
Agentic artificial intelligence enables businesses to simplify the complexity of various challenging or specialized tasks through automation. Instead of relying on human-driven manual practices, using agentic AI can automate tedious processes, freeing up time for your employees. Your employees can use the extra time that agentic AI saves them on more demanding tasks, such as problem-solving, strategic planning, and other drivers of growth.
[H3] Increased user trust
Agentic AI can offer a higher degree of personalization when interacting with customers. By utilizing existing customer data, agentic AI can quickly produce tailored messaging, engage with the customer in their preferred tone, and offer practical product recommendations. Over time, agentic AI improves customer relationships and builds trust between customers and your business.
Businesses can also utilize agentic artificial intelligence to analyze customer feedback, identify the most frequently occurring information, and provide it to product engineers. It can also directly respond to users who leave feedback, creating positive feedback loops where customers feel that their feedback is taken seriously by your company.
[H3] Continuous improvement
Agentic AI can continuously learn and improve, adapting to any tasks assigned to it. It interacts, learns from feedback, and optimizes its decision-making based on this recursive loop. For businesses, this means that it continues to deliver its benefits at higher and higher levels over time.
[H3] Human augmentation
Agentic AI can serve as a fantastic collaboration tool for human agents, enhancing their productivity and reducing the number of laborious manual tasks they must complete. By working alongside agentic AI models, human agents can overcome complex challenges, automate difficult decision-making pathways, and drive their efficiency.

[H2] What are the types of agentic AI systems?

Agentic AI can be single or multi-agent setups. In a single-agentic AI system, one AI agent handles all tasks sequentially. These are preferable when businesses need a faster solution that can work on a well-defined problem or process.
Multi-agentic AI, on the other hand, involves multiple AI agents collaborating to break down complex workflows into smaller segments. This approach is more scalable than single systems and is much more flexible for solving complex scenarios. The vast majority of agentic AI agents refer to this latter, more diverse form of AI deployment.
Here are a few different structures of multi-agent systems.
[H3] Horizontal multi-agent
Horizontal multi-agent AI is a system of working where every AI agent has the same level of technical proficiency and complexity. Each agent specializes in a narrow skill, bringing their findings together to solve a complex problem. This structure utilizes lateral collaboration and communication among the specialized AI agents.
[H3] Vertical multi-agent
In a vertical multi-agent system, there is a hierarchical structure in which lower-level AI agents have ‘easier’ tasks compared to the higher ones. The highest levels of this structure handle tasks that require more processing power and LLMs, such as critical thinking, reasoning, and decision-making. Lower-level AI agents in this structure perform tasks such as collecting data, formatting it, or processing it to pass it to higher levels.

[H2] How does agentic AI work?

Agentic AI agents operate by using a structured pathway that moves through four stages — perceive, reason, act, and learn. Each stage in this process integrates several advanced AI technologies and methods.
[H3] Perceive
At the perception stage, AI agents collect real-time data from a range of diverse sources, ingesting structured, semi-structured, and unstructured data. Agents directly interact with RESTful APIs, gRPC services, and GraphQL endpoints to ingest data as needed from cloud platforms, enterprise systems, and SaaS applications.
In certain legacy systems or those that require interaction with document-heavy environments, optimal character recognition technology (OCR) and natural language processing can help sift through scanned documents for relevant information. At the perceive stage, agents also process data to determine what is useful based on the task context in which they are working.
[H3] Reason
The reasoning stage is powered by LLMs that help to interpret the context of the goals a model has, develop an action plan to follow, and adapt in real-time using new information received through the perceive stage. LLMs employ models that utilize semantic reasoning, error handling, and adjust to any ambiguous user inputs.
Beyond just processing ideas and developing strategy in this stage, some LLMs use predictive machine learning models to manage complex problems. For example, a predictive ML model can forecast surges in demand, enabling better preparation for future use cases.
At this stage, LLMs use long-term memory systems to ensure that situational and context-dependent tasks remain consistent throughout the entire process.
[H3] Act
At the act stage, agentic AI takes action to achieve what was set out by the reasoning stage effectively. As agentic AI can access administrator-installed plugins on each of these external software systems, it can directly interact with and run tasks on these third-party applications.
The act stage orchestrates several subtasks that the agentic models will then tackle sequentially, with specific actions ranging from compiling code to interacting with software and documents, running simulations, migrating applications, and performing functions within a third-party application. For some agentic AI models, actions are gated by human-in-the-loop systems, where developers must verify what the model is doing and approve its actions.
All actions taken by a model are closely monitored and logged, allowing businesses to align with governance and safeguard their use of this technology.
[H3] Learn
The learning stage of agentic AI is what enables these models to continually improve their functionality and effectiveness. The agent utilizes reinforcement learning techniques, such as proximal policy optimization (PPO) and Q-learning, to refine actions based on the success of a specific task within the broader system.
AI agents learn from autonomous agents, LLMs, or through human feedback, all of which can fine-tune the system to improve its functioning. There are several metrics that a model can use to track its performance, including latency, confidence, and success rate. Multi-agent AI typically distributes learning across different agents, sharing information in communal memory layers to enhance the entire system's performance.
Over time, this style of reinforcement learning can utilize successful iterations to improve its overall functioning and enhance efficiency continually.

[H2] What are the challenges with agentic AI systems?

Several challenges are associated with agentic AI and building effective models.
[H3] System design
The process of building

[H1] Cloud Computing Concepts Hub
The Cloud Computing Concepts Hub is the centralized place where you can browse or search for informative articles about cloud computing. You'll find easy-to-understand info about broad topics such as "What is Machine Learning?" and "What is Data Science?" These articles are intended to help you up-level your understanding of frequently asked cloud computing topics.

[H2] Most popular cloud computing concepts

[H3] What is AI?

Artificial intelligence (AI) is the field of computer science dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, creation, and image recognition. Modern organizations collect large volumes of data from diverse sources like smart sensors, human-generated content, monitoring tools, and system logs. The goal with AI is to create self-learning systems that derive meaning from data. Then, AI can apply that knowledge to solve new problems in human-like ways.

Read more about Artificial Intelligence here

[H3] What is Prompt Engineering?

Prompt engineering is the process where you guide generative AI, which requires detailed instructions, solutions to generate desired outputs. In prompt engineering, you choose the most appropriate formats, phrases, words, and symbols that guide the AI to interact with your users more meaningfully. Prompt engineers use creativity plus trial and error to create a collection of input texts, so an application's generative AI works as expected.

Read more about Prompt Engineering here

[H3] What is Generative AI?

Generative artificial intelligence is a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. AI technologies attempt to mimic human intelligence in nontraditional computing tasks like image recognition, natural language processing (NLP), and translation. Generative AI can be trained to learn human language, programming languages, or any complex subject matter. It reuses training data to solve new problems. Generative AI can be used for various purposes, like chatbots, media creation, and product development and design.

Read more about Generative AI here

[H3] What is Conversational AI?

Conversational artificial intelligence is a technology that makes software capable of understanding and responding to voice-based or text-based human conversations. Conversational AI goes beyond the traditional human chat with software which has been limited to preprogrammed inputs where users enter or speak predetermined commands. Conversational AI can recognize all types of speech and text input, mimic human interactions, and understand and respond to queries in various languages.

Read more about Conversational AI here

[H2] Browse all cloud computing concepts
Browse all cloud computing concepts content here:

Loading

Loading

Loading

Loading

Loading

[H2] Learn more about cloud comparisons

The Cloud Comparisons page features content that helps readers understand common use cases for when to use one cloud solution or another. Compare and contrast cloud solutions and learn the nuances of different use cases that work best for your situation. Learn about cloud comparisons

[H2] Get started

Companies of all sizes across all industries are transforming their businesses every day using AWS. Contact our experts and start your own AWS Cloud journey today. Contact Sales