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What is an AI agent in simple words?

Examples of agentic systems

What is the main task of an AI agent?

Understanding the architecture of an AI agent

Core Principles of AI Agents

How do AI agents work?

The Four Fundamental Rules of AI Agents

What’s the difference between horizontal, vertical, narrow agents?

Horizontal AI agents

Vertical AI agents

Narrow AI agents

What types of agentic systems are there? (For The Technical Reader)

Workflow or GUI agent: How to choose

Workflow agents

GUI agents

Other comparable AI paradigms

How are AI agents trained?

Benefits, risks, and challenges

Conclusion: Are AI agents just hype?

Overview: Agentic AI vs. AI agents

What’s the difference between Agentic AI and AI agents?

Agentic AI in e-learning

AI agents vs. other paradigms & tools: The comprehensive definition list

What is the difference between an AI Agent and a Chatbot?

What is the difference between an AI Agent and a Virtual Assistant?

What is the difference between an AI Agent and an AI Model/LLM?

What is the difference between an AI Agent and Generative AI?

What is the difference between an AI Agent and ChatGPT/GPT?

What is the difference between an AI Agent and Copilots?

What is the difference between an AI Agent and Workflow Automation?

What is the difference between an AI Agent and a Bot?

What is the difference between an AI Agent and Robotic Process Automation (RPA)?

What is the difference between Agentic AI and Multi-Agent Systems?

What is the difference between Agentic AI and Compound AI?

What is the difference between an AI Agent and Causal AI?

What is the difference between an AI Agent and RAG?

Other agentic systems: Workflow & GUI agents

Workflow vs. GUI agent

Workflow agents

GUI agents

Future Trends in AI: Collaboration Between Humans and Machines

How has the definition of agentic AI changed?

What is the origin of agentic AI: Early foundations (1950s-1980s)

The first problem solvers

The first chatbot: ELIZA

Two competing schools of thought

How did advancements in technology influence the progression of agentic AI?

The expert systems era (1980s-1990s)

The machine learning revolution (1990s-2000s)

Deep Learning Breakthrough (2010s)

The Four Stages of AI Development

Stage 1: Reactive machines

Stage 2: Limited memory

Stage 3: Theory of mind

Stage 4: Self-aware AI

An alternative for the four stages of AI

What role did early AI agents play in the evolution of autonomous systems?

From static to dynamic decision-making

Technology integration

Why this matters for EdTech

Looking Forward: The future of agentic AI

The problem learners face

The problem for businesses

The old way of solving broken search

AI agents for better search

What implementation looks like

The outcomes

Here is a breakdown of OpenAI's announcements:

Speed & intelligence combined

Improved vision 

Improved non-English language capabilities 

Increased context window

Multi-modal level up (coming soon)

What does all of this mean for Mindset customers?

Get answers quicker than before

Speak to agents

More accurate search through conversation

More accurate Search, across all your data sources

Search for images and ask questions about them

Next Steps

How could such AI-driven interactivity translate to a business context?

How AI can help you get your content seen

What if your audience saw more of what they liked?

But how do you know if your content is working for you?

How can AI-powered Knowledge Assistants benefit HR departments?

How are AI-powered Knowledge Assistants being used in HR today?

How will AI-powered knowledge assistants change HR in the future?

Understanding the challenges of traditional onboarding

Information overload and lengthy orientation sessions

Administrative burden and paperwork

One-size-fits-all approach

Longer ramp-up times and delayed productivity

Time commitment and high dependability on people within the business

Self-guided employee onboarding with AI

Personalised learning and knowledge assistants

Interactive and engaging content delivery

Automated onboarding workflows and processes

Continuous learning and performance tracking

Benefits of AI-powered employee onboarding

Faster integration and productivity

Personalised support and guidance

Enhanced knowledge retention and skill development

Reduced training costs and time‍

Mindset AI’s Knowledge Assistant

Personalised and relevant guidance‍

Enhanced learning experience

24/7 support and accessibility

Scalability and consistency‍

Accelerated ramp times

The costs & challenges of unmanaged knowledge 

How to manage unstructured knowledge?

Creating a knowledge repository 

Using tagging and categorisation 

Implementing a knowledge-sharing culture 

Using technology 

Key benefits of AI-driven knowledge management 

The evolution of knowledge management with AI