The World of AI : Explanation of LLMs, AI Workflows, and AI Agents.
Artificial Intelligence (AI) is everywhere today – from helping people write emails, images creation, customer interactions, or managing businesses. But the real questions is why?
Let’s break it down into three key ideas:
- LLMs (Large Language Models)
- AI Workflows
- AI Agents
1. Large Language Models (LLMs): The Brain of AI
LLMs are computer programs that understand and write human language.You can ask them questions or give instructions, and they reply in a way that sounds like a real person.
What’s the process?
- To train LLMs, texts from books, articles, and websites are utilized on a large scale.
- Their heads are not understanding like humans, but recognizing elements of speech and writing that patterns enable will do wonders for AI’s comprehension.
- AI understands these patterns enabling them to intelligently guess what words ought to be next in the sentence and know the best way to respond to your queries.
What do they do?
- Comprehension: From your text, comprehension is reading widely in demand in the modern working world.
- Creation: Emails, stories, summaries, and code can be automated, written, generated, and created.
- Translation: Many languages or LLMs will swish back and forth between enabling you to code freely without being held back by language barriers.
- Answer questions: You can ask historical questions, scientific questions, or even have it explain a cooking procedure for you.
For Example:
ChatGPT, Gemini, and Claude – these are all LLMs that respond when you type something in.
2. AI Workflows: The Recipe That Gets Things Done
An AI workflow is a list of instructions organized in a specific way for the AI to follow. It is a systematic approach broken down into mini steps to complete a task and achieve a goal.
How does it work?
Let’s say you want to read product reviews and their good or bad rating:
- A new review arrives.
- The AI scans through it.
- The AI accesses whether it’s good or bad.
- It is kept in file or database.
This is a workflow— a specific plan defining AI tasks and the sequential order to execute them.
Why do we use workflows?
- Automation: Tasks are done without human intervention ever since they were set up.
- Consistency: Every time the task is completed, the same outcome is reached.
- Efforts and Time: Achieving the task takes much less time and the chances of making errors are virtually eliminated.
- Link different tools: An LLM can be used with other tools such as Excel, Gmail, or Docs to enhance its functionalities.
Real-life example:
A business might set up a workflow like this:
- Extract data from the datasource/external website.
- LLM generates document/extract data.
- Send out email containing the summary.
- All these functions will be done without manual guidance.
3. AI Agents: The Smart Workers
An AI agent is a type of a smart assistant which is goal oriented and knows how to achieve the goal. Instead of following a sequential list, it makes choices, employs tools, and alters its strategies when necessary.
How does it work?
An AI agent can:
- Plan – think of how its goal can be achieved step by step.
- Act – employ a LLM, a search engine, or other software applications.
- Adjust – try employing a different approach when there are hurdles blocking the way.
This is called the ReAct framework – Reason and Act.
Real-world example:
Imagine a case where an AI agent is instructed to update an Instagram account with an company picnic post.
Here’s how it might work:
Goal – create an instagram update and post it.
- Step 1 (Get info): Use webs to fetch photos and details of the event.
- Step 2 (Use LLM): Provide the gathered data to LLM, request a catchy few sentences and relevant hashtags.
- Step 3 (Organize): Store the caption and photo in Google docs.
- Step 4 (Schedule): Monitor user activities and determine the best time to post.
- Step 5 (Post): Sign into the Instagram account and execute the post.
- Step 6 (Monitor): It tracks the likes and comments and reports back.
In the case of one step failing (for example, no photographs being taken), it can return to capture other pictures and continue from where it left off.