If you’ve been following the advancements in the AI (Artificial Intelligence) space, it will be no surprise to you that tons of models and apps are released every single day.
AI solutions come in various forms and solve a wide range of use cases. Though the evolution is still at its nascent stage, I see a few trends emerging.
In this post, I talk about three types or categories of AI solutions – AI tools, AI assistants, AI agents – why they exist and what problems they solve.
Here’s a comparison of the various types of AI solutions, their applicability, and ease of implementation.
Let’s start with the first one.
#1 AI Tools
This is something most of us are familiar with.
AI tools are software applications that using artificial intelligence and models, to perform specific tasks and solve problems.
ChatGPT, Copilot, and Perplexity are good examples of this.
What are their characteristics?
- They offer a standard interface to interact (web app, mobile app, etc.)
- They are useful for general-purpose use cases (e.g., summarizing an article, tightening a paragraph, understanding a specific topic, etc.)
- With prompt engineering, they can understand your context and generate better content
They are good as a general-purpose vehicle, covering majority of an average person’s needs.
#2 AI Assistants
How do they differ from an AI tool? Not by a huge margin.
AI Assistants are a specific adaptation of AI tools that make it easier and simpler to use an application or a website
Have you seen the AI assistant in Notion, that helps you write? It is an AI assistant.
- AI assistants are very context-specific and assist you with specific activities
- They make use of one or more AI tools behind the scenes
- With continuous usage, they can adapt and assist you better
#3 AI Agents
AI Agents take the game to the next level.
AI Agents are designed to perceive the environment, process signals, and take actions to achieve specific goals.
These agents can be software-based or physical entities and are commonly built using artificial intelligence techniques.
AI agents typically have 3 distinct components:
- Sensors & Perception Layer – process signals and find out what’s happening in the environment
- Skills Layer – to examine different options based on inputs
- Decision Layer – to take actions and send it to the target environment
This space is still nascent. Auto-GPT, BabyAGI are some frameworks gaining traction.
There is consensus that most growth will be here – to automate workflows and perform actions that otherwise require complex decision-making.
To conclude…
AI Paradigm can be seen as a combination of general-purpose AI tools, specialized AI apps, and sophisticated AI agents. Each differs in its purpose, ease of use, and applicability. AI agents that mimic humans is where I anticipate huge growth in the future!
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