AI Tools And How To Use Them
- subymmathew
- Sep 2
- 4 min read
Artificial Intelligence (AI) has quickly evolved from a buzzword into a collection of powerful tools that are transforming the way we work, create, and communicate. But here’s the truth: what we call “AI” isn’t some magical thinking machine. At its core, it’s a system of neural networks—mathematical models trained to recognize patterns in massive amounts of data and generate useful results.
Neural networks are the engines behind today’s AI boom. Think of them as layers of filters: each layer processes raw data, refines it, and passes it along until the final output emerges. But they don’t start out smart. Developers feed them text, images, or videos, and the networks learn through trial and error—making billions of adjustments until they become accurate at predicting outcomes or generating results. This is the foundation of every AI tool we use today, from chatbots to image creators.
In this blog, we’ll break down the different types of AI you can use right now—from large language models (LLMs) and image generators to voice assistants and productivity platforms—while also exploring the best ways to make them work for you.
The AI Tools You Can Use Right Now
As consumers, we already have access to powerful AI tools that can make our lives easier and more creative. Some of the most popular include:
Large Language Models (LLMs) – e.g., ChatGPT, used for writing, coding, and problem-solving.
Image Generators – create art, designs, or realistic visuals from text prompts.
Audio Generators – produce music, sound effects, or even lifelike voices.
Video Generators and Editors – speed up content creation with automated editing.
Voice Assistants – think Siri, Alexa, and more advanced AI-powered companions.
Productivity AIs – help manage tasks, summarize information, and boost efficiency.
While they might seem wildly different, all these tools rely on the same principle: analyzing data and predicting the most likely next step.
Large Language Models (LLMs): ChatGPT, Gemini, Claude & More
Large Language Models (LLMs) like ChatGPT, Gemini, and Claude dominate today’s AI conversation. These systems are powered by transformers, which break down your input, weigh the relationships between words, and generate responses based on probabilities.
The secret to their success lies in two things:
Massive data exposure – they’ve read enormous amounts of text.
Attention mechanisms – they focus on the most relevant parts of your query to generate coherent answers.
From writing essays and analyzing data to coding, these models are versatile but still limited: they don’t “understand” in the human sense—everything is math, probabilities, and pattern recognition.
How to Prompt LLMs Effectively
Prompting is an art. Bigger models like ChatGPT-4 or Gemini are more forgiving, while smaller ones require stricter input. The golden rules of prompting include:
Be descriptive: Give context, tone, audience, and desired format.
Use roleplay: Ask the model to act like an expert for more refined responses.
Set limits: Clearly state what not to include.
Mastering prompts ensures better, more relevant outputs.
Image Generators
The second big category is image generators. Instead of working with words, they’re trained on millions of labeled images. Over time, they learn how words map to visual patterns.
When you type “a black cat with glowing green eyes,” the model doesn’t pull a picture from the web. Instead, it starts with static noise and refines it through a process called diffusion until an image emerges.
That’s why these are often called diffusion models.
Picking the Right Image Generator
DALL·E – Beginner-friendly, simple, but full potential often requires a subscription.
Gemini – Can generate images but isn’t the most customizable.
Adobe Firefly / Express – User-friendly, with controls for customization, though results can be hit-or-miss.
Midjourney – The gold standard for creativity, but requires Discord and structured prompts.
Runway – Decent for still images, excellent for video generation.
Voice Assistants: Evolving Beyond Commands
Current voice assistants like Siri or Alexa aren’t as “smart” as they appear. Most of their magic lies in three simple stages:
Speech-to-text
Intent recognition
Text-to-speech
However, this is changing. Newer systems are beginning to integrate neural networks for contextual understanding, which could allow them to perform deeper, more personalized actions directly inside apps.
Unlike LLMs, prompting here is almost nonexistent—you just talk normally, and the assistant interprets your request.
Productivity AI: Smarter Workflows
One of the most practical applications of AI is in productivity tools. These platforms are designed to help you work smarter, not harder, and they’re rapidly being integrated into everyday apps.
Examples include:
Email clients (like Superhuman): Speed through inboxes with AI-powered summaries, rewrites, and sorting.
Task & project managers (like Taskade): Automate workflows, assign tasks, and track progress.
CRM platforms (like HubSpot, Pipedrive): Optimize customer management with predictive insights.
Automation tools (Zapier, Integromat): Connect different apps to reduce repetitive tasks.
AI isn’t here to replace us — it’s here to enhance workflows. In fact, many content creators and businesses are already using it to:
Brainstorm new ideas.
Write scripts and blog posts.
Create thumbnails and titles.
Edit videos.
Automate SEO tasks.
Final Thoughts
· AI isn’t here to replace creativity or human intelligence—it’s here to amplify it. Whether you’re using ChatGPT to brainstorm, Midjourney to visualize, or Taskade to manage projects, the key is to stay consistent and intentional. AI isn’t magic, and it isn’t a thinking machine. It’s a tool — an incredibly powerful one — that can help you work smarter, faster, and more creatively.
