969.9K
SAHow to quickly understand code using ai #code #ai #howto
@sanjaycodingchamp
#Genai Code Basics
Mira videos de Reels sobre Genai Code Basics de personas de todo el mundo.
Ver anónimamente sin iniciar sesión.
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Reels en Tendencia
(12)
65.5K
AIMaster these basics and every GenAI concept becomes easier.
Phase 2 coming next make sure you save this post.
#GenerativeAI
#AIEngineer
#Python
#MachineLearning
#TechLearning
@aiwithtani
1.9M
SOCode Generator AI ⚡| #ai #code #useful #website #top #generator #robot #lifehacks #hack
@sortedcoding
43.5K
THBest Gen AI course. Link in comments. #genai #chatgpt #llm #machinelearning
@thenadcoder
309.2K
ARMaster these 3 GenAI Topics 👇
1️⃣Prompting: The MOST important skill you can have as an AI engineer. This is all about clearly telling an LLM what your output needs to be a long with the context of your input
2️⃣Vector Database: The backbone of any AI system now. This allows you to consume large amounts of data and store it in a format easily accessible by an LLM
3️⃣RAG: ‘Retrieval Augmented Generation’, the easiest way to provide business context (internal documents / knowledge bases / data) to an LLM WITHOUT having to go through the pain of fine tuning
@arkie.develops
40.5K
CORegister for a Free Live Webinar. Link in bio 🔗
Have you got these skills? Watch till the end.
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[GenAI, What is GenAI, How to do Machine Learning?, AI, How to Updkill in GenAI, Coding Ninjas]
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#codingninjas #genai #ai #coding #fyp
@coding.ninjas
578.0K
GEFind all these topics at my GenAI Roadmap GitHub Repo —> genieincodebottle/generative-ai
pdf location - https://github.com/genieincodebottle/generative-ai/blob/main/docs/genai_tech_stacks.pdf
Prompt Engineering: Perfecting questions to get smarter AI answers.
RAG (Retrieval-Augmented Generation): Blending real-time info with AI for accurate results.
Agents: Specialized mini-AIs that complete tasks or answer on specific topics.
LLMs (Large Language Models): Core of GenAI based on Transformer architecture that understand and generate text.
Multimodal AI: AI that handles text, images, and more together for richer outputs.
Fine-Tuning: Adjusting LLMs for specific jobs, like customer support or medical advice.
LLM Evaluation: Measuring if AI responses are accurate and reliable.
LLMOps: Managing and improving GenAI in production, think maintenance for models.
AWS, Azure, Vertex AI: Leading cloud platforms powering AI capabilities.
Transformers: The core architecture behind modern LLMs, making complex tasks easier.
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#generativeai #genai #technology #softwaredeveloper #softwareengineer #python #dataanalyst #datascientist #fullstackdeveloper #fullstackdevelopment #machinelearning #softwaredevelopment #artificialintelligence
@genieincodebottle
152.4K
AVDay 1 of my 50 Days of GenAI challenge.
The most important thing to understand about LLMs is this:
An LLM is just text in, text out.
In other words, at every step, the model is just asking itself:
“Given all the previous tokens, what’s the most likely next token?”
There’s no separate reasoning engine inside.
It’s simply continuing a pattern it learned from tons of text.
All those “smart” answers? They’re just well-predicted next words.
Every chatbot you’ve used, ChatGPT, Gemini, Claude - is this same idea, just wrapped inside a user interface.
Once this mental model is clear, concepts like prompts, tokens, context windows, tools, RAG, and agents start to make a lot more sense.
Code shown in the video is available on GitHub (link in bio).
This series is focused on understanding GenAI through real code, one concept at a time.
#GenAI #LLM #AIForDevelopers #LearnByBuilding #50DaysOfGenAI
@average.yash
177.6K
GEGenAI for beginners !
#coding #programming #developer #genai #software #tech #java #python
@geekydev.in
8.3K
COGenAI vs Agentic AI — what’s the difference? 🤖⚡
GenAI generates.
Agentic AI gets things done.
One gives you answers.
The other takes action on your behalf.
Generative AI is the foundational technology used to build Agentic AI systems.
#GenAI #AgenticAI #AIExplained #Codebasics #AIRevolution
@codebasicshub
2.3M
TRFor your basic understanding 👇
A generative AI skill means your ability to effectively use, understand, or build tools that can generate content—like text, images, code, music, video, etc.—using AI models such as ChatGPT, DALL·E, Gemini, Claude, or Midjourney.
Generative AI falls into 3 main categories:
( 1st ) Prompting and usage skills ( Non - Technical)
These are beginner-friendly skills that help you use generative AI tools smartly:
.Writing better prompts to get what you want from ChatGPT
. Generating blogs, emails, scripts, or social media posts
Using tools like:
• ChatGPT (text)
• DALL·E or Midjourney (images)
• ElevenLabs (AI voice)
• Notion AI, Canva AI, etc.
( 2nd ) Creative and Applied Skills
These include:
• Designing AI-powered lesson plans, marketing campaigns, or presentations
• Building AI-powered chatbots (with no-code tools like Zapier, Make, Voiceflow)
• Using AI for research, brainstorming, video scripts, storytelling
( 3rd ) Technical Skills ( Advanced )
These require coding and deeper understanding of AI:
• Fine-tuning LLMs (like GPT-4 or LLaMA)
• Using OpenAI API, LangChain, Pinecone, or vector databases
• Developing AI-powered apps and automations.
@trickpilot
168.0K
DAComment “AI” for the full tool guide + links + workflow 🚀
Most students use ChatGPT for everything.
Assignments? ChatGPT.
PDFs? ChatGPT.
Debugging? ChatGPT.
Emails? ChatGPT.
And that’s exactly where inefficiency starts.
ChatGPT is powerful — but it’s a generalist.
If you want better output, faster clarity, and smarter workflows, you need specialized AI tools for specific tasks.
That’s why I created a complete playbook covering:
✍️ Writing assignments → Why Claude handles long-form better
📚 PDF summaries → Why Humata understands full documents
📖 Technical documentation → Why Swimm reads context
💻 Code debugging → Why Phind gives sharper developer answers
📝 English clarity → Why GrammarlyGO preserves your tone
📩 Email writing → Why Superhuman works inside your inbox
This is not about replacing ChatGPT.
It’s about knowing:
When ChatGPT is enough
When to switch
How to use each tool properly
The difference between average and efficient in 2026 won’t be “using AI.”
It’ll be:
Knowing which AI tool to use, when.
If you’re serious about:
• College productivity
• Smarter learning
• Better coding
• Clear communication
• Internship readiness
Then this stack matters.
Comment AI and I’ll send you:
✔ Full tool links
✔ Why each tool works
✔ When to switch from ChatGPT
✔ How to use them properly
Save this post.
You’ll come back to it.
#AItools #StudentProductivity #TechStack
@dasandcode
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