Generative AI – Telegram
Generative AI
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Welcome to Generative AI
👨‍💻 Join us to understand and use the tech
👩‍💻 Learn how to use Open AI & Chatgpt
🤖 The REAL No.1 AI Community

Admin: @coderfun

Buy ads: https://telega.io/c/generativeai_gpt
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Applications of Generative AI

Content Creation – AI writes articles, designs graphics, and generates videos.
Software Development – AI assists in coding, debugging, and software optimization.
Healthcare – AI helps in medical imaging and drug discovery.
Marketing & Business – AI powers chatbots, personalized ads, and customer insights.
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Generative AI vs. AGI

Generative AI is task-specific, working within predefined training limits.
AGI (Artificial General Intelligence) can adapt and think like a human, which doesn’t exist yet.

Generative AI is powerful but lacks true understanding—it predicts, not thinks.

Limitations of Generative AI

Bias & Ethical Issues – AI can inherit biases from its training data.
Computational Costs – Running AI models requires high computing power.
Lack of True Creativity – AI mimics existing styles but doesn’t create original ideas.

Future of Generative AI

🔹 More efficient models with lower costs
🔹 Stronger ethical guidelines to prevent misuse
🔹 AI as a tool to enhance human creativity, not replace it
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Risks & Challenges of Generative AI

1️⃣ Misinformation & Deepfakes
AI-generated fake news, images, and videos can spread misinformation, making it harder to distinguish truth from fiction.

2️⃣ Bias in AI Models
🔍 AI learns from existing data, which may include biases. This can lead to unfair or discriminatory outputs in hiring, lending, and law enforcement.

3️⃣ Job Displacement
👨‍💻 While AI creates new roles, automation may replace repetitive jobs, requiring workers to upskill.

4️⃣ Ethical & Legal Issues
⚖️ AI-generated content raises copyright concerns, data privacy risks, and ethical dilemmas in areas like deepfake misuse.

5️⃣ High Computational Costs
💰 Training and running AI models require massive computing power, making AI expensive for smaller businesses.

6️⃣ Lack of True Understanding
🤖 AI doesn’t "think" or "understand" like humans; it generates content based on patterns, which can sometimes be inaccurate or misleading.

7️⃣ Security Threats
🔐 AI can be exploited for cyberattacks, including generating phishing emails and automating malware creation.

AI is powerful but needs responsible use to prevent harm. Awareness is the first step! 🚀
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Applied Generative AI for Beginners.pdf
7.9 MB
Applied Generative AI for Beginners
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Here are two amazing SQL Projects for data analytics 👇👇

Calculating Free-to-Paid Conversion Rate with SQL Project

Career Track Analysis with SQL and Tableau Project

Like this post if you need more data analytics projects in the channel 😄

Hope it helps :)
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How to Use Generative AI Effectively

1️⃣ Be Clear with Prompts
✍️ The more specific your input, the better the output. Use detailed instructions for accurate results.

2️⃣ Verify AI-Generated Content
🔍 AI can make mistakes. Always fact-check information before using it.

3️⃣ Use AI as an Assistant, Not a Replacement
🤝 AI enhances productivity but still needs human creativity and judgment.

4️⃣ Avoid Bias and Ethical Risks
AI reflects the data it learns from. Be mindful of biases in its responses.

5️⃣ Experiment with Different Models
🔄 Try multiple AI tools (GPT, DALL·E, Midjourney) to see which works best for your needs.

6️⃣ Stay Updated with AI Trends
📢 AI evolves fast. Keep learning about new updates and ethical guidelines.

7️⃣ Use AI to Automate Repetitive Tasks
AI can handle tasks like summarization, translation, and data analysis, freeing up your time.

AI is a tool—use it wisely to boost efficiency and creativity. 🚀
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How Generative AI is Changing the World

1️⃣ Revolutionizing Content Creation
📝 AI drafts blogs, summarizes reports, and refines content
🎨 AI generates images, logos, and even full animations
🎬 AI enhances video editing and automates noscriptwriting

2️⃣ Boosting Productivity in Tech
💻 AI suggests code, fixes bugs, and improves efficiency
📊 AI extracts insights from large datasets in seconds
🔐 AI detects fraud and strengthens online security

3️⃣ Transforming Healthcare
🩺 AI improves diagnostics from X-rays and MRIs
💊 AI speeds up the process of finding new medicines
📈 AI analyzes patient data to prevent diseases

4️⃣ Reshaping Business & Marketing
🤖 AI chatbots automate customer service and support
📢 AI analyzes behavior to create targeted marketing
💰 AI predicts stock trends and detects fraud

5️⃣ The Ethical & Practical Challenges
Fake content & deepfakes can mislead people
AI reflects biases from its training data
Automation may replace certain jobs

6️⃣ The Future of AI
🔹 AI will become more efficient and less costly
🔹 Regulations will improve ethical AI use
🔹 AI will enhance human creativity, not replace it

Generative AI is here to stay. Are we ready to use it responsibly? 🚀
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PERCENTAGE GROWTH IN REVENUE FROM GENERATIVE AI ENGINES (Jan - Aug 2024)
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LLM Project Ideas 👆
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Top Platforms for Building Data Science Portfolio

Build an irresistible portfolio that hooks recruiters with these free platforms.

Landing a job as a data scientist begins with building your portfolio with a comprehensive list of all your projects. To help you get started with building your portfolio, here is the list of top data science platforms. Remember the stronger your portfolio, the better chances you have of landing your dream job.

1. GitHub
2. Kaggle
3. LinkedIn
4. Medium
5. MachineHack
6. DagsHub
7. HuggingFace

7 Websites to Learn Data Science for FREE🧑‍💻

w3school
datasimplifier
hackerrank
kaggle
geeksforgeeks
leetcode
freecodecamp
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ML Engineer vs Data Engineer
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Step-by-Step Approach to Learn Generative AI

Learn AI & Deep Learning Basics → Neural Networks, Supervised vs. Unsupervised Learning

Master Python & Essential Libraries → NumPy, Pandas, TensorFlow, PyTorch

Understand Neural Networks → Activation Functions, Backpropagation, Optimizers

Learn GANs (Generative Adversarial Networks) → Generator vs. Discriminator, Training Stability

Explore Variational Autoencoders (VAEs) → Latent Space, KL Divergence

NLP & Large Language Models (LLMs) → Transformers, BERT, GPT, Tokenization

Text-to-Image & Multimodal Models → Stable Diffusion, DALL·E, CLIP

Fine-tuning & Deployment → Custom Model Training, APIs, Model Optimization

Free Generative AI Resources: https://whatsapp.com/channel/0029VazaRBY2UPBNj1aCrN0U
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Google, Harvard, and even OpenAI are offering FREE Generative AI courses (no payment required) 🎓

Here are 8 FREE courses to master AI in 2024:

1. Google AI Courses
5 courses covering generative AI from the ground up
https://www.cloudskillsboost.google/paths/118

2. Microsoft AI Course
Basics of AI, neural networks, and deep learning
https://microsoft.github.io/AI-For-Beginners/

3. Introduction to AI with Python (Harvard)
7-week course exploring AI concepts and algorithms
https://www.edx.org/learn/artificial-intelligence/harvard-university-cs50-s-introduction-to-artificial-intelligence-with-python

4. ChatGPT Prompt Engineering for Devs (OpenAI & DeepLearning)
Best practices and hands-on prompting experience
https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/

5. LLMOps (Google Cloud & DeepLearning)
Learn the LLMOps pipeline and deploy custom LLMs
https://www.deeplearning.ai/short-courses/llmops/
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Startup ideas with Generative AI
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1. Personalized wellness AI: Develop an AI platform that analyzes users' lifestyle habits, health data, and preferences to provide personalized recommendations for improving overall wellness.

2. AI-powered virtual assistant for small businesses: Create a virtual assistant that uses AI to help small business owners manage tasks such as scheduling appointments, sending reminders, and handling customer inquiries.

3. AI-powered content creation tool: Develop an AI tool that can generate high-quality written content, such as blog posts or social media updates, based on a user's input and preferences.

4. AI-driven personalized shopping experience: Build an AI platform that analyzes users' browsing history, purchase behavior, and preferences to recommend personalized product suggestions and discounts.

5. AI-powered mental health support platform: Create an AI-driven platform that provides personalized mental health support, including therapy sessions, coping strategies, and resources for managing stress and anxiety.

6. AI-driven sustainability platform: Develop an AI platform that helps businesses and individuals track their carbon footprint, set sustainability goals, and receive personalized recommendations for reducing environmental impact.

7. AI-powered language learning platform: Build an AI platform that uses natural language processing and machine learning to personalize language learning experiences for users, helping them improve their proficiency in a new language.

8. AI-driven financial planning tool: Create an AI tool that analyzes users' financial data, spending habits, and goals to provide personalized recommendations for budgeting, saving, and investing.

9. AI-powered talent recruitment platform: Develop an AI platform that uses data analytics and machine learning to match job seekers with employers based on their skills, experience, and preferences.

10. AI-driven personalized travel planning platform: Build an AI platform that analyzes users' travel preferences, budget, and interests to recommend personalized travel itineraries, accommodations, and activities.
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AI & ML Project Ideas
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