Which of these is an example of Narrow AI?
Anonymous Quiz
36%
A) A robot that cooks and teaches
36%
B) ChatGPT
9%
C) AI with emotions
20%
D) AI that thinks like a human
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🚀 The 10 Levels of AI Agents — Where We Stand Today
AI isn’t a single goal — it’s an evolution. From simple rules to intelligent reasoning, here’s the journey 👇
🔹 Levels 1–3: The Basics
• Reactive → Fixed rules, no learning
• Context-Aware → Adapts from past data
• Goal-Oriented → Acts to achieve objectives (Alexa, Siri)
🔹 Levels 4–6: The Present
• Adaptive → Learns from feedback
• Autonomous → Makes independent decisions
• Collaborative → Works with humans/AI (e.g., supply chain systems)
🔹 Levels 7–10: The Future
• Proactive → Anticipates needs
• Social → Understands emotions
• Ethical → Fair & transparent
• Superintelligent → Beyond human capability
👉 Today: Most industries operate at Levels 4–6.
👉 Tomorrow: The focus shifts to ethical & proactive AI — systems that act intelligently and responsibly.
💡 The future of AI isn’t just about power — it’s about purpose and trust.
AI isn’t a single goal — it’s an evolution. From simple rules to intelligent reasoning, here’s the journey 👇
🔹 Levels 1–3: The Basics
• Reactive → Fixed rules, no learning
• Context-Aware → Adapts from past data
• Goal-Oriented → Acts to achieve objectives (Alexa, Siri)
🔹 Levels 4–6: The Present
• Adaptive → Learns from feedback
• Autonomous → Makes independent decisions
• Collaborative → Works with humans/AI (e.g., supply chain systems)
🔹 Levels 7–10: The Future
• Proactive → Anticipates needs
• Social → Understands emotions
• Ethical → Fair & transparent
• Superintelligent → Beyond human capability
👉 Today: Most industries operate at Levels 4–6.
👉 Tomorrow: The focus shifts to ethical & proactive AI — systems that act intelligently and responsibly.
💡 The future of AI isn’t just about power — it’s about purpose and trust.
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The program for the 10th AI Journey 2025 international conference has been unveiled: scientists, visionaries, and global AI practitioners will come together on one stage. Here, you will hear the voices of those who don't just believe in the future—they are creating it!
Speakers include visionaries Kai-Fu Lee and Chen Qufan, as well as dozens of global AI gurus from around the world!
On the first day of the conference, November 19, we will talk about how AI is already being used in various areas of life, helping to unlock human potential for the future and changing creative industries, and what impact it has on humans and on a sustainable future.
On November 20, we will focus on the role of AI in business and economic development and present technologies that will help businesses and developers be more effective by unlocking human potential.
On November 21, we will talk about how engineers and scientists are making scientific and technological breakthroughs and creating the future today!
Ride the wave with AI into the future!
Tune in to the AI Journey webcast on November 19-21.
Speakers include visionaries Kai-Fu Lee and Chen Qufan, as well as dozens of global AI gurus from around the world!
On the first day of the conference, November 19, we will talk about how AI is already being used in various areas of life, helping to unlock human potential for the future and changing creative industries, and what impact it has on humans and on a sustainable future.
On November 20, we will focus on the role of AI in business and economic development and present technologies that will help businesses and developers be more effective by unlocking human potential.
On November 21, we will talk about how engineers and scientists are making scientific and technological breakthroughs and creating the future today!
Ride the wave with AI into the future!
Tune in to the AI Journey webcast on November 19-21.
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✅ How to Build Your First AI Project 🤖
1️⃣ Choose Your Project Idea
Start small and pick a practical project:
⦁ Spam Email Classifier
⦁ Sentiment Analysis on Tweets
⦁ Handwritten Digit Recognizer (MNIST)
⦁ Chatbot for FAQs
2️⃣ Collect & Prepare Data
⦁ Find datasets online (Kaggle, UCI ML Repo) or create your own
⦁ Clean the data: remove missing values, duplicates
⦁ Normalize or scale features if needed
⦁ Split data into training & testing sets (typically 80:20)
3️⃣ Select Algorithms & Tools
⦁ For beginner projects, use libraries like scikit-learn for ML or TensorFlow/PyTorch for deep learning
⦁ Choose algorithms based on your problem type:
⦁ Classification → Logistic Regression, Decision Trees, Neural Networks
⦁ Regression → Linear Regression, Random Forests
⦁ NLP → Naive Bayes, Transformers
4️⃣ Train Your Model
⦁ Feed the training data to your model
⦁ Adjust hyperparameters (like learning rate, epochs) to improve performance
⦁ Use validation data to check if your model is learning well (not overfitting)
5️⃣ Evaluate Model Performance
⦁ Use metrics such as Accuracy, Precision, Recall, F1 Score for classification
⦁ Use RMSE or MAE for regression
⦁ Visualize results with confusion matrix or plots
6️⃣ Improve & Tune
⦁ Try different algorithms or architectures
⦁ Use feature engineering: add or remove features to improve results
⦁ Apply techniques like cross-validation to ensure robustness
7️⃣ Deploy Your Model
⦁ Create an API using Flask or FastAPI to serve your model
⦁ Build a simple UI (web app or chatbot interface)
⦁ Deploy on platforms like Heroku, AWS, or Streamlit Sharing
8️⃣ Document & Share
⦁ Write clear README with project overview
⦁ Share code on GitHub
⦁ Include instructions on how to run & use the model
Example Project: Spam Email Classifier
⦁ Dataset: Use the “SpamAssassin” dataset
⦁ Tool: Python + scikit-learn
⦁ Steps:
1. Load & clean email texts
2. Convert text to numerical features using TF-IDF
3. Train a Naive Bayes classifier
4. Evaluate accuracy on test set (~95%)
5. Deploy with Flask API
🎯 Pro Tip: Start simple, focus on understanding the flow, and gradually tackle more complex AI projects.
💬 Tap ❤️ for more!
1️⃣ Choose Your Project Idea
Start small and pick a practical project:
⦁ Spam Email Classifier
⦁ Sentiment Analysis on Tweets
⦁ Handwritten Digit Recognizer (MNIST)
⦁ Chatbot for FAQs
2️⃣ Collect & Prepare Data
⦁ Find datasets online (Kaggle, UCI ML Repo) or create your own
⦁ Clean the data: remove missing values, duplicates
⦁ Normalize or scale features if needed
⦁ Split data into training & testing sets (typically 80:20)
3️⃣ Select Algorithms & Tools
⦁ For beginner projects, use libraries like scikit-learn for ML or TensorFlow/PyTorch for deep learning
⦁ Choose algorithms based on your problem type:
⦁ Classification → Logistic Regression, Decision Trees, Neural Networks
⦁ Regression → Linear Regression, Random Forests
⦁ NLP → Naive Bayes, Transformers
4️⃣ Train Your Model
⦁ Feed the training data to your model
⦁ Adjust hyperparameters (like learning rate, epochs) to improve performance
⦁ Use validation data to check if your model is learning well (not overfitting)
5️⃣ Evaluate Model Performance
⦁ Use metrics such as Accuracy, Precision, Recall, F1 Score for classification
⦁ Use RMSE or MAE for regression
⦁ Visualize results with confusion matrix or plots
6️⃣ Improve & Tune
⦁ Try different algorithms or architectures
⦁ Use feature engineering: add or remove features to improve results
⦁ Apply techniques like cross-validation to ensure robustness
7️⃣ Deploy Your Model
⦁ Create an API using Flask or FastAPI to serve your model
⦁ Build a simple UI (web app or chatbot interface)
⦁ Deploy on platforms like Heroku, AWS, or Streamlit Sharing
8️⃣ Document & Share
⦁ Write clear README with project overview
⦁ Share code on GitHub
⦁ Include instructions on how to run & use the model
Example Project: Spam Email Classifier
⦁ Dataset: Use the “SpamAssassin” dataset
⦁ Tool: Python + scikit-learn
⦁ Steps:
1. Load & clean email texts
2. Convert text to numerical features using TF-IDF
3. Train a Naive Bayes classifier
4. Evaluate accuracy on test set (~95%)
5. Deploy with Flask API
🎯 Pro Tip: Start simple, focus on understanding the flow, and gradually tackle more complex AI projects.
💬 Tap ❤️ for more!
❤12🔥2
Tune in to the 10th AI Journey 2025 international conference: scientists, visionaries, and global AI practitioners will come together on one stage. Here, you will hear the voices of those who don't just believe in the future—they are creating it!
Speakers include visionaries Kai-Fu Lee and Chen Qufan, as well as dozens of global AI gurus! Do you agree with their predictions about AI?
On November 20, we will focus on the role of AI in business and economic development and present technologies that will help businesses and developers be more effective by unlocking human potential.
On November 21, we will talk about how engineers and scientists are making scientific and technological breakthroughs and creating the future today! The day's program includes presentations by scientists from around the world:
- Ajit Abraham (Sai University, India) will present on “Generative AI in Healthcare”
- Nebojša Bačanin Džakula (Singidunum University, Serbia) will talk about the latest advances in bio-inspired metaheuristics
- AIexandre Ferreira Ramos (University of São Paulo, Brazil) will present his work on using thermodynamic models to study the regulatory logic of transcriptional control at the DNA level
- Anderson Rocha (University of Campinas, Brazil) will give a presentation entitled “AI in the New Era: From Basics to Trends, Opportunities, and Global Cooperation”.
And in the special AIJ Junior track, we will talk about how AI helps us learn, create and ride the wave with AI.
The day will conclude with an award ceremony for the winners of the AI Challenge for aspiring data scientists and the AIJ Contest for experienced AI specialists. The results of an open selection of AIJ Science research papers will be announced.
Ride the wave with AI into the future!
Tune in to the AI Journey webcast on November 19-21.
Speakers include visionaries Kai-Fu Lee and Chen Qufan, as well as dozens of global AI gurus! Do you agree with their predictions about AI?
On November 20, we will focus on the role of AI in business and economic development and present technologies that will help businesses and developers be more effective by unlocking human potential.
On November 21, we will talk about how engineers and scientists are making scientific and technological breakthroughs and creating the future today! The day's program includes presentations by scientists from around the world:
- Ajit Abraham (Sai University, India) will present on “Generative AI in Healthcare”
- Nebojša Bačanin Džakula (Singidunum University, Serbia) will talk about the latest advances in bio-inspired metaheuristics
- AIexandre Ferreira Ramos (University of São Paulo, Brazil) will present his work on using thermodynamic models to study the regulatory logic of transcriptional control at the DNA level
- Anderson Rocha (University of Campinas, Brazil) will give a presentation entitled “AI in the New Era: From Basics to Trends, Opportunities, and Global Cooperation”.
And in the special AIJ Junior track, we will talk about how AI helps us learn, create and ride the wave with AI.
The day will conclude with an award ceremony for the winners of the AI Challenge for aspiring data scientists and the AIJ Contest for experienced AI specialists. The results of an open selection of AIJ Science research papers will be announced.
Ride the wave with AI into the future!
Tune in to the AI Journey webcast on November 19-21.
❤5👍1🔥1🥰1
What is the broadest concept among AI, ML, and DL?
Anonymous Quiz
12%
A) Machine Learning
17%
B) Deep Learning
46%
C) Artificial Intelligence
25%
D) Data Science
❤3🔥1
Machine Learning is a subset of…
Anonymous Quiz
17%
A) Deep Learning
74%
B) Artificial Intelligence
4%
C) Robotics
5%
D) Data Engineering
❤3🔥1
What does Machine Learning need to learn?
Anonymous Quiz
16%
A) Instructions
70%
B) Data
5%
C) Hardware
9%
D) Rules
❤2🔥1
Which of these uses neural networks with many layers?
Anonymous Quiz
7%
A) Rule-based AI
8%
B) Traditional ML
77%
C) Deep Learning
8%
D) Genetic Algorithms
❤2
Which is best for tasks like face recognition and voice assistants?
Anonymous Quiz
17%
A) AI
18%
B) ML
24%
C) DL
42%
D) All of the above
👍5🔥1
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She’s made trading SO SIMPLE that anyone can do it.
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❗️Follow her trades step by step
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🚨 BONUS: Lisa is giving away $10,000 to her subscribers!
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✅ How to Choose the Right AI Skill to Learn in 2025 🤖🎯
AI is broad, but choosing the right skill makes it manageable. Here's how to decide:
1️⃣ Define Your Interest
- Want to build AI models? Start with Python, NumPy, scikit-learn
- Like text-based AI? Focus on NLP, Transformers, LLMs
- Into AI apps/tools? Learn LangChain, RAG, vector DBs
2️⃣ Follow Market Signals
- AI roles are booming: ML Engineer, AI Developer, Data Scientist
- Skills in demand: TensorFlow, PyTorch, GenAI tools, OpenAI APIs
3️⃣ Choose a Track & Go Deep
- Track:
- ML Core: Algorithms, model tuning, deployment
- LLMs & RAG: OpenAI, LangChain, Pinecone
- AI Agents: AutoGen, CrewAI, planning tools
- Stick to one, build solid projects
4️⃣ Learn from Free & Top Sources
- YouTube, GitHub, free MOOCs
- Follow AI communities on Discord, X (Twitter), and LinkedIn
5️⃣ Build Real AI Projects
- Chatbots, RAG search engines, AI agents
- Host on GitHub, write case studies
6️⃣ Understand AI Ethics & Safety
- Learn about fairness, hallucination handling, guardrails
- Critical for responsible AI use
✨ Don’t chase everything. Go deep in one branch and grow from there.
💬 Double Tap ❤️ for more!
AI is broad, but choosing the right skill makes it manageable. Here's how to decide:
1️⃣ Define Your Interest
- Want to build AI models? Start with Python, NumPy, scikit-learn
- Like text-based AI? Focus on NLP, Transformers, LLMs
- Into AI apps/tools? Learn LangChain, RAG, vector DBs
2️⃣ Follow Market Signals
- AI roles are booming: ML Engineer, AI Developer, Data Scientist
- Skills in demand: TensorFlow, PyTorch, GenAI tools, OpenAI APIs
3️⃣ Choose a Track & Go Deep
- Track:
- ML Core: Algorithms, model tuning, deployment
- LLMs & RAG: OpenAI, LangChain, Pinecone
- AI Agents: AutoGen, CrewAI, planning tools
- Stick to one, build solid projects
4️⃣ Learn from Free & Top Sources
- YouTube, GitHub, free MOOCs
- Follow AI communities on Discord, X (Twitter), and LinkedIn
5️⃣ Build Real AI Projects
- Chatbots, RAG search engines, AI agents
- Host on GitHub, write case studies
6️⃣ Understand AI Ethics & Safety
- Learn about fairness, hallucination handling, guardrails
- Critical for responsible AI use
✨ Don’t chase everything. Go deep in one branch and grow from there.
💬 Double Tap ❤️ for more!
❤1
🤖 AI Career Paths & What to Learn 💡
🧑💻 1. Machine Learning Engineer
▶️ Tools: Python, TensorFlow, PyTorch
▶️ Skills: ML algorithms, model training, deployment
▶️ Projects: Image recognition, fraud detection, recommendation systems
🗣️ 2. NLP Engineer
▶️ Tools: Python, Hugging Face, spaCy, Transformers
▶️ Skills: Text processing, language modeling, chatbot development
▶️ Projects: Sentiment analysis, question answering, language translation
🤖 3. AI Researcher
▶️ Tools: Python, PyTorch, Jupyter, academic papers
▶️ Skills: Algorithm design, experimentation, deep learning theory
▶️ Projects: Novel model development, publishing papers, prototyping
⚙️ 4. AI Engineer (AI Agent Specialist)
▶️ Tools: LangChain, AutoGen, OpenAI APIs, vector databases
▶️ Skills: Prompt engineering, agent design, multi-agent workflows
▶️ Projects: Autonomous chatbots, task automation, AI assistants
💾 5. Data Scientist (AI Focus)
▶️ Tools: Python, R, Scikit-learn, MLflow
▶️ Skills: Data analysis, feature engineering, predictive modeling
▶️ Projects: Customer churn prediction, demand forecasting, anomaly detection
🛠️ 6. AI Product Manager
▶️ Tools: Jira, Asana, SQL, BI tools
▶️ Skills: AI project planning, stakeholder communication, user research
▶️ Projects: AI feature rollout, user feedback analysis, roadmap creation
🔒 7. AI Ethics Specialist
▶️ Tools: Research papers, policy frameworks
▶️ Skills: Fairness auditing, bias detection, regulatory compliance
▶️ Projects: AI audits, ethical guidelines, transparency reports
💡 Tip: Pick your AI role → Master core tools → Build projects → Join AI communities → Showcase work
AI Resources: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
💬 Tap ❤️ for more!
🧑💻 1. Machine Learning Engineer
▶️ Tools: Python, TensorFlow, PyTorch
▶️ Skills: ML algorithms, model training, deployment
▶️ Projects: Image recognition, fraud detection, recommendation systems
🗣️ 2. NLP Engineer
▶️ Tools: Python, Hugging Face, spaCy, Transformers
▶️ Skills: Text processing, language modeling, chatbot development
▶️ Projects: Sentiment analysis, question answering, language translation
🤖 3. AI Researcher
▶️ Tools: Python, PyTorch, Jupyter, academic papers
▶️ Skills: Algorithm design, experimentation, deep learning theory
▶️ Projects: Novel model development, publishing papers, prototyping
⚙️ 4. AI Engineer (AI Agent Specialist)
▶️ Tools: LangChain, AutoGen, OpenAI APIs, vector databases
▶️ Skills: Prompt engineering, agent design, multi-agent workflows
▶️ Projects: Autonomous chatbots, task automation, AI assistants
💾 5. Data Scientist (AI Focus)
▶️ Tools: Python, R, Scikit-learn, MLflow
▶️ Skills: Data analysis, feature engineering, predictive modeling
▶️ Projects: Customer churn prediction, demand forecasting, anomaly detection
🛠️ 6. AI Product Manager
▶️ Tools: Jira, Asana, SQL, BI tools
▶️ Skills: AI project planning, stakeholder communication, user research
▶️ Projects: AI feature rollout, user feedback analysis, roadmap creation
🔒 7. AI Ethics Specialist
▶️ Tools: Research papers, policy frameworks
▶️ Skills: Fairness auditing, bias detection, regulatory compliance
▶️ Projects: AI audits, ethical guidelines, transparency reports
💡 Tip: Pick your AI role → Master core tools → Build projects → Join AI communities → Showcase work
AI Resources: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
💬 Tap ❤️ for more!
❤2
What role does AI play in healthcare?
Anonymous Quiz
8%
A. Manage hospital billing
15%
B. Schedule appointments
77%
C. Read X-rays and assist in diagnosis
1%
D. Clean hospital equipment
🔥1
How does AI help in finance?
Anonymous Quiz
0%
A. Prints currency
95%
B. Detects fraud and enables smart trading
4%
C. Manages physical bank branches
1%
D. Files taxes
🔥2
Which of these uses AI in e-commerce?
Anonymous Quiz
3%
A. Product packaging
3%
B. Warehouse construction
92%
C. Personalized product recommendations
3%
D. Manual checkout processing
👏1
What powers self-driving cars like Tesla?
Anonymous Quiz
15%
A. Motion sensors only
12%
B. Rule-based software
72%
C. Deep learning models
1%
D. Manual programming
👍1
What do Siri and Alexa use to understand human speech?
Anonymous Quiz
1%
A. Spreadsheets
3%
B. SQL queries
94%
C. Natural Language Processing
2%
D. Keyboard shortcuts
🔥1
How does AI assist in agriculture?
Anonymous Quiz
3%
A. Driving tractors
3%
B. Forecasting sales
93%
C. Predicting weather and monitoring crops
1%
D. Planting seeds manually
👏1