Artificial Intelligence | ChatGPT AI | Data Science & Machine Learning
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Red:📈 Análisis del canal de Telegram Artificial Intelligence | ChatGPT AI | Data Science & Machine Learning
El canal Artificial Intelligence | ChatGPT AI | Data Science & Machine Learning (@aichads) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 22 924 suscriptores, ocupando la posición 5 625 en la categoría Tecnologías y Aplicaciones y el puesto 1 726 en la región EEUU.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 22 924 suscriptores.
Según los últimos datos del 29 septiembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 55, y en las últimas 24 horas de 2, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 4.40%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.87% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 009 visualizaciones. En el primer día suele acumular 199 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 3.
- Intereses temáticos: El contenido se centra en temas clave como tpg, learning, reply, chunk, \[\.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Best Place to know latest AI Trends & Projects. Latest updates on Artificial Intelligence, Deep Learning, Machine Learning, and Computer Vision 💻💹
Admin: @love_data
Buy ads: https://telega.io/c/aichads”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 30 septiembre, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
22 924
Suscriptores
+224 horas
-97 días
+5530 días
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Publicaciones del Canal
🎯 GigaChat 3.5 Reasoning: 5 Key Features
1️⃣ Advanced Reasoning: Explores multiple step-by-step paths, using automated verification to reinforce correct answers and self-correct
2️⃣ Autonomous Tool Usage: Independently decides when to call external APIs or revise earlier steps
3️⃣ Linear Attention: Proprietary architecture retains key context points without re-matching from scratch
4️⃣ Token Economy: Uses 37% fewer tokens than DeepSeek V4 Flash Preview on math problems
5️⃣ Proven Performance: Open-source LLM (built on GigaChat 3.5 Ultra) with massive benchmark gains:
• IFBench: 44 → 77
• Natural Plan: 64 → 80
• LiveCodeBench v6: 56 → 85
🔗 MIT License. Weights on Hugging Face: fp8 | bf16
| 2 | How to use ChatGPT to improve your decision-making 🧠🎯
Prompt:
I want you to act as my personal decision-making coach.
My goal is to make clearer, more logical, and better-informed decisions.
Help me by:
• First, assess how I currently make decisions through questions and real-life scenarios
• Identify common patterns, biases, or mistakes in my thinking
• Teach me practical decision-making frameworks
• Give me realistic situations where I have to make a choice
• Ask me to explain my reasoning before giving feedback
• Challenge my assumptions and help me consider alternative perspectives
• Show me how to separate facts, assumptions, emotions, and opinions
• Help me evaluate risks, trade-offs, and consequences
• Give me exercises to strengthen my critical thinking
• Track my progress and gradually increase the difficulty
Don't make decisions for me. Help me develop the ability to make better decisions independently.
Start with the first scenario.
Double Tap ❤️ For More Useful Prompts | 404 |
| 3 | ✅ Top 5 Mistakes to Avoid When Learning Artificial Intelligence 🤖❌
1️⃣ Skipping Math Foundations
AI relies on linear algebra, calculus, and probability. Learn the basics or struggle later.
2️⃣ Confusing AI with ML and DL
AI is the broad field. ML and DL are subsets. Know the difference to learn the right tools.
3️⃣ Focusing Only on Code
Don't just run models. Understand why and how algorithms work under the hood.
4️⃣ Neglecting Ethics and Bias
AI systems affect real lives. Always check for fairness, explainability, and transparency.
5️⃣ Not Building Real-World Projects
Theory won't get you hired. Apply AI in fields like healthcare, finance, or NLP. Share results.
💬 Tap ❤️ for more! | 531 |
| 4 | AI Automation is hard until you watch those videos 👇
1/ N8N Full Course: Build AI Automations in 2026:
https://www.youtube.com/watch?v=7_PeuTsx7UM
2/ Make.com AI Agent Tutorial
https://www.youtube.com/watch?v=3L48KfOrIo8
3/ AI Automation Concepts: APIs, Webhooks, RAG & MCP:
https://www.youtube.com/watch?v=s4hF6VbyOQU
4/ Automate Everything with Zapier AI Agents:
https://www.youtube.com/watch?v=avQMU1yJkyY
5/ 5/ AI-Powered Social Media Agent with n8n & Make:
https://www.youtube.com/watch?v=K1VwNCfBYE8 | 1 004 |
| 5 | 🤖 AI News of the Day: 11 September 2026
1️⃣ AI misuse raises major security concerns ⚠️
Anthropic says it disrupted multiple attempts to misuse its Claude models for cyberattacks, surveillance, weapons development and biological research. The findings are intensifying debate over AI safeguards.
2️⃣ US lawmakers push for tougher AI rules 🏛️
Growing concerns about advanced AI systems have prompted lawmakers from both parties to consider stronger oversight, independent evaluations and emergency controls for powerful AI models.
3️⃣ China's Z.AI raises $5 billion 💰
Chinese AI company Z.AI has launched a massive $5 billion fundraising effort to finance computing infrastructure, research, acquisitions and expansion as competition with US AI companies intensifies.
4️⃣ AI agents become the new cybersecurity challenge 🛡️
Anthropic's latest report says attackers are increasingly using AI agents to automate reconnaissance, data theft and cyber operations, reducing the amount of human involvement required.
5️⃣ India becomes increasingly important to global AI 🇮🇳
Anthropic's India leadership says the country's large developer community and willingness to experiment are helping shape AI products and adoption strategies for global markets.
Double Tap ❤️ For More | 1 048 |
| 6 |  Your Data Science degree just got an AI update.
Yeah.
Things are moving fast.
Python. SQL. Machine Learning. Deep Learning. MLOps.
And now GenAI, LLMs, RAG & AI-powered workflows.
An 8-month program with 20+ industry projects and live weekend classes.
Maybe Data Science was just the beginning.
https://lp.pwskills.com/data-science-ai-online-program-pw-skills?utm_source=telegram&utm_medium=influencer&utm_campaign=deepakAugDS | 1 269 |
| 7 |  +5n8n cheat sheet
I wish I had this cheat sheet when I started automating using n8n.
Save this before it disappears. This cheat sheet covers everything from triggers to AI agents, expressions to keyboard shortcuts. Whether you're building your first workflow or your hundredth, you'll want this in your back pocket. | 1 271 |
| 8 | Top AI Models for Developers
There is no single winner for every dev task.
1. Claude — Anthropic
Best for: Complex coding & large codebases
Excellent for: Debugging, refactoring, code reviews, multi-file changes, agentic coding, understanding existing codebases
Best choice: Complex production development
2. GPT — OpenAI
Best for: All-round software development
Excellent for: Coding, debugging, architecture, algorithms, code explanation, agentic workflows
Best choice: Developers who want one versatile model
3. ChatGPT — Google
Best for: Large codebases & multimodal development
Excellent for: Large-context code analysis, coding, documentation, multimodal inputs, Google Cloud development
Note: Very large context window is great for big repositories
4. DeepSeek
Best for: Cost-effective coding & reasoning
Excellent for: Coding, mathematics, reasoning, debugging, high-volume development
Best choice: Strong performance at lower cost
5. Qwen
Best for: Open-weight coding
Excellent for: Code generation, coding agents, local deployment, customization, multilingual development
Best choice: You want control over deployment and open-weight models
6. Grok — xAI
Best for: Coding + real-time information
Useful for: Coding, reasoning, web research, current information, developer experimentation
7. Mistral
Best for: Efficient/open AI development
Useful for: Enterprise applications, coding, local/private deployments, multilingual applications
8. Llama — Meta
Best for: Open-weight AI development
Useful for: Local AI, fine-tuning, research, custom AI applications, private deployments
9. Kimi — Moonshot AI
Best for: Reasoning + long-context development
Useful for: Complex reasoning, coding, large-context tasks, AI agents
10. GLM — Zhipu AI
Best for: Coding + agents + open models
Useful for: Code generation, reasoning, agent development, open-weight experimentation
Quick Ranking for Developers
🥇 Claude → Complex coding & refactoring
🥈 GPT → Best all-rounder
🥉 ChatGPT → Large codebases & multimodal work
4️⃣ DeepSeek → Cost-effective coding
5️⃣ Qwen → Open-weight/local coding
6️⃣ Grok → Coding + real-time information
7️⃣ Mistral → Efficient/open AI
8️⃣ Llama → Custom/local AI
9️⃣ Kimi → Long-context reasoning
🔟 GLM → Agents + coding
These rankings are task-dependent. Different models win different coding scenarios.
How to pick for your workflow:
Working on a 100k line repo → Claude or ChatGPT for context + refactoring
Need one model for everything → GPT
Budget + high volume → DeepSeek
Need local/private deployment → Qwen, Llama, Mistral
Building agents → GLM, Kimi, Claude
Need live docs + X trends → Grok
Double Tap ❤️ For More
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2.14 ₽ · /balance_help | 1 059 |
| 9 | 5 Free Courses to Go From AI Beginner to Practitioner
1️⃣ Harvard CS50: Introduction to AI with Python
🎓 Learn the fundamentals of AI before diving into machine learning. Build AI projects like Tic-Tac-Toe, search algorithms, and logic solvers while mastering core AI concepts.
👉 Click Here: https://cs50.harvard.edu/ai/
2️⃣ Google Machine Learning Crash Course
📊 Google's official ML course teaches gradient descent, TensorFlow, feature engineering, and model training with interactive lessons used by Google engineers.
👉 Click Here: https://developers.google.com/machine-learning/crash-course
3️⃣ fast.ai – Practical Deep Learning for Coders
💻 Build real deep learning models from the very first lesson. Learn computer vision, NLP, PyTorch, and deploy AI applications with practical projects.
👉 Click Here: https://course.fast.ai/
4️⃣ Hugging Face NLP Course
🤖 Master Transformers, LLMs, and modern Generative AI. Learn to fine-tune open-source models using the Hugging Face ecosystem.
👉 Click Here: https://huggingface.co/learn/nlp-course
5️⃣ Andrej Karpathy – Neural Networks: Zero to Hero
🧠 Build neural networks and a mini GPT completely from scratch. One of the best free resources to deeply understand how LLMs actually work.
👉 Click Here: https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ
❤️ Follow AIJobs for more AI drops | 1 099 |
| 10 | ✅ Top Artificial Intelligence Concepts You Should Know 🤖🧠
🔹 1. Natural Language Processing (NLP)
Use Case: Chatbots, language translation
→ Enables machines to understand and generate human language.
🔹 2. Computer Vision
Use Case: Face recognition, self-driving cars
→ Allows machines to "see" and interpret visual data.
🔹 3. Machine Learning (ML)
Use Case: Predictive analytics, spam filtering
→ AI learns patterns from data to make decisions without explicit programming.
🔹 4. Deep Learning
Use Case: Voice assistants, image recognition
→ A type of ML using neural networks with many layers for complex tasks.
🔹 5. Reinforcement Learning
Use Case: Game AI, robotics
→ AI learns by interacting with the environment and receiving feedback.
🔹 6. Generative AI
Use Case: Text, image, and music generation
→ Models like ChatGPT or DALL·E create human-like content.
🔹 7. Expert Systems
Use Case: Medical diagnosis, legal advice
→ AI systems that mimic decision-making of human experts.
🔹 8. Speech Recognition
Use Case: Voice search, virtual assistants
→ Converts spoken language into text.
🔹 9. AI Ethics
Use Case: Bias detection, fair AI systems
→ Ensures responsible and transparent AI usage.
🔹 10. Robotic Process Automation (RPA)
Use Case: Automating repetitive office tasks
→ Uses AI to handle rule-based digital tasks efficiently.
💡 Learn these concepts to understand how AI is transforming industries!
💬 Tap ❤️ for more! | 1 394 |
| 11 |  If you’re a student, graduate, or someone looking for a career switch, read this.
Most people spend months watching random YouTube videos and still don’t become job-ready.
Instead, learn in a structured offline classroom.
📌 Data Analytics with GenAI
📌 Python + SQL + Power BI
📌 6-Month Program
📌 1:1 Mentorship
📌 Job Assistance
📍Now available in your city.
Seats are limited.
👉 Register Here: https://lp.pwskills.com/data-analytics-course-offline-batch0?utm_source=telegram&utm_medium=influencer&utm_campaign=daoffline | 1 034 |
| 12 |  Aaj hi ek certified Hackar bano!💻
Shuru se saari cheeze seekho bilkul basic se!!
PW skills leke aaya h certified Ethical Hacking ka course!!
Isme milega :
✅ Hands on Practice
✅ LIVE Hacking Labs
✅ Certificate after Completion
Sirf Rs 4999 mai
Abhi enroll karo HACK30 Coupon code use karke 30% OFF milega!
Enroll NOW : https://pwskills.com/web-development/certified-ethical-hacking-course-035473/?source=pwskills.com&position=course_dropdown&from=home_page&utm_source=pwskills&utm_medium=telegram&utm_campaign=ethical_hacking | 1 185 |
| 13 |  Sin texto... | 1 154 |
| 14 |  🤝 Agentic AI Explained | 1 121 |
| 15 | 🎯 Step by step AI and ML roadmap with a YouTube playlist 👇
Step 1 - Python programming:
https://youtu.be/eirjjyP2qcQ?si=KuAvg-DuKxMkD7jR
Step 2 - Foundation of AI/ML:
https://youtu.be/VOpETRQGXy0?si=mfJ86zEFHv2VqGrb
Step 3 - Data Science:
https://youtu.be/fM4qTMfCoak?si=AhpjlpEmRAQh9k0g
Step 4 - Gen AI + LLM foundation:
https://youtu.be/pSVk-5WemQ0?si=7tb-RGCSxwrXV5E2
Step 5 - LangChain + LangGraph:
https://youtu.be/yC36gN-rqjo?si=43HnisWd1V1IfvRM
Step 6 - Model Context Protocol:
https://youtu.be/3_TN1i3MTEU?si=nkp-nGv-MN0X9Ukb
Step 7 - Google ADK + A2A:
https://youtu.be/mFkw3p5qSuA?si=cTJZiYX7L1ZdVwOc
React '❤️' for more such content! | 1 432 |
| 16 |  🐶 ASO Corgi — platform for the App Store developers.
Find the keywords your apps and competitors rank for, and track positions across every country in one place.
🔑 Keyword research: by topic, by your app's languages, from App Store suggestions, by competitors, and with AI analysis.
• Rankings by country — history, charts, demand score (0–100)
• Global search across any App Store storefront
• ASO assistant builds your listing for each locale
• App Store top charts for any country
🎁 14 days of Pro, free 👇 (no card required)
https://asocorgi.com/?promo=promo14&utm_source=aichads&utm_medium=telegram&utm_campaign=launch | 1 191 |
| 17 | AI agents are no longer just a developer toy.
OpenAI published new research on how agents are changing work, and the main takeaway is important:
AI is moving from short chat interactions to delegated long-horizon tasks.
That sounds abstract, but here is the simple version:
Old way:
ask AI one question, get one answer.
New way:
give AI a task, let it work for minutes or hours, review the result.
This is the shift that matters.
According to OpenAI's research, by May 2026, 80.6% of sampled individual Codex users made at least one request estimated to represent more than 30 minutes of human work.
70.2% made at least one request estimated at more than one hour of human work.
And 25.6% delegated work estimated to take more than eight hours.
The most interesting part:
Non-developer adoption is growing fast.
That means agents are not only for engineers anymore.
They are becoming useful for:
- operations
- support
- finance
- recruiting
- marketing
- research
- reporting
- personal productivity
- small business workflows
This is the practical question now:
Not "Which AI model is smartest?"
But:
"What work can I safely delegate to an agent?"
The answer is not "everything."
The answer is:
one clear task,
with context,
tools,
rules,
memory,
and human review.
This is what we will focus on next:
how to turn normal work into agent-ready tasks.
Not theory.
Not hype.
Practical AI systems you can actually build and use.
Sources:
https://openai.com/index/how-agents-are-transforming-work/
https://www.axios.com/2026/06/25/codex-agents-growth-openai | 1 188 |
| 18 |  🤖 Anthropic updates Claude Design with brand style sync
Anthropic's Claude Design now integrates your design system directly from repositories, design files, or codebases to maintain your brand style across projects. It builds interfaces using your real components and checks compliance before you see the result.
The editor is more stable for daily use and adds new layout controls. You can drag, resize, and align elements on the canvas without extra steps. Claude Design and Claude Code sync bidirectionally, letting you start in code or design and keep projects aligned.
Finished work exports to PDF, PowerPoint, or other tools you already use. This update tightens the workflow between design and development with fewer style mismatches.
📊@tech | 1 104 |
| 19 | ✅ Today's AI News
1️⃣ AI regulation is tightening
Reuters reports fresh pressure on xAI, OpenAI, and Anthropic, with lawsuits, access restrictions, and national-security concerns all in focus.
2️⃣ Big tech spending on AI is still huge
Microsoft’s AI infrastructure push, Google’s Gemini updates, and broader platform expansion remain major parts of the story.
3️⃣ AI is reshaping business models
The Economist highlights rising costs from AI agents and notes that companies are still figuring out how to make AI economically efficient.
4️⃣ India is a major AI hub right now
Indian Express is tracking AI governance, Anthropic’s India expansion, OpenAI’s compute growth, and Google’s AI features.
5️⃣ Research and product launches keep accelerating
MIT, Bloomberg, TechCrunch, and Google all show continued momentum in AI research, tools, and commercial applications.
💬 Tap ❤️ for more! | 1 150 |
| 20 | 🧑💻 Useful AI Tools for Coding – 2026 🤖
1️⃣ Full IDEs
• Cursor (v2 with agentic workflows)
• Windsurf
• Trae
• Zed (AI-native forks)
• JetBrains AI Assistant
• VS Code with CopilotX
2️⃣ IDE Extensions
• GitHub Copilot (Workspace mode)
• Tabnine Pro
• Codeium
• Cline
• Continue.dev
• AskCodi
• Bito
3️⃣ Code Analysis
• CodeRabbit
• Mintlify
• Swimm
• Qodo
• MutableAI
4️⃣ Auto Agents
• Claude Code (3.5 Sonnet)
• OpenDevin
• RooCode
• Aider
• Cognition Devin
• SmythOS
5️⃣ Cloud-based Coding
• GitHub Codespaces (AI-accelerated)
• Amazon Q Developer
• Replit Agent
• StackBlitz
• CodeSandbox AI
• Cursor Cloud
6️⃣ AI Chatbots
• ChatGPT (o3 models)
• Claude
• Gemini 2.0
• Perplexity Labs
• Cody (Sourcegraph)
• Phind
• Grok Code
💬 Tap ❤️ if you found this useful! | 1 281 |
