Artificial Intelligence - ChatGPT & AI Tech News
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Welcome to ChatGPT & AI Tutorials! 🤖 Unlock the power of Artificial intelligence with clear and concise guides. From basics to advanced techniques, you'll get free Resources to learn AI. 🚀Artificial Intelligence 🚀Machine Learning 🚀Tech News 🚀ChatGPT
显示更多📈 Telegram 频道 Artificial Intelligence - ChatGPT & AI Tech News 的分析概览
频道 Artificial Intelligence - ChatGPT & AI Tech News (@aisigma) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 19 486 名订阅者，在 技术与应用 类别中位列第 6 777，并在 印度 地区排名第 21 593 位。
📊 受众指标与增长动态
自 невідомо 创建以来，项目保持高速增长，吸引了 19 486 名订阅者。
根据 13 七月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 9，过去 24 小时变化为 0，整体触达仍然可观。
- 认证状态： 未认证
- 互动率 (ER)： 平均受众互动率为 3.23%。内容发布后 24 小时内通常能获得 0.69% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 630 次浏览，首日通常累积 135 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 0。
- 主题关注点： 内容集中在 learning, openai, phi, capability, llamafile 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台：
“Welcome to ChatGPT & AI Tutorials! 🤖 Unlock the power of Artificial intelligence with clear and concise guides. From basics to advanced techniques, you'll get free Resources to learn AI.
🚀Artificial Intelligence
🚀Machine Learning
🚀Tech News
🚀Ch...”
凭借高频更新（最新数据采集于 14 七月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 技术与应用 类别中的关键影响点。
19 486
订阅者
无数据24 小时
+37 天
+930 天
数据加载中...
吸引订阅者
七月 '26
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+176
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+351
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+203
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+309
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二月 '26
+422
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一月 '26
+641
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+500
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+588
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+652
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+605
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+775
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+1 075
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+1 515
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+3 620
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+1 047
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+568
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+622
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+1 311
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+249
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+2
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| 日期 | 订阅者增长 | 提及 | 频道 | |
| 14 七月 | +3 | |||
| 13 七月 | +4 | |||
| 12 七月 | 0 | |||
| 11 七月 | +9 | |||
| 10 七月 | 0 | |||
| 09 七月 | +5 | |||
| 08 七月 | +14 | |||
| 07 七月 | 0 | |||
| 06 七月 | +8 | |||
| 05 七月 | 0 | |||
| 04 七月 | +9 | |||
| 03 七月 | 0 | |||
| 02 七月 | +4 | |||
| 01 七月 | +11 |
频道帖子
The only LLM cheat sheet you'll ever need 🚀
Covers the main concepts, architectures, and practical applications.
Basics
- Tokens (tokenization, BPE)
- Embeddings (cosine similarity)
- Attention mechanism (Attention formula, Multi-Head Attention)
Transformer architecture and its variants
- BERT (models with only an encoder)
- GPT (models with only a decoder)
- T5 (models with an encoder and a decoder)
Large language models (LLMs)
- Prompting (context length, Chain-of-Thought)
- Pre-training (SFT, PEFT/LoRA)
- Preference tuning (Reward Model, Reinforcement Learning)
- Optimizations (Mixture of Experts, Distillation, Quantization)
Applications
- LLM-as-a-Judge (LaaJ)
- RAG (Retrieval-Augmented Generation)
- Agents (ReAct)
- Reasoning models (Scaling)
| 2 |  Today, we can see AI agents almost everywhere, making our lives easier. Almost every field benefits from it, whether it is your last-minute ticket booking or your coding companion.
AI agents have effectively tapped into every market. Everyone wants to build them to optimize their workflows. This post explores the top 8 things that you should keep in mind while building your AI agent. | 263 |
| 3 | 🎯 7 best YouTube channels to learn AI from scratch 👇
1/ DeepLearning AI:
https://www.youtube.com/c/DeepLearningAI
2/ Krish Naik:
https://www.youtube.com/channel/UCNU_lfiiWBdtULKOw6X0Dig
3/ StatQuest with Josh Starmer:
https://www.youtube.com/c/joshstarmer
4/ 3Blue1Brown:
https://www.youtube.com/c/3blue1brown
5/ FreeCodeCamp
https://www.youtube.com/c/Freecodecamp
6/ Yannic Kilcher:
https://www.youtube.com/c/YannicKilcher
7/ IBM Technology:
https://www.youtube.com/c/IBMTechnology | 542 |
| 4 |  Google DeepMind CEO, Demis Hassabis:
AGI is now at the edge of the singularity.
Cyber is only the first warning shot.
Bio and nuclear risks may come within 2 years.
"That's just a warning shot for humanity."
AGI safety now needs global standards. | 719 |
| 5 | 50 AI/Dev Projects 🚀
React ❤️ For More | 938 |
| 6 | Claude prompts to optimize your GitHub profile 🚀
React ❤️ For More | 1 184 |
| 7 | AI/ML roadmap
Topic: Mathematics
- Subtopic: Linear Algebra
- Vectors, Matrices, Eigenvalues and Eigenvectors
- Subtopic: Calculus
- Differentiation, Integration, Partial Derivatives
- Subtopic: Probability and Statistics
- Probability Theory, Random Variables, Statistical Inference
Topic: Programming
- Subtopic: Python
- Python Basics, Libraries like NumPy, Pandas, Matplotlib
Topic: Machine Learning
- Subtopic: Supervised Learning
- Linear Regression, Logistic Regression, Decision Trees
- Subtopic: Unsupervised Learning
- Clustering, Dimensionality Reduction[1](https://i.am.ai/roadmap)
- Subtopic: Neural Networks and Deep Learning
- Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks
Topic: Specializations
- Subtopic: Natural Language Processing
- Text Preprocessing, Topic Modeling, Word Embeddings
- Subtopic: Computer Vision
- Image Processing, Object Detection, Image Segmentation
- Subtopic: Reinforcement Learning
- Markov Decision Processes, Q-Learning, Policy Gradients
Join for more: https://t.me/machinelearning_deeplearning | 1 210 |
| 8 |  🧠 How to Build an AI Agent | 978 |
