Endi mavjud! Telegram Tadqiqoti 2025 — yilning asosiy insaytlari 
Artificial Intelligence
Kanalga Telegram’da o‘tish
🔒 Welcome Artificial Intelligence Channel Buy ads: https://telega.io/c/Artificial_Intelligence_COM
Ko'proq ko'rsatish📈 Telegram kanali Artificial Intelligence analitikasi
Artificial Intelligence (@artificial_intelligence_com) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 70 469 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 1 849-o'rinni va Hindiston mintaqasida 4 788-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 70 469 obunachiga ega bo‘ldi.
14 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 1 228 ga, so‘nggi 24 soatda esa 27 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 7.47% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.10% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 5 264 marta ko‘riladi; birinchi sutkada odatda 1 480 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 10 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent learning, linkedin, linux, udemy, 040k| kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“🔒 Welcome Artificial Intelligence Channel
Buy ads: https://telega.io/c/Artificial_Intelligence_COM”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 15 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
70 469
Obunachilar
+2724 soatlar
+2637 kunlar
+1 22830 kunlar
Postlar arxiv
70 482
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70 482
Meme of the day: Waymo robotaxi is circling around one point due to a malfunction.
The company has already responded and promised to fix Delamain's crazy chariot.
#meme
70 482
📱Artificial Intelligence and Machine Learning
📱Machine Learning Foundations: Prototyping with Edge Impulse
70 482
📂 Full description
Explore the world of machine learning on edge devices with this hands-on course. Robert Gallup—a technologist, designer, and maker—guides you through basic machine learning concepts and workflow. Set up the necessary tools and hardware to develop a voice-driven prototype using the Arduino Nano 33 BLE Sense microcontroller. Discover how to use the Edge Impulse platform to acquire data, train a machine learning model, and generate code for your prototype. Upload and modify the code to complete your prototype using the Arduino IDE. Finally, explore practical challenges in deploying ethical machine learning on edge devices. By the end of this course, you'll be equipped to create your own intelligent prototypes, enhancing your technical portfolio and practical problem-solving abilities.
70 482
🔅 Machine Learning Foundations: Prototyping with Edge Impulse
🌐 Author: Robert Gallup
🔰 Level: Beginner
⏰ Duration: 1h 9m
🌀 Discover how to collect data, train models, and deploy code on the Arduino Nano 33 BLE Sense, making intelligent and responsive prototypes.📗 Topics: Arduino IDE, Machine Learning 📤 Join Artificial Intelligence and Machine Learning for more courses
70 482
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70 482
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
70 482
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
70 482
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
70 482
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
70 482
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
70 482
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
70 482
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
70 482
📂 Full description
Explore the ins and outs of hacking machine learning with the cybersecurity training experts at Infosec Institute. Deep dive into topics such as hacking a CAPTCHA system, fuzzing a target, evading malware detection, and attacking machine learning systems. Plus, learn about deepfakes and how to perform backdoor attacks on machine learning.
This course was created by Infosec Institute. We are pleased to host this training in our library.
70 482
🔅 Machine Learning for Red Team Hackers by Infosec
🌐 Author: Infosec Institute
🔰 Level: Intermediate
⏰ Duration: 3h 39m
🌀 Learn the various techniques used in hacking machine learning.📗 Topics: Ethical Hacking, Machine Learning, Red Teaming 📤 Join Artificial Intelligence and Machine Learning for more courses
70 482
🤗 HuggingFace is offering 9 AI courses for FREE!
These 9 courses covers LLMs, Agents, Deep RL, Audio and more
1️⃣ LLM Course:
https://huggingface.co/learn/llm-course/chapter1/1
2️⃣ Agents Course:
https://huggingface.co/learn/agents-course/unit0/introduction
3️⃣ Deep Reinforcement Learning Course:
https://huggingface.co/learn/deep-rl-course/unit0/introduction
4️⃣ Open-Source AI Cookbook:
https://huggingface.co/learn/cookbook/index
5️⃣ Machine Learning for Games Course
https://huggingface.co/learn/ml-games-course/unit0/introduction
6️⃣ Hugging Face Audio course:
https://huggingface.co/learn/audio-course/chapter0/introduction
7️⃣ Vision Course:
https://huggingface.co/learn/computer-vision-course/unit0/welcome/welcome
8️⃣ Machine Learning for 3D Course:
https://huggingface.co/learn/ml-for-3d-course/unit0/introduction
9️⃣ Hugging Face Diffusion Models Course:
https://huggingface.co/learn/diffusion-course/unit0/1
70 482
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060k| 🔰 Learn React and NextJs
059k| 🔰 Data Analysis and Databases
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+3
🔥 Google has introduced InstructPipe , an AI editor for ML pipelines that works via text queries.
❔ What is InstructPipe?
InstructPipe is an AI assistant that transforms text commands into visual flowcharts representing machine learning pipelines.
The system uses two large language model (LLM) modules and a code interpreter to generate pseudocode and visualize it in a graph editor.
This is a low-code approach: you simply connect ready-made components (nodes) without writing code.
🌟 How does this work?
1️⃣ The user enters a text instruction describing the desired pipeline.
2️⃣ LLM modules process the instruction and generate the corresponding pseudocode.
3️⃣ The code interpreter converts pseudocode into a visual flowchart that you can edit and customize.
✔️ Benefits of InstructPipe
🟡 Accessibility: Allows newcomers to programming to create complex ML pipelines without having to write code.
🟡 Flexibility: Accepts text description in any form, no strict format.
🟡 Lower barrier to entry: Simplifies the process of learning and prototyping ml projects.
🔜 Read more
