Statistics of @ai_release1 for the week 👥 Subscribers: 145 👁 Posts: 105 | Views: 716 | Average: 6.8 🔥 Top
AI Release 📊 Statistics of @ai_release1 for the week 👥 Subscribers: 145 👁 Posts: 105 | Views: 716 | Average: 6.8 🔥 Top posts: • AI Release 📰 Without disclosing the amount: GlobalFoundries and Marvell — 43 👁 • AI Release https://www.youtube.com/watch?v=pnEGnt99-UQ YouTu — 40 👁 • AI Release 📰 Every day hundreds of AI news appear — about — 37 👁 • AI Release https://www.youtube.com/shorts/cFrKSYNk3Sc YouTub — 35 👁 • AI Release 🎬 A real online store created by a neural network — 31 👁 🧪 Weekly trends: This week's main topics were AI agents in real development and new models like GPT-6 Astra, Claude, and DeepSeek. Practical analyses showed that agents are limited not by model quality, but by constraints of instructions, access, and tools, so the industry is shifting from benchmarks to testing on real tasks. In the coming days, expect even more materials on agent debugging, harnesses, and comparisons of fresh models in practice. YouTube AI doesn't think: how LLM actually works 🚀 Free lessons from Merion Academy: https://wiki.merionet.ru/merion-academy/courses?utm_source=YT&utm_medium=own&utm_campaign=llm 🚀 Free part of the Neural Networks course: https://wiki.merionet.ru/merion-academy/course/kurs-po-nejrosetyam-i-mashinnomu-obucheniyu… 4 views 18:05
🤖 AI summary
- Date: 2026-09-21
- Source: t.me
- Key facts:
- AI Release 📊 Statistics of @ai_release1 for the week 👥 Subscribers: 145 👁 Posts: 105 | Views: 716 | Average: 6.8 🔥 Top posts: • AI Release 📰 Without disclosing the amount: GlobalFoundries and Marvell — 43 👁 • AI Release https://www.youtube.com/watch?v=pnEGnt99-UQ YouTu — 40 👁 • AI Release 📰 Every day hundreds of AI news appear — about — 37 👁 • AI Release https://www.youtube.com/shorts/cFrKSYNk3Sc YouTub — 35 👁 • AI Release 🎬 A real online store created by a neural network — 31 👁 🧪 Weekly trends: This week's main topics were AI agents in real development and new models like GPT-6 Astra, Claude, and DeepSeek.
- Practical analyses showed that agents are limited not by model quality, but by constraints of instructions, access, and tools, so the industry is shifting from benchmarks to testing on real tasks.
- In the coming days, expect even more materials on agent debugging, harnesses, and comparisons of fresh models in practice.
- YouTube AI doesn't think: how LLM actually works 🚀 Free lessons from Merion Academy: https://wiki.merionet.ru/merion-academy/courses?utm_source=YT&utm_medium=own&utm_campaign=llm 🚀 Free part of the Neural Networks course: https://wiki.merionet.ru/merion-academy/course/kurs-po-nejrosetyam-i-mashinnomu-obucheniyu…
Source: t.me · post in Telegram