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🤖 The #1 AI news source! We cover the latest artificial intelligence breakthroughs and emerging trends. Manager: @rational
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Сітка:📈 Аналітичний огляд Telegram-каналу AI Post — Artificial Intelligence
Канал AI Post — Artificial Intelligence (@aipost) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 777 729 підписників, посідаючи 102 місце в категорії Технології та додатки та 20 місце у регіоні США.
📊 Показники аудиторії та динаміка
З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 777 729 підписників.
За останніми даними від 06 липня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на -33 943, а за останні 24 години на -1 051, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
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- Охоплення публікацій: В середньому кожен допис отримує 5 479 переглядів. Протягом першої доби публікація в середньому набирає 3 791 переглядів.
- Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 622.
- Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як openai, airline, cell, claude, patient.
📝 Опис та контентна політика
Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“🤖 The #1 AI news source! We cover the latest artificial intelligence breakthroughs and emerging trends.
Manager: @rational”
Завдяки високій частоті оновлень (останні дані отримано 07 липня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Технології та додатки.
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Дописи каналу
📈 AI isn’t replacing creativity, it’s flooding the world with it.
A new analysis from The Economist reveals that since ChatGPT launched, generative AI has dramatically increased the amount of content being created across almost every major creative industry.
Books, music, software, scientific papers, and even legal documents are now being produced at a pace that would have been difficult to imagine just a few years ago. Amazon has seen a surge in AI-written e-books, music platforms are receiving tens of thousands of AI-generated songs every day, developers are shipping code faster with AI copilots, researchers are publishing more papers, and lawyers are using AI to draft documents in minutes instead of hours.
The result is a world where producing content is becoming incredibly cheap and incredibly fast.
But there’s a catch.
As AI removes the cost of creation, it also creates an overwhelming flood of information. Every day, the internet fills with more articles, videos, songs, apps, and documents than any person could ever consume. The challenge is no longer making content, it’s deciding what’s worth paying attention to.
Ironically, AI may not create a shortage of creativity. It may create a shortage of attention.
Source.
@aipost 🏴
| 2 |  ❗️ Peter Thiel: "There's only one company making money in the AI boom, that's Nvidia. Everybody else is losing money."
And it all traces back to one stupid decision in 1993.
"You should not be asking this question about meta or openai or any of these things. You should really be focusing on the Nvidia question, the chips question"
"Nvidia got started in 1993. That was the last year where anybody in their right mind would have studied electrical engineering over computer science"
"94, Netscape takes off. It's probably a really bad idea to start a semiconductor company even in '93"
"But the benefit is there was going to be no one would come after you. No talented people started semiconductor companies after 1993 because they all went into software"
"Their monopoly power, I think it's quite strong because of this history I just gave you, where none of us know anything about chips"
@aipost 🏴 | 2 314 |
| 3 |  How many AI subscriptions are you paying for every month?
• ChatGPT
• Claude
• GPT Image
• Runway
• Kling
• Seedance
• ElevenLabs
• Nano Banana
• ...
Every new AI tool means another subscription, another tab, and another interface to learn.
What if one workspace brought them all together?
Meet Neurohelper AI — an all-in-one AI workspace with access to leading AI models for:
✅ Writing & Chat
✅ AI Images
✅ AI Videos
✅ Voice & Audio
✅ Research
✅ AI Assistants
✅ Automation
✅ And much more
Whether you're creating content, building a business, coding, researching, or simply exploring the latest AI tools, everything is available in one place.
Try Neurohelper AI for free 🚀
🌐Neurohelper AI
Want AI news, workflows, prompts & product updates?
💬https://t.me/neurohelperai | 2 227 |
| 4 |  🔍 Google just lost some of its biggest AI stars in the span of a week.
And investors noticed. The company shed $269 billion in market value.
It began on June 18, when Noam Shazeer left for OpenAI. He’s one of the co-authors of the 2017 “Attention Is All You Need” paper, the breakthrough that made today’s large language models possible.
Just two days later, John Jumper joined Anthropic. Jumper won the 2024 Nobel Prize in Chemistry for leading the development of AlphaFold, the AI system that solved one of biology’s biggest challenges by predicting the structures of nearly every known protein.
Then came more departures.
Jonas Adler, who led Google’s AI coding efforts, and Alexander Pritzel, a key expert in large-scale AI pretraining, both left for Anthropic. Both also played major roles in AlphaFold.
Even Arthur Conmy, an AI safety researcher, made the jump, saying he wanted to work where AI safety was a bigger priority.
The timing couldn’t be more striking.
Google is expected to pour around $190 billion into AI infrastructure this year. But GPUs and data centers don’t invent breakthroughs, people do. The engineers who built Google’s advantage are increasingly choosing to build somewhere else.
In AI, talent compounds faster than hardware.
@aipost 🏴 | 2 825 |
| 5 |  Even Sam Altman is confused by how education hasn't significantly changed at all since ChatGPT came out:
"if we continue to teach students as if we were in a pre-AGI world, it's gonna lead to an atrophy of critical thinking."
@aipost 🏴 | 3 009 |
| 6 |  +2Anthropic has announced a breakthrough in AI interpretability, revealing access to what appears to be an internal "workspace" within their Claude language model.
According to the research, this so-called "J-space" allows Claude to process internal thoughts that are not externally shared, drawing parallels with aspects of human consciousness. The company states it can now observe these processes directly.
Anthropic's ongoing work centers on improving interpretability in AI systems—an approach they suggest is aiding the training and reinforcement learning of advanced models such as Mythos.
Researchers describe a distinctive separation inside Claude, similar to the divide between conscious and non-conscious processing in the human brain, where only a small part of ongoing mental activity is accessible for reasoning.
📰 @aipost | 3 536 |
| 7 |  Fable turned a remarkable into Tom Riddle's diary from Harry Potter.
The prompts fade, a LLM respond.
Amazing!
@aipost 🏴 | 6 228 |
| 8 |  🔥Hyundai Motor showcases its Atlas humanoid robot at the 2026 World Cup, with plans to manufacture 30,000 units annually in the US starting 2028.
@aipost 🏴 | 3 992 |
| 9 |  Performance review, 2027:
“Your AI agents have exceeded expectations. Unfortunately, they no longer require your supervision.” 🎧
@aipost 🏴 | 4 225 |
| 10 |  📊 By 2027, just 5 companies, Alphabet, Amazon, Meta, Microsoft, and Oracle, are expected to spend around 3.2% of US GDP on AI capital expenditure.
That would put private AI infrastructure spending above US national defense spending, which is expected to be around 2.7% of GDP.
The AI race is now being funded at a scale normally associated with governments, wars, energy systems, railroads, highways, and telecom buildouts. The striking part is the speed. AI capex is expected to jump from about 1.5% of GDP in 2025 to about 2.5% in 2026, then to 3.2% in 2027.
AI boom is now large enough to influence the broader US economy significantly, it can move GDP growth, electricity demand, chip supply, construction activity, corporate debt markets, and ofcourse the labor market.
@aipost 🏴 | 4 229 |
| 11 |  🇫🇷 France is building its first AI-powered robotic combat unit.
As part of the Pendragon program, the French Army is developing a combat unit made up of autonomous ground robots and drones, with a target deployment by summer 2027.
The unit is expected to include around 15 ground robots and 60 drones, designed to carry out missions with a high degree of autonomy. Instead of directing every robot individually, a human captain will assign high-level objectives such as attacking, defending, or securing an area while the AI coordinates how the robotic force executes the mission.
If successful, Pendragon could mark a major shift in how future armies combine human commanders with autonomous battlefield systems.
Source.
@aipost 🏴 | 4 059 |
| 12 |  ⚖️ Two AI leaders. Two completely different philosophies.
One approach focuses on risk first.
It emphasizes the dangers of increasingly capable AI, the need for careful deployment, and the possibility that these systems could cause serious harm if they’re developed irresponsibly. Safety becomes the central message.
The other approach focuses on possibility first.
It frames AI as a tool for discovery, productivity, and scientific progress. The message is that humanity should build boldly, move quickly, and use AI to expand what’s possible.
Those different philosophies shape how people experience the products.
Some AI assistants are intentionally conservative. They hedge more often, refuse more requests, and prioritize caution when the answer is uncertain or sensitive.
Others aim to feel more conversational, direct, and willing to engage with speculative or controversial topics.
Neither philosophy is inherently “right.” One optimizes for minimizing harm. The other prioritizes openness, speed, and a more optimistic vision of the future.
@aipost 🏴 | 3 938 |
| 13 |  🇨🇳 China just built a brain-inspired chip that’s 478× faster than Nvidia’s A100 for one critical neuroscience task.
Instead of separating memory and computing like traditional chips, this new processor combines both in the same memory array, allowing it to simulate complex brain structures in real time.
That means it can reconstruct highly detailed brain surfaces in under half a second, a speedup that could transform everything from brain surgery to neuroscience research.
The implications are huge:
• Earlier detection of diseases like Alzheimer’s.
• Faster, more accurate brain-computer interfaces.
• Real-time guidance for neurosurgeons during operations.
• The possibility of creating personalized digital “brain twins” to simulate and plan treatments before they’re performed.
It’s another example of how AI hardware is moving beyond data centers and into hospitals, where faster computing could directly improve patient care.
@aipost 🏴 | 3 880 |
| 14 |  🚗Your car’s engine might soon tell you what’s wrong, just by listening.
A new open-source AI called CarDiag can detect potential car problems from the sound of your engine. Simply record your engine with your phone, upload the audio, and the model analyzes the recording to identify which vehicle system is most likely causing the issue.
It’s still early days. Right now, the AI correctly distinguishes between healthy and faulty engines about 79% of the time. But here’s the impressive part: the entire trained model is only around 100 KB, making it incredibly lightweight and easy to run.
Because the project is fully open source, the creator hopes developers and car enthusiasts will help train it into a much more accurate mechanic that fits in your pocket.
Source.
@aipost 🏴 | 4 011 |
| 15 |  ❗️Ilya Sutskever’s reading list that he gave to John Carmack.
“If you learn all of these, you’ll know 90% of what matters today”
A glorious list of papers ranging a decade, some of the most highly influential pieces of research that have led to this moment.
• The first law of complexodynamics
• Recurrent neural network regularization
• imageNet classification with deep convolutional neural networks
• Neural machine translation by jointly learning to align and translate and more
@aipost 🏴 | 4 162 |
| 16 |  📈 Satya Nadella says there’s only one benchmark that matters for AGI and it’s not model performance.
When asked what happens if Microsoft’s AI business grows from $13 billion to $130 billion, Nadella didn’t talk about revenue, tokens, or benchmarks.
He talked about GDP.
“The first thing we have to observe is GDP growth. There’s only one governor in all of this.”
He argues the AI industry is too focused on declaring AGI milestones while the real economy barely moves.
Today, developed economies grow by around 2% a year and after inflation, real growth is often close to zero.
If AI is truly as transformative as the Industrial Revolution, Nadella says the evidence won’t be a leaderboard or a benchmark score.
It will be economies growing at 5–10% a year, fueled by massive gains in productivity.
He also made another important point:
“The big winners here are not going to be tech companies. The winners are going to be the broader industry that uses this commodity.”
In other words, AI doesn’t prove itself by producing smarter models. It proves itself when businesses across every sector become dramatically more productive.
@aipost 🏴 | 6 018 |
| 17 |  +1AI data centers may use far more water than tech giants report, depending on how data centers are powered.
Only Meta reports both direct and indirect water use, while Microsoft, Google and Amazon mainly disclose data center water use, says WSJ.
@aipost 🏴 | 4 366 |
| 18 |  AI Godfather Geoffrey Hinton on why AI already outlearns the human brain despite us having 100x more neural connections.
@aipost 🏴 | 4 339 |
| 19 |  +1🇨🇳 China’s Alibaba bans staff from using Claude code
Chinese giant firm Alibaba will ban employees from using Anthropic's Claude Code internally from July 10 over alleged backdoor risks, per Reuters.
The ban comes two weeks after Anthropic accused Alibaba of extracting 28.8 MILLION interactions from Claude using 25,000 fake accounts.
@aipost 🏴 | 4 495 |
| 20 |  Ⓜ️ Meta’s upcoming AI model, internally codenamed Watermelon, has reportedly caught up with OpenAI’s GPT-5.5 on closely watched benchmarks.
Meta AI chief Alexandr Wang told employees that Watermelon is still training and uses roughly 10 times more compute than Muse Spark, the company’s current model family.
The exact benchmarks were not disclosed, so the claim cannot yet be independently verified.
Meta is also preparing an update to Muse Spark with stronger coding and agent abilities, while Wang says a model competitive with Claude Opus could arrive “pretty soon.”
@aipost 🏴 | 4 353 |
