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🤖 The #1 AI news source! We cover the latest artificial intelligence breakthroughs and emerging trends. Manager: @rational
Показати більше📈 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 783 740 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 783 740 підписників.
За останніми даними від 30 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на -35 261, а за останні 24 години на -1 026, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
- Рівень залученості (ER): Середній показник залученості аудиторії становить 0.68%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.47% реакцій від загальної кількості підписників.
- Охоплення публікацій: В середньому кожен допис отримує 5 340 переглядів. Протягом першої доби публікація в середньому набирає 3 685 переглядів.
- Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 548.
- 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 01 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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Ⓜ️ Meta is reportedly telling engineers to be careful with Claude and Codex and the reason is surprisingly simple: AI can “catch” another AI’s knowledge.
According to reports, Meta has restricted the use of Anthropic’s Claude Code and OpenAI’s Codex for some engineering work to avoid contaminating its own AI training data.
Here’s the concern: if Meta’s future models are trained on outputs generated by rival AIs, competitors could argue Meta distilled their models instead of developing its own. Both OpenAI and Anthropic prohibit using their AI outputs to build competing models.
That doesn’t mean engineers can’t use these tools for everyday coding. The key is keeping those outputs completely separate from anything that could end up training, evaluating, or improving Meta’s own AI.
The biggest legal risks would likely come from deliberate behavior such as mass scraping, automated extraction, or knowingly using competitors’ outputs as training data not casual productivity use.
@aipost 🏴
| 2 |  Ford engineers walking back into HQ
@aipost 🏴 | 1 274 |
| 3 |  +1❗️Ford rehires 350 engineers after replacing them with AI
Ford’s VP of engineering admitted the company “mistakenly thought” AI alone could replace experienced workers and still produce high-quality vehicles, per The Verge.
Ford has recalled more cars than any other US automaker this year after cutting over 5,000 workers since 2020. CEO Jim Farley previously declared that AI is “going to replace literally half of all white-collar workers.”
@aipost 🏴 | 1 475 |
| 4 |  🤖 Anthropic just unveiled Claude Sonnet 5, its smartest and most agentic Sonnet yet.
The model can plan multi-step tasks, browse the web, use terminals and other tools, and work autonomously on problems that only much larger, more expensive AI models could handle a few months ago.
Compared to Sonnet 4.6, it delivers major gains in reasoning, coding, tool use, and knowledge work while approaching the performance of Opus 4.8 at a much lower cost.
Early testers say Sonnet 5 completes complex tasks that previous versions couldn’t finish, double-checks its own work without being prompted, and offers one of the best price-to-performance ratios for AI agents today.
Source.
@aipost 🏴 | 2 323 |
| 5 |  +1❗️Secretary of War Pete Hegseth appointed Marc Andreessen to the Defense Policy Board.
Andreessen is one of 15 members on the newly rebuilt advisory panel. Andreessen has spent years arguing that software, AI, autonomous weapons, drones, robotics, and private manufacturing will reshape national power.
Now he can make that argument directly to the people planning America’s military strategy.
@aipost 🏴 | 3 092 |
| 6 |  🤖 OpenAI is preparing to reveal new Codex hardware on July 15.
It looks like OpenAI is building a physical control panel for an AI coding agent.
@aipost 🏴 | 3 079 |
| 7 |  Chinese AI models now offer processing at rates as low as 18 cents per million tokens, compared to the $4 average charged by leading models, according to CitiBank Research.
By June, 65% of open-source model processing on OpenRouter was handled by these lower-cost options, up from 34% in January. DeepSeek and other models from China have attracted interest due to their affordable pricing.
As companies shift focus to controlling AI costs, the decision to adopt a specific model is increasingly based on price instead of technical superiority. This trend is prompting leading providers like OpenAI and Anthropic to reassess pricing, as enterprises now compare models according to specific tasks.
Gartner projects that by 2028, spending on AI coding may surpass the average salary of a developer.
📰 @aipost | 3 584 |
| 8 |  Agibot robots demonstrate high performance in factory trial
Agibot humanoid robots reached a 99% success rate during a six-day live demonstration at a factory. Over 64 hours of operation, the robots completed 64,828 individual tasks and assembled 17,625 tablet units.
Progress in this field is accelerating, as developments of this magnitude were uncommon a year ago but have recently become more frequent.
📰 @aipost | 3 579 |
| 9 |  🇨🇳 Ex Meta PM and AI founder Xiaoyin Qu says “American and European enterprises will ditch OpenAI and anthropic and adopt Chinese models.”
@aipost 🏴 | 3 788 |
| 10 |  🔥The race to dominate enterprise AI
Anthropic's recent surge has propelled it past OpenAI to become the leading paid AI provider for U.S. businesses, marking a shift in the AI race from model superiority to workflow dominance.
@aipost 🏴 | 3 758 |
| 11 |  We can all relate.
@aipost 🏴 | 4 000 |
| 12 |  🇰🇷 Korea is quietly becoming the world’s humanoid robot factory.
Goldman Sachs Research estimates Korean companies could produce 30% of all humanoid robots by 2035, jumping from virtually zero today to more than 412,000 robots a year. The reason? Decades of automotive manufacturing have given Korea the motors, actuators, supply chains, and factories needed to scale humanoids.
The government is fueling the push with ₩700 billion ($500M) for robotics in 2026, aiming to produce 1,000 domestically built humanoids annually by 2029.
Investors have already noticed. LG Electronics is leveraging its massive motor business to supply humanoid robots, Hyundai Motor is combining its manufacturing muscle with Boston Dynamics, while Hyundai Mobis, Rainbow Robotics, Robotis, and Doosan Robotics are all positioning themselves across the humanoid supply chain.
For broader exposure, Korea’s new humanoid robot ETFs have surged in popularity, with pension funds pouring billions into the sector.
@aipost 🏴 | 3 518 |
| 13 |  🧠 Meta unveils Brain2Qwerty v2: AI can turn brain signals into text, no brain implant required
Imagine typing… without actually typing.
Meta has demonstrated Brain2Qwerty v2, an AI system that converts brain activity into text using a non-invasive magnetoencephalography (MEG) helmet instead of a surgically implanted brain chip.
Here’s how it works:
🪖 The user wears an MEG helmet that measures the tiny magnetic signals produced by the brain.
🧠 As the person thinks about typing, the AI filters through the noisy brain activity.
⌨️ The model reconstructs the intended keystrokes and generates coherent sentences.
The technology is still confined to research labs because MEG scanners are large, expensive, and require highly controlled environments. It’s nowhere near replacing a laptop or smartphone keyboard yet.
Still, it’s a major step for non-invasive brain-computer interfaces. While companies like Neuralink rely on implanted electrodes, Meta is exploring whether AI can decode thoughts without surgery.
@aipost 🏴 | 3 588 |
| 14 |  +1🇺🇸 A closed-door AI demo on Capitol Hill reportedly left U.S. lawmakers shaken.
Anthropic showed members of the House Homeland Security Committee how its Claude Mythos model could identify and connect software vulnerabilities to map out a theoretical attack that could compromise financial systems and potentially drain bank accounts all inside a controlled demonstration. No real money was involved.
Committee Chair Andrew Garbarino also described a separate demo where a jailbroken AI model generated a detailed plan to kidnap a lawmaker in under 30 seconds, though public reports don’t clearly confirm that Mythos was the model used.
The demonstrations underscored a growing concern in Washington: as AI becomes more capable, it could also become a powerful tool for cybercriminals and hostile governments if it falls into the wrong hands.
@aipost 🏴 | 3 842 |
| 15 | A fact-check regarding artificial intelligence’s water consumption, with focus on the impact of data centers, has emerged.
Available data suggests that large AI models and the facilities housing them require notable amounts of water, particularly for cooling equipment during intensive computations. This operational need has led to increased scrutiny of the technology sector’s environmental footprint.
Sources underline that water usage figures can vary depending on the location, the type of cooling technology used, and the demand placed on data centers. Reliable quantification is challenging, as not all companies disclose detailed consumption data. Nonetheless, the topic continues to attract attention as AI development accelerates.
📰 @aipost | 4 041 |
| 16 |  Grok 4.5 has been developed using xAI’s new V9 foundation model, which contains 1.5 trillion parameters and incorporates data from Cursor. This makes it roughly three times larger than its predecessor, the v8-small model, which had 0.5 trillion parameters.
The V9 foundation model is described as a strong, reliable system comparable to Opus, rather than bringing a sudden leap in performance.
Notably, the pace of advancements at SpaceXAI has accelerated, following a shift in focus by several leading engineers from Starlink and Starship projects to artificial intelligence development.
The previous v8 model, used for Grok 4.3, was completed in December with several significant limitations. Grok 4.5 is expected to represent a substantial improvement in capability.
📰 @aipost | 4 136 |
| 17 |  AI is coming for the job of smokers too…
@aipost 🏴 | 4 233 |
| 18 |  ❗️Oracle just crossed a major milestone in the AI era.
For the first time, an S&P 500 company has explicitly linked mass layoffs to AI in an SEC filing.
Oracle cut 21,000 jobs, about 13% of its workforce and took a $1.8 billion restructuring charge, saying AI adoption is driving the changes.
The productivity gains are staggering. Internal pilots reportedly shrank teams of 47 database administrators to just 3 senior architects supported by AI. The system catches 94% of issues before they become problems, while engineering tasks that once took 6 weeks now take just 6 hours.
But this isn’t simply about cutting costs.
Oracle is redirecting those savings into a $50 billion AI infrastructure expansion for fiscal 2026, pouring money into data centers, GPUs, and cloud capacity.
@aipost 🏴 | 4 153 |
| 19 |  🇺🇸 U.S. data center spending now surpasses most infrastructure projects
U.S. spending on data center construction has reached $50 BILLION, now exceeding the COMBINED spending on airports, ports, and mass transit, per Bloomberg.
The AI infrastructure boom continues to accelerate, with US data center construction spending up 357% since 2022 and now accounting for 2.3% of all U.S. construction spending.
@aipost 🏴 | 4 246 |
| 20 |  🇪🇺 Europe wants Anthropic on its own turf
Europe is starting to treat frontier AI like critical infrastructure.
According to Reuters, Austria is urging the EU to convince Anthropic to establish part of its business inside Europe, with EU laws, customers, capital, and infrastructure to reduce the bloc’s dependence on US-controlled AI.
The problem? Moving servers to Europe doesn’t move control.
Anthropic is still an American company, and its ownership, model governance, key employees, and training infrastructure remain subject to US export controls. That means Washington could still restrict access to its most advanced models for foreign users.
Austria’s argument isn’t that this is easy, it’s that Europe shouldn’t rely entirely on AI systems that could become unavailable because of a US political decision.
Source.
@aipost 🏴 | 4 069 |
