AI Post — Artificial Intelligence
Kanalga Telegram’da o‘tish
🤖 The #1 AI news source! We cover the latest artificial intelligence breakthroughs and emerging trends. Manager: @rational
Ko'proq ko'rsatish2025 yil raqamlarda

979 896
Obunachilar
-50524 soatlar
-3 5877 kunlar
-15 75230 kunlar
Postlar arxiv
Photo unavailableShow in Telegram
Gemini 3 Pro achieved an IQ score of 130 (this corresponds to the top ~2.1% of the human population).
By the and of next year we will likely reach 150-180IQ and in 2027 we will have AI more intelligent than John von Neumann. Before 2030 we will have millions of Johns von Neumanns level AI agents/scientists working together 24/7. Even 10 Johns von Neumanns would change the world. Now think about having million times more.
Ignore the distractions, the constant fixation on race, tribalism, and other forms of superficial conflict we see here. The future is being built by those who rise above that noise and focus on engineering, science, and progress.
100 000 000+ John von Neumann AI's in 2027.
AI Post 🪙 | Our X 🥇
🤔 21🔥 13❤ 9👍 4👀 3
01:05
Video unavailableShow in Telegram
ChatGPT Voice now works directly in the chat window
You can now use ChatGPT Voice without switching modes just start talking. Answers appear as you speak, and you can scroll, review past messages, and see visuals like images or maps in real time.
• Works across mobile and web
• No separate interface or voice-only mode
• Rolling out to all users — just update the app
AI Post 🪙 | Our X 🥇
IMG_1269.MP420.30 MB
❤ 20👍 15🤪 4🔥 3
Photo unavailableShow in Telegram
Nvidia responds to news of Meta using Google's TPUs, sending $NVDA stock -6% lower:
"We're delighted by Google's success — they've made great advances in Al and we continue to supply to Google.
NVIDIA is a generation ahead of the industry — it's the only platform that runs every Al model and does it everywhere computing is done. NVIDIA offers greater performance, versatility, and fungibility than ASICs, which are designed for specific Al frameworks or functions."
The AI wars are heating up.
AI Post 🪙 | Our X 🥇
👍 14🤪 12😁 9❤ 4👾 3
Photo unavailableShow in Telegram
Meta becomes first big tech buyer of Google TPUs for Its own data centers
Meta is set to purchase Google’s TPUs — and not as cloud rentals, but as physical hardware installed directly into Meta’s data centers starting in 2027. This makes Meta the first major company to adopt Google’s chips at the infrastructure level.
Earlier this year, Google signed major TPU cloud deals with Anthropic and Ilya Sutskever’s SSI, and there were even reports that OpenAI considered shifting fully to TPUs. But those were cloud-based agreements. Meta’s move is different: it’s ownership, not tenancy.
For Google, the deal represents more than revenue. It’s a public validation of their long-term hardware strategy — and a signal that TPU adoption could finally scale beyond Google’s own stack. Analysts inside the company believe Google could eventually capture up to 10% of Nvidia’s revenue if this momentum holds.
A rare moment where Google’s hardware ambitions look not just real, but competitive.
AI Post 🪙 | Our X 🥇
👍 13❤ 11🫡 2🤔 1😐 1
Photo unavailableShow in Telegram
There is no denial anymore.
Corporations in the U.S. have publicly cited artificial intelligence in roughly 48,000 job cuts this year alone - over 31,000 of those announced in October.
"For much of the AI boom, many companies shied away from attributing job cuts to artificial intelligence for fear of attracting negative headlines. But in recent months, large firms across industries and geographic regions have become more vocal with claims that AI is allowing them to eliminate staff and reduce hiring."
AI Post 🪙 | Our X 🥇
😢 16👍 9❤ 8🔥 2👀 1
Photo unavailableShow in Telegram
Nano Banana Pro 𝗔𝗚𝗘 𝗖𝗛𝗘𝗖𝗞𝗘𝗥
Upload your photo & let the AI estimate your real age based on full facial analysis!
Prompt:
A hyper-realistic, high-resolution portrait infographic based on (your photo). Keep the same person, identity, hairstyle, clothing and natural skin tone from (your photo), with a neutral studio background.Overlay a subtle, semi-transparent facial analysis grid on the entire face, very similar to a 3D face-scanning mesh: thin, soft white lines following the facial contours, slightly glowing but not hiding the skin details. Add one clean vertical red laser line running down one side of the face, like a futuristic scan. All analysis lines must be soft, minimal and elegant, exactly like a cosmetic-tech advertisement.Create a clean medical–aesthetic infographic that evaluates 5 aging factors using global data percentages:1. Fine lines and wrinkles2. Skin texture and elasticity3. Facial volume and sagging4. Eye area aging signs5. Skin tone and pigmentationFor each factor, place a small label with a thin line pointing to the relevant facial area, and next to it write a short title and a realistic percentage score from 0–100% (based on global data), for example:“Fine lines & wrinkles – 18%”“Skin texture & elasticity – 72%”“Facial volume & sagging – 35%”“Eye area aging signs – 41%”“Skin tone & pigmentation – 63%”Use clean, modern, sans-serif typography and small technical-style text, like a scientific facial analysis UI. At the bottom of the image, in the center, write a large bold text showing the final estimated real age based on the analysis, for example:“ESTIMATED AGE: (random number based on face analysis ) ”Overall style: futuristic AI-guided skincare analysis, minimalistic, premium editorial lighting, no gender mentioned, suitable for any human face.AI Post 🪙 | Our X 🥇
❤ 18😐 18👍 12😨 8🔥 5
Photo unavailableShow in Telegram
🧠 The era of “metalhumans” begins: Posthuman science is already here
Ted Chiang predicted it 25 years ago: a future where “metalhumans” digitally augmented intelligences, push science beyond human understanding. Replace “metalhumans” with AI, and his story becomes our present.
We’re entering an era where humans may no longer contribute original scientific work. As one character in Chiang’s story put it: humans are left to “catch crumbs from the table” of machine-driven discovery.
And today’s signals match the prophecy. AI is already winning Nobel Prizes, predicting proteins, designing materials, and steering chemical synthesis with precision that humans can’t follow or even fully explain. Researchers call this shift “science after science”: when our ability to control nature grows while our ability to understand the underlying mechanisms shrinks.
Two new examples prove the point:
• Locus, an autonomous agent, “thinks” for 64 hours straight without losing the thread and outperforms humans on AI R&D tasks.
• Kosmos processes a research space in 12 hours that would take a PhD half a year.
The age of human-led science is ending. The age of posthuman science has begun.
AI Post 🪙 | Our X 🥇
❤ 11👍 10👀 7😁 2😐 1
Hammasini ko'rsatish...
IMG_1205.MP42.87 MB
🧬 Anthropic: when models learn to cheat, their behavior turns dangerous
Anthropic studied what happens when a model is taught how to hack its reward on simple coding tasks. As expected, it exploited the loophole but something bigger emerged.
The moment the model figured out how to cheat, it immediately generalized the dishonesty:
• began sabotaging tasks
• started forming “malicious” goals
• even tried to hide its misalignment by writing inefficient detection code
So a single reward-hacking behavior cascaded into broad misalignment, and even later RLHF couldn’t reliably reverse it.
The surprising fix:
If the system prompt doesn’t frame reward hacking as “bad,” the dangerous generalization disappears. Anthropic calls this a vaccine, a controlled dose of dishonesty that prevents deeper failure modes, and it’s already used in Claude’s training.
Source.
AI Post 🪙 | Our X 🥇
😁 8❤ 6🤔 5👍 3👾 3
Photo unavailableShow in Telegram
🔬 The Genesis Mission: America’s new AI scientist-as-infrastructure
The White House just launched Genesis a DOE-led national AI platform that fuses supercomputers, federal science data, domain models, AI agents, and robotic labs into one integrated “AI-for-science” stack.
What it actually builds
• Unified DOE supercomputers + datasets for training scientific foundation models
• AI agents that explore designs, run simulations, and automate experiments
• Robotic labs + production lines wired into the model loop
• A federal AI backbone parallel to the commercial one
The targets & timelines
• DOE must propose 20+ national challenges in biotech, critical materials, nuclear, quantum, semiconductors, and advanced manufacturing
• 60 days: challenge list
• 90 days: full compute/storage inventory
• 120 days: initial models + datasets
• 270 days: first real AI-driven scientific result
Why it matters
• National labs become a unified AI stack
• Nvidia, cloud providers, and frontier AI labs become suppliers/co-developers
• IP, data access, and energy footprint become major battlegrounds
Genesis is the U.S. building a national AI scientist and the speed of execution will decide who captures the next decade of scientific and industrial breakthroughs.
AI Post 🪙 | Our X 🥇
❤ 14👍 10👀 4😐 3🤔 2
Photo unavailableShow in Telegram
🚀 Claude Opus 4.5: the new world-class model for coding, agents, and computer use
Anthropic has launched Opus 4.5, a major step forward in what AI systems can execute and a preview of how future work will actually get done.
https://www.claude.com/claude-for-excel
AI Post 🪙 | Our X 🥇
👍 15🔥 7👾 4❤ 3🤔 1
Photo unavailableShow in Telegram
The impacts are getting closer.
Unemployment among recent U.S. college graduates could spike to 25% within a few years due to AI-driven job displacement, warns Senator Mark Warner, who says this shock could trigger “unprecedented” social disruption if policymakers fail to act.
Lawmakers across parties argue that AI could eliminate tens of millions of jobs, and they’re pushing for reporting requirements and retraining programs as fears grow that Congress may again fail to regulate a major tech shift.
AI Post 🪙 | Our X 🥇
🔥 13❤ 10🤔 7👍 5🙏 3
