🩷 Tinder will soon use AI to read your camera roll and match you better

Tinder is testing a new AI feature called “Chemistry” that analyzes your camera roll with your permission to understand your lifestyle and interests more deeply than profile bios or prompts ever could.

🔸 The system uses computer vision to spot patterns in your photos (like travel, pets, or food) and combines them with short quiz answers to build a personalized match profile.
🔸 The pilot is currently rolling out in New Zealand and Australia, with plans to make it a major feature in Tinder’s 2026 redesign.
🔸 Match Group expects a short-term $14 million revenue dip as it experiments with the rollout, betting that deeper personalization will drive long-term engagement.

If it works, Tinder’s next matchmaker might not be an algorithm guessing from swipes but an AI quietly studying your photo gallery.

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🧠 Anthropic launches “Skills”, modular extensions that let Claude learn on the fly

Anthropic has introduced Skills, a new way for users to extend Claude’s capabilities with custom instructions, noscripts, data, and templates turning the model into a flexible, task-specific assistant without retraining it.

🔸 A Skill can contain rules (“if X then Y”), datasets, documents, or even company-specific resources like brand guidelines or tone templates.
🔸 Claude can automatically select the right Skill for a task or let users toggle between manual, semi-automatic, or fully automatic activation.
🔸 Anthropic also ships default Skill packs for common tasks like data analysis, summarization, and editing, available to all paid Claude users, including API and Claude Code.
🔸 Unlike OpenAI’s separate user-built GPTs, Skills work as modular layers on top of the main model, meaning multiple can run or switch dynamically in a single session.

By blending flexibility with simplicity, Anthropic’s Skills may redefine how users personalize AI not by building new bots, but by teaching one model to think in many modes.

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📹 REAL Video Enhancer launches, upgrade any video by tens of times

A new tool called REAL Video Enhancer has just dropped, promising professional-grade video restoration and upscaling all processed locally on your device.

🔸 Enhances and sharpens footage by tens of times, improving clarity and resolution.
🔸 Compresses files without any visible quality loss, ideal for large projects.
🔸 Removes noise, distortion, and artifacts from low-quality or old recordings.
🔸 Maintains full detail and texture integrity during enhancement.
🔸 Works entirely offline, keeping all content private.
🔸 And it’s completely free to use.

For creators and editors, REAL Video Enhancer could turn grainy clips into studio-quality footage without needing cloud access or paid software.

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💎 45 startups poised for breakout exits in the next decade

CB Insights has identified 45 private startups most likely to achieve major exits IPOs or acquisitions within 5–10 years, driven by shifts in AI infrastructure, strategic partnerships, and vertical specialization.

🔸 Infrastructure over applications: As AI agents replace traditional SaaS, infrastructure companies are becoming the real profit centers. Many founders, ex-Google, Stripe, and Robinhood engineers are building the core systems that others depend on.
🔸 Partnerships drive scale: The strongest startups aren’t going solo. They’re integrating with corporations, creating ecosystems where partnerships are as critical as technology itself.
🔸 Vertical AI wins: With foundation models turning into commodities, value is moving toward startups with domain-specific data and expertise in sectors like health, law, and energy.

The biggest exits of the 2030s may come not from AI chat apps, but from the deep infrastructure and vertical players quietly powering the entire AI economy.

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🎓 Free AI & Python courses with certificates from Google, IBM, and Microsoft

Some of the biggest tech companies are offering free, certified courses to help you build real AI and coding skills no paywall, no subnoscription.

⚙️ Google — Machine Learning Crash Course
• 40+ hours of hands-on exercises, TensorFlow tutorials, and real-world data projects.
• Includes a verified certificate from Google.

🧠 IBM — AI Engineering Professional Certificate
• Covers NLP, ML, and Deep Learning with practical labs and model-building projects.
• Recognized pathway for IBM’s AI roles.

💻 Microsoft — Python for Beginners
• A full video series made by Microsoft engineers.
• Teaches Python step-by-step perfect for coding newcomers.

🤖 DeepLearning.AI — Generative AI with LLMs
• Learn how to build prompts, use GPT models, and apply LLMs in real scenarios.
• Co-created with top AI researchers.

📊 Kaggle Learn — Python & Machine Learning Tracks
• Short, interactive modules on Python, Pandas, ML, and AI foundations.
• Practice directly in your browser no setup required.

These courses don’t just teach,they certify your skills from the companies shaping the AI revolution.

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🚀 Neural networks that can replace your entire business team

These new AI services can handle nearly everything, from writing and coding to design, scheduling, and client communication, helping founders save hundreds of thousands in operating costs.

🔸 Text & code: advanced models now draft full marketing campaigns, blogs, and even production-ready codebases.
🔸 Design & media: AI tools generate realistic product photos, animations, and promo videos in minutes no studio required.
🔸 Ops & support: smart agents manage calendars, emails, and even chat with customers 24/7 with human-level tone and context.

For entrepreneurs, these neural networks don’t just boost productivity, they’re a direct path to scaling lean, fast, and profitably.

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🧠 PewDiePie builds a $20,000 supercomputer to run local AI models

One of the world’s biggest streamers, PewDiePie, has taken a sharp turn from YouTube entertainment to AI independence. After more than a decade of gaming videos and vlogs, he’s now built a personal supercomputer worth around $20,000 to run local large language models (LLMs) entirely offline.

🔸 The setup includes 10 GPUs: 8 custom RTX 4090s (48 GB each) and 2 RTX 4000 Ada cards, powerful enough to handle models like Llama 70B, gpt-oss-120B, and Qwen 245B or up to 64 smaller models simultaneously.
🔸 He even created his own local AI interface and a “council of models” that debate his questions in real time.
🔸 PewDiePie says his goal is simple: keep full control of his data and avoid AI corporations like OpenAI, criticizing them for storing user chats including deleted ones.

From Let’s Plays to local LLMs, PewDiePie’s pivot marks a new era where creators aren’t just using AI, they’re owning it.

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⚡️ Inside Tesla’s first Optimus production line

Tesla has quietly set up its first pilot production line for the humanoid robot Optimus. It’s a small-scale test run for what the company hopes will evolve into a full manufacturing system by 2026, when a larger line is planned.

🔸 The current line assembles and tests robots directly at Tesla’s factory and R&D labs, where Optimus units are already performing basic tasks.
🔸 The company’s target is ambitious, a $20,000 cost price per robot, putting it in the same range as a compact car.
🔸 This phase remains experimental, aimed at refining motion control, battery integration, and safety routines before ramping up.
🔸 Musk’s bet: mass-producing humanoids could one day be as routine as building cars — though testing them next to car lines raises the question, what could possibly go wrong?

Tesla’s robot factory may be small, but symbolically, it marks the moment the company moved from demo mode to industrial ambition.

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📰 Bad news: AI now writes more articles than humans

A new analysis shows that, for the first time, AI-generated articles have overtaken human-written ones on the web. The gap is still small but growing fast.

🔸 Researchers sampled 65,000 web articles (2020–2025) from the CommonCrawl dataset and analyzed them with Surfer AI Detector.
🔸 If over half of an article’s text was flagged as AI-written, it counted as machine-made.
🔸 Cross-checks by publication date helped avoid false positives older pre-ChatGPT articles, for example, were assumed to be human.
🔸 The tipping point came in November 2024, when AI-made content first surpassed human output; after a brief dip, AI now dominates again.

Not all “AI-written” pieces are fully automated, many show signs of human editing or partial rewriting and such content still appears less often in top search results.

Still, the web’s content balance has flipped. The internet’s new authors may not be people, just machines that learned to sound like them.

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